Cursos de IT y software
Los mismos datos para todos, vengan de Udemy o de Coursera: precio, valoración, duración e idioma. 902 cursos encontrados. Afinar la búsqueda
Linux for Network Engineers: Practical Linux with GNS3
It is important for you as a network engineer to learn Linux! Why? There are many reasons including: 1) A lot of network operating systems are based on Linux, or have a Linux shell you can access, or use Linux type commands. I'll show you an example using Cisco, Arista and Cumulus Linux. 2) Network Automation tools such as Ansible don't run the command node on Windows. You are probably going to use Linux with tools such as Ansible, Netmkio, NAPALM and other network automation tools. 3) SDN controllers such as OpenDaylight, ONOS, RYU and APIC-EM run on Linux.You will find that many SDN tools require Linux. 4) DevOps tools such as git work best with Linux. 5) IoT devices typically run Linux 6) A new breed of network devices from companies like Facebook, Microsoft and Cumulus Linux use Linux. There are even more reasons, but make sure you don't get left behind! You as a network engineer start learning Linux. This course teaches foundational Linux knowledge without assuming that you have any Linux experience. Learn practically with GNS3! Learn how to configure Linux networking, how to create users and assign permissions, how to install and run Linux services such as DNS and DHCP. The course uses various GNS3 topologies with devices such as: 1) Linux Docker containers 2) Linux GNS3 QEMU virtual machines 3) Traditional Linux virtual mahcines 4) Network devices - you could use Cisco, Arista, Cumulus Linux or others Do you want to see something else added to the course? Just let me know. I like to get your feedback on ways I can improve the course and add more content that you think is relevant. Networking is changing. Make sure you keep up to date! All the very best! David
Building Data Centers - Maximum Environmental Sustainability
Data centers now account for nearly 4% of global electricity consumption, with U.S. facilities consuming 17 billion gallons of water annually for cooling alone. This Short Course was created to help Sustainability professionals accomplish strategic environmental optimization of data center infrastructure. By completing this course, you'll be able to identify high-impact efficiency opportunities through metrics analysis, evaluate cooling architectures that balance carbon reduction with operational resilience, and develop actionable sustainability roadmaps you can present to leadership tomorrow. By the end of this course, you will be able to: Analyze facility PUE, CUE, and WUE data to isolate high-impact efficiency opportunities within an existing or proposed data center Evaluate cooling and power architecture options to recommend solutions that reduce carbon and water footprints while safeguarding uptime requirements Create a comprehensive sustainability action plan incorporating lifecycle thinking, embodied carbon analysis, and verification protocols aligned to a reporting framework This course is unique because it combines advanced efficiency metrics (PUE, CUE, WUE) with lifecycle carbon analysis and ISO 14064 verification protocols, addressing the full spectrum from operational optimization to ESG reporting compliance. To be successful in this project, you should have a background in facility engineering, sustainability program management, or energy systems at CB3 senior-level expertise.
Mastering Group Policy on Windows Server
Mastering Group Policy on Windows Server applies to Windows Server 2022, 2019, and 2016. This course is designed to teach Group Policy management to those that need to utilize group policy and other Active Directory tools to manage users and computers within their environments or to anyone that wants to able to understand group policy processing and capabilities at an Active Directory level. In this course you will gain a deep understanding for different considerations of Active Directory design that can impact how group policies are applied. You will gain insight into the decisions made to design Forest, Domain and Organizational Unit structures to ensure that they allow group policies to be effectively applied. You will also learn to plan for various considerations- for example, some users accounts of computer accounts may need to be exempt from a group policy object, you will learn the options that are available for that type of scenario. This course will cover the following topics, and more. · Group Policy processing order with Active Directory · Altering the processing order with Active Directory · Software deployment · Central store design · Administrative templates · Security settings · Firewall management · Password polices · User rights assignments · Preferences · App locker restrictions · Folder redirection · Starter GPO design · Scripts · Delegation · Refresh intervals · Troubleshooting GPO issues · Backup/restore/copy/import
AWS Foundations & Cloud Architecture
This course launches the AWS Certified Solutions Architect Specialization with the foundational cloud and AWS knowledge every architect needs. Covering approximately 4 hours and 29 minutes of expert instruction across cloud computing fundamentals, AWS history and global infrastructure, core services overview, and the AWS Essentials chapters, learners build the conceptual foundation for all AWS architecture decisions. Learners benefit by understanding how AWS organizes its global infrastructure, how the core service categories fit together, and how to navigate the AWS Management Console and CLI to begin building cloud solutions. By the end of this course, learners will be able to explain AWS cloud concepts, describe the AWS global infrastructure, and identify the core services used in solutions architect exam scenarios.
Amazon Bedrock AgentCore: Build & Deploy any AI Agent on AWS
Welcome to “Amazon Bedrock AgentCore: Build AI Agents on AWS [HANDS-ON]” — the most practical, hands-on course to master Agentic AI development and deployment on AWS in just 2 weeks. This course is designed for developers, data scientists, and AI enthusiasts who want to learn how to build, deploy, and monitor fully functional Serverless AI Agents (any open-source framework) using Amazon Bedrock AgentCore. You’ll work through real-world, hands-on projects that combine Bedrock primitives, runtime orchestration, memory, observability, and deployment with AWS Lambda and API Gateway. Through step-by-step labs, you’ll: • Build a Personal Vacation Planner AI Agent from scratch (CrewAI Framework) • Deploy your agent using Bedrock AgentCore Runtime, AWS Lambda, API Gateway, and optionally Streamlit for interactive apps. • Enable full Observability with OpenTelemetry and CloudWatch to monitor agent behavior and performance. • Implement memory for context-aware, multi-turn conversations. • Learn about AgentCore Identity and Gateway for production readiness By the end of this course, you’ll have a deep, practical understanding of how to create, operate, and scale Agentic AI systems on Amazon Bedrock AgentCore. • Section 1 - Course Overview – Introduction and learning outcomes • Section 2 - Amazon Bedrock AgentCore Building Blocks - Primitives and the Problem it is trying to solve • Section 3 - Build Agentic AI App from Scratch [Hands-On] – Personal Vacation Planner [on CrewAI] • Section 4 - Bedrock AgentCore Runtime [Hands-On] – Deploy with AgentCore Runtime + Lambda + API Gateway • Section 5 - Bedrock AgentCore Observability [Hands-On] – Monitor with OpenTelemetry & CloudWatch • Section 6 - Amazon Bedrock AgentCore Identity & Gateway [Hands-On]– Setup AgentCore Gateway & invoke Agent Tools • Section 7 - Amazon Bedrock AgentCore Memory [Hands-On] – Add context and session memory • Section 8 - Refresher: Agentic AI, CrewAI, and MCP IMPORTANT << Learning Path: GenAI Developer / Architect on AWS >> Many learners ask how to switch their career to an AWS Generative AI Developer or Architect and which sequence of my Udemy courses they should follow. Here is some guidance based on my experience working in the IT industry. My GenAI/Agentic AI courses are divided into two tracks • Hands-On learning to build real world skills required in the IT industry (Most important) • Certification preparation to help you pass the certification exam (Good to have) << Hands-On Courses >> 1. Hands-On Course 1 (Beginner) - Amazon Bedrock, Amazon Q & AWS Generative AI [Hands-On] Start here if you’re new to GenAI & Amazon Bedrock. 2. Hands-On Course 2 (Intermediate) - Build Production Ready AI Agents on AWS – Bedrock, CrewAI & MCP Take this after Course 1 - Focused on Agentic AI but will be easier to understand if you have taken Course 1 3. Hands-On Course 3 (Advanced) - Amazon Bedrock AgentCore : Deploy AI Agents on AWS This is the advanced course and focused on how to deploy, scale, and operate AI agents in Production. Recommend to take after Course 1 & Course 2. << AWS GenAI Certification Path >> 1. Certification Course 1 : AWS Certified AI Practitioner (AIF-C01) – Beginner to Advanced · Take after Step 1, or · In parallel with Step 2 Outcome You pass AWS Certified AI Practitioner (AIF-C01) and understand GenAI concepts AWS expects. 2. Certification Course 2 : AWS Certified Generative AI Developer Professional (Coming Soon)
Microservices Architecture and Communication Patterns
This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course will guide you through the essentials of microservices architecture and communication patterns. You will explore key communication strategies, such as synchronous and asynchronous communication, RESTful APIs, GraphQL, and gRPC. The course dives into advanced patterns like API Gateways, service-to-service communication, and event-driven architectures, preparing you to design and implement scalable microservices systems. You will also delve into data management within microservices, learning about database patterns like Database-per-Service, polyglot persistence, and CQRS. The course offers practical applications, including handling real-world problems like network traffic issues, database bottlenecks, and long-running operations in microservices. This course is ideal for software developers and engineers who have a basic understanding of system architecture. It’s perfect for those wanting to dive into microservices and their complex communication and data management patterns. By the end, you’ll be ready to build robust microservices systems with efficient communication and data handling strategies. By the end of the course, you will be able to design and implement microservices using various communication patterns, select appropriate databases for microservices, and optimize data management techniques, including CQRS and Event Sourcing.
Communication Series P1 : UART, SPI and I2C in Verilog
This comprehensive course is meticulously designed to cater to a broad audience, ranging from beginners who are just stepping into the world of digital design and hardware description languages (HDLs) to experienced FPGA/ASIC developers looking to deepen their expertise. The central aim of this course is to equip participants with a thorough mastery of digital communication interfaces, employing Verilog as the primary tool. Regardless of your prior experience in the field, this course offers something valuable. Beginners will find a structured and gradual introduction to the complex world of digital communication interfaces and Verilog. The course spans a comprehensive curriculum that encompasses three fundamental digital communication protocols: Serial Peripheral Interface (SPI), Universal Asynchronous Receiver-Transmitter (UART), and Inter-Integrated Circuit (I2C). Each of these protocols plays a critical role in modern electronics and embedded systems, and mastering them is vital for both aspiring and experienced engineers. In summary, this course is a transformative journey that welcomes participants at all skill levels into the world of digital communication interfaces and Verilog. It equips you with the skills, knowledge, and confidence needed to excel in the dynamic and ever-evolving field of digital design and embedded systems. Whether you're taking your first steps or seeking to advance your career, this course provides a robust foundation for your success.
MS-700 Microsoft Teams Admin & Management Exam Guide
This course provides a comprehensive guide to managing Microsoft Teams, focusing on both administration and configuration strategies vital for modern workplace collaboration. Professionals will learn how to effectively plan, configure, and govern Teams environments to ensure optimal performance and security. Learners will gain hands-on skills in managing Teams clients, channels, chats, meetings, and external collaboration. The course also covers network planning, compliance, and reporting, enabling students to achieve practical outcomes and excel in the MS-700 certification exam. What sets this course apart is its balance of theory and real-world application. You will not only understand Microsoft Teams’ core concepts but also practice troubleshooting, managing apps, and implementing governance strategies used in enterprise environments. This course is ideal for IT professionals, system administrators, and collaboration specialists looking to strengthen their Microsoft Teams management skills. Basic familiarity with Microsoft 365 administration is recommended but not required. Based on the book, MS-700 Managing Microsoft Teams Exam Guide, by Nate Chamberlain and Peter Rising.
Complete ASIC Design Flow: VLSI From Idea to Silicon
USE PROMO "PAY.13 " No prior VLSI experience? No problem. This course is designed to take you from absolute beginner to an engineer capable of designing a complete, complex system chip—all the way from digital logic to a tape‑out ready GDSII file. Most courses teach isolated pieces: a bit of Verilog, some timing, or a tool. This one is different. We walk you through the entire ASIC design flow in a structured, step‑by‑step way, assuming no background in chip design. You’ll start by understanding what a transistor is and how digital circuits work. Then, you’ll learn Verilog HDL through dozens of labs and assignments, progressing from simple counters to a 16‑bit ALU, register files, and finite state machines. But front‑end RTL is only the beginning. We then dive into the critical implementation stages: TCL scripting to automate flows, Static Timing Analysis (STA) to fix setup/hold violations, low‑power design techniques used in modern mobile chips, and logic synthesis where RTL is transformed into gates. You’ll also master Clock Domain Crossing (CDC) with asynchronous FIFOs, Design for Test (DFT) with scan chains, and formal verification to ensure equivalence. All of this culminates in a final system assignment—a UART‑based subsystem with a register file and ALU, which you then take through the physical design (PnR) flow using Cadence tools, ending with GDSII export. By the end, you will have built a chip from the ground up, with a portfolio project that proves your skills.
K8sGPT Essentials - Unlocking Kubernetes Insights with AI
This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you will explore K8sGPT, a powerful tool designed to enhance Kubernetes management with AI-powered insights. You will learn to leverage K8sGPT's functionalities to streamline workflows, analyze data, and gain valuable insights into Kubernetes environments. By integrating AI into your Kubernetes processes, this course aims to equip you with the tools to optimize your cloud-native infrastructure. The journey begins by introducing you to the core concepts and the significance of K8sGPT in Kubernetes management. As you progress, you’ll learn how to set up K8sGPT in your environment, including installing it via CLI or the In-Cluster Operator. Detailed demonstrations will show you how to use commands, integrate K8sGPT with other systems, and analyze real-time issues. This course is perfect for IT professionals, Kubernetes administrators, and DevOps engineers looking to leverage AI to improve their Kubernetes workflows. Basic knowledge of Kubernetes is recommended, but the course is designed to be beginner-friendly and progressively builds skills. By the end of the course, you will be able to set up K8sGPT, analyze Kubernetes data, integrate it with various systems, and use AI-driven insights for real-time issue resolution.
Complete Salesforce Certified Platform Administrator Course
New Exam Structure Practice Test Added - This course now contains the latest exam structure weighted practice test including the 8 knowledge areas of the current exam guide and covers Agentforce topics. The amount of information and concepts that you need to understand in order to pass the Administrator exam is massive. This course is the most in-depth and complete course you'll find and I encourage you to not settle for a lightweight course that glosses over or entirely skips key concepts that you need to know. I have authored a book for this certification by a major tech publisher, so you can trust that I have thought through your learning journey thoroughly. I don't teach trivia - I teach conceptually, so that you succeed on the exam and in your career. I am the best-selling Saleforce instructor on the Udemy platform because I get results for you and know and understand the platform. There are no shortcuts, so don't be fooled by someone selling you a happy/easy path. You are on the correct course right now and here you will learn all that you need and be well thoroughly equipped for the exam. Also, there is a better way to learn Salesforce now. And that better way is leveraging the power of AI to deepen and broaden your Salesforce learning and understanding. I am the only Salesforce instructor teaching how to use ChatGPT to prepare for certification exams. You can now create your own practice test questions, study guides, flash cards, and even get massive help on your resumes and interview prep, LinkedIn presence and more, for free, with AI. Rather than trying to hide this new reality from you, I am embracing this revolutionary technology to take your learning and potential earning to the next level. That is why I recorded a brand new and updated version of this course to leverage the power of ChatGPT to help you prepare for and pass the Salesforce Certified Platform Administrator Exam in record time! This course includes a ChatGPT Prompt Library. You can copy and paste all of the prompts I use inside this course into your own free ChatGPT account. This ChatGPT Prompt Library will help you to learn the now in-demand skills for Prompt Engineering! With the power of ChatGPT you can now do amazing things such as creating apex code to mass update records, create formula fields, validation rules, and so much more. I have worked on the Salesforce platform for well over a decade. I have helped hundreds of thousands of students attain one or multiple Salesforce certifications. I have been teaching on the Udemy platform since 2016 and this is my fourth full revamp of this course. I continually work in the latest Salesforce release to remain current and am constantly updating this course. In addition to the hundreds of in-depth video lessons inside this course, you will also find a Practice Test at the end of this course. It contains 60 questions, and is timed at 90 minutes. You receive Section Level Feedback, just like in the real test. I provide further details and explanations as to why your answers are either correct or incorrect. "I'm at (Salesforce's) Destination Success right now and your course goes more in-depth than the classroom courses here, and for 1% of the cost!" - Ben L. The Complete Salesforce Platform Administrator Certification Course is for anyone interested in passing the Administrator Certification exam. This course is designed with the new Salesforce administrator in mind. I cover each section of the Administrator Study Guide in-depth, giving examples in the interface, as well as hands-on experience so you can apply the concepts you are learning. After 90,000+ Survey ratings for my courses, the students have spoken: "Are you learning valuable information?" 99.6% answered YES "Are the explanations of the concepts clear?" 99.8% answered YES "Is the instructor knowledgeable about the topic?" 99.9% answered YES If you are interested in becoming a Salesforce Platform Admin, take this course. Here are some recent reviews and feedback this course has received: "Mike, your course was great! I took the Admin Essentials class by Salesforce in which my company paid over 2000 dollars for in person live training and the training did not come close to anything on the exam. Your course helped me to get properly prepped and covered all the pertinent aspects of the 201 exam in which I passed." ~ Harris L. "Very well presented, excellent video quality, incredibly easy to follow. Covers more than what is necessary (not a criticism), Creator is a legend, I've contacted him multiple times and had a response within 5 minutes. Could not rate any higher ! Definitely the best choice out of the courses offered for this qualification. Amazing." ~ Paul R. "I'm amazed that a training program of such great quality is available for such a reasonable price! Mike is a wonderful trainer and the material covered is excellent!" ~ Rick A. "Mike is awesome and learning so much so far! Mike thanks so much for the really awesome course! I am sure that when I take the admin exam soon that I will pass with flying colors!!" ~ James W. "This is the best course so far. Thank you for your video." ~ Christian M. "I have been using SF as a rep, not an admin and while I already had a working knowledge of the product and it's capabilities this is very insightful material and I have learned a lot of new things." ~ Alexis K.
Information Systems Implementation and Business Resilience
Information Systems Implementation and Business Resilience is the second course of Exam Prep: Certified Information Systems Auditor (CISA) Specialization. Database concepts, including relational models, controls, and DBA responsibilities, are also covered. The course concludes with business continuity and disaster recovery planning, including backup strategies, system resiliency, and RTO/RPO analysis, equipping learners to ensure organizational stability and preparedness in the face of disruptions. The course is divided into three modules, and each module is further segmented into Lessons and Video Lectures. This course facilitates learners with approximately 2:00-2:30 Hours of Video lectures that provide both Theory and Hands-On knowledge. Also, Graded and Ungraded Quizzes are provided with every module to test the ability of learners. - Module 1: Information Systems Implementation - Module 2: Information Systems Operations - Module 3: Business Resilience This course is designed for IT auditors, audit managers, security professionals, and consultants. Their current job roles often involve assessing IT and business systems, managing risks, ensuring compliance, and implementing controls. By the end of the course, learners will be able to: - Manage IT Assets, Operations, and Service Levels. - Understand Database Concepts, Controls, and Administration. - Grasp Business Continuity and Disaster Recovery Planning.
The Agentic AI Engineering Masterclass 2026
In this hands-on masterclass, you’ll learn how to design, build, and deploy next-generation AI agents that combine memory, tools, collaboration, and automation to solve real-world problems. Starting with the OpenAI Agents SDK, you’ll explore how to create simple agents and gradually extend them with advanced features such as persistent memory, guardrails, and smooth handoffs between workflows. You’ll then dive into multi-agent systems, where specialized agents, like researchers, analysts, and writers, work together, passing context and outputs to build complex deliverables. Along the way, you’ll learn how to orchestrate these systems with manager functions, enforce ethical and domain boundaries with guardrails, and design creative pipelines for use cases from market research to advertising campaigns. The course introduces multiple frameworks for building production-ready agentic workflows. You’ll explore AutoGen for multi-model collaboration, LangGraph for modular pipelines connected to user interfaces, and CrewAI for advanced orchestration. You’ll also learn how to extend agents with custom tools, from Python code execution for data analysis to classical machine learning models like linear regression, random forest, and XGBoost. You’ll gain practical experience with the Model Context Protocol (MCP), enabling agents to interoperate with standardized external services, and learn how to build and deploy MCP tools using Gradio. Finally, you’ll see how low-code platforms like n8n can bring everything together into seamless automation flows, integrating Gmail, Google Sheets, Google Calendar, and AI models to create complete end-to-end systems. By the end of the course, you’ll have the skills to: • Build AI agents with memory, tools, and reasoning capabilities. • Orchestrate multi-agent workflows for research, analysis, and creative tasks. • Integrate guardrails, handoffs, and oversight to ensure safe, reliable outputs. • Deploy advanced agentic workflows across AutoGen, LangGraph, CrewAI, and MCP. • Automate business processes with low-code tools like n8n connected to real-world apps. Whether you’re a developer, data scientist, or business innovator, this course equips you with the full toolkit to design AI systems that collaborate, automate, and scale in production.
Smart Analytics, Machine Learning, and AI on Google Cloud
Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
NIST AI Risk Management Framework (RMF) Masterclass - 2026
The NIST AI Risk Management Framework (RMF) Masterclass is an essential course for professionals navigating the complex landscape of AI risk management. With the rapid integration of artificial intelligence into various business sectors, understanding and managing the unique risks associated with these technologies is crucial. This course offers an in-depth exploration of the National Institute of Standards and Technology's AI Risk Management Framework (AI RMF), providing practical insights for its application in corporate environments. What You Will Learn • Comprehensive understanding of NIST's AI RMF, its structure, and key concepts. • Techniques to identify, assess, and manage AI-related risks within your organization. • Case Studies to help you understand the framework in practical settings • Strategies to align AI risk management with legal, regulatory, and organizational goals. Course Outline Introduction to NIST AI RMF • Understanding the NIST AI RMF and its relevance in today's corporate landscape. • Key principles and structure of the AI RMF. AI Risks in the Corporate Environment • Overview of unique AI risks and their implications in business settings. • Detailed analysis of how to mitigate AI risks Implementing AI RMF in Organizations • Step-by-step guide to applying AI RMF in a corporate setting. • Case studies and practical examples of AI risk management. Who Should Take This Course This course is ideal for professionals involved in AI implementation and risk management, including: • Risk Management Professionals • Cybersecurity Professionals • Privacy Professionals • Business Executives and Decision-Makers • Compliance and Regulatory Affairs Specialists • Anyone interested in AI risk management frameworks Prerequisites A basic understanding of AI technologies and risk management is recommended, but not mandatory. Instructor A multi-award winning, information security leader with over 20+ years of international experience in cyber-security and IT risk management in the fin-tech industry. Winner of major industry awards such as CISO of the year, CISO top 30, CISO top 50 and Most Outstanding Security team. Taimur's courses on Cybersecurity and AI have thousands of students from all over the world. He has also been published in leading publications like ISACA journal, CIO Magazine Middle East and published two books on AI Security and Cloud Computing ( ranked #1 new release on Amazon )
Amazon EMR Getting Started
Amazon EMR is a managed cluster solution that can make it more efficient to run big data frameworks, such as Apache Hadoop and Apache Spark, on Amazon Web Services (AWS) to process and analyze vast amounts of data. In this course, you will learn the benefits and technical concepts of Amazon EMR. If you are new to the service, you will learn how to start using Amazon EMR through a demonstration using the AWS Management Console and AWS Command Line Interface (AWS CLI). You will learn about the native architecture and how the built-in features can help you process data for analytics purposes and business intelligence workloads.
Claude Code Beginner Crash Course: Claude Code In a Day
This course contains the use of artificial intelligence :) Welcome to the the Claude Code Beginner Crash Course! This curriculum is designed for professionals new to Claude Code and assumes you have a solid background in software engineering and are proficient in Python, Next JS and generative ai. We will be working extensively in the terminal and using the Cursor IDE for seamless integration, but you can follow along with any editor that supports the Claude Code extension. This course is for software developers, AI engineers, and data scientists who want to move beyond simple chat interactions and harness the full power of Claude Code to build automated, context-aware, and secure development workflows. What You Will Learn in Claude Code Claude Code is more than just a coding assistant; it's a powerful, extensible platform for creating AI-driven development tools. This course will teach you to master its core architecture, from basic commands to building complex, multi-agent systems. Architecture and Core Concepts • Slash Commands: Go beyond basic prompting and learn to control every aspect of Claude Code's behavior, context, and configuration directly from your terminal. • Persistent Memory (CLAUDE .md): Learn to give Claude a long-term memory. We'll cover how to create and manage user, project, and local memory files to store preferences, coding standards, and architectural context that persists across sessions. • Hooks: Unlock the ultimate automation tool. You will learn to create shell commands that trigger at specific events in Claude's lifecycle, enabling you to automate everything from running tests to formatting code and even calling other AI agents. • Sub-Agents: Design and build a team of specialized AI assistants. You'll learn how to create and manage sub-agents, each with its own unique context, tools, and system prompt, to handle specific tasks like code reviews, debugging, or security analysis. • Agentic Coding Principles • Claude Code Plugins • Claude Code Output Styles • Course syllabus covers: Claude Certified Architect - Foundations Key Capabilities and Topics Covered This course provides a deep dive into practical, real-world applications of Claude Code: • Advanced Context Engineering: Master the art of keeping Claude focused and efficient by managing its context window with /clear, /compact, and automated memory systems. • Multi-Agent Workflows: Design and implement complex workflows where specialized sub-agents collaborate to solve problems, orchestrated by Hooks and a central Claude instance. • Tool Use and Permissions: Securely grant Claude access to your local tools and scripts, and manage what it can and cannot do with granular permission controls. • IDE Integration: Set up and optimize the Claude Code extension in your IDE for a seamless workflow that combines terminal power with in-editor diffs and context. • Cost and Performance Optimization: Understand the tokenomics of Claude Code and learn best practices for managing cost and ensuring high-performance interactions. • Real-World Projects: Apply everything you've learned in hands-on projects, from building a custom linter with Hooks to creating a multi-agent system for automated code reviews. Who this course is for: • Advanced GenAI Users: Users who are ready to go beyond the chat interface and leverage the full programmatic power of Claude Code. • AI Engineers: Professionals looking to build and deploy sophisticated, agentic workflows directly within their development environment. • Application Developers: Software engineers who want to automate repetitive tasks and integrate a deeply context-aware AI partner into their daily workflow. • Data Scientists: Practitioners aiming to automate complex data analysis, scripting, and pipeline generation tasks.
Security Operations
Welcome to course 5 of 5 of this Specialization, Security Operations. This course focuses our attention on the day-to-day, moment-by-moment active use of the security controls and risk mitigation strategies that an organization has in place. We will explore ways to secure the data and the systems they reside on, and how to encourage secure practices among people who interact with the data and systems during their daily duties. After completing this course, the participant will be able to: Explain concepts of security operations. - Discuss data handling best practices. - Identify important concepts of logging and monitoring. - Summarize the different types of encryption and their common uses. - Describe the concepts of configuration management. - Explain the application of common security policies. - Discuss the importance of security awareness training. - Practice the terminology of and review the concepts of network operations. Agenda Course Introduction Module 1: Understanding Data Security and Encryption Module 2: Controls and Asset Management Module 3: Best Practice Security Policies Module 4: Understand Security Education Training and Awareness (SETA) Module 5: Security Operations Review Final Assessment This training is for IT professionals, career changers, college students, recent college graduates, advanced high school students and recent high school graduates looking to start their path toward cybersecurity leadership by taking the Certified in Cybersecurity entry-level exam. There are no prerequisites to take the training or the exam. It is recommended that candidates have basic Information Technology (IT) knowledge. No work experience in cybersecurity or formal education diploma/degree is required.
Cyber Security SOC Analyst Training - SIEM (Splunk)
Cyber Security SOC analyst training Splunk (SIEM) For those who are aspiring to certify themselves as well as enhance their knowledge and skills on becoming a SOC analyst. This course is specially designed for all level of interested candidates who wants get in to SOC. Work of a SOC analyst? A Security Operation Center Analyst is primarily responsible for all activities that occur within the SOC. Analysts in Security Operations work with Security Engineers and SOC Managers to give situational awareness via detection, containment, and remediation of IT threats. With the increment in cyber threats and hacks, businesses are becoming more vulnerable to threats. This has significantly enhanced the importance of a SOC Analyst. For those in cybersecurity, it can be a dynamic role. SOC Analysts cooperate with other team members to detect and respond to information security incidents, develop and follow security events such as alerts, and engage in security investigations. Furthermore, SOC Analysts analyze and react to undisclosed hardware and software vulnerabilities. They also examine reports on security issues and act as ‘security advisors’ for an organization. This course helps you to learn and implement those strategies and with training provided. This will in turn help you play a significant role in defending against cyber threats and keeping sensitive information secure.
استخدام Git + GitLab فى مشاريع تطوير البرمجيات
في نهاية هذا المشروع هتكون قادر تنشئ repository على GitLab باستعمال أى command line terminal، وترفع عليها أى تغييرات فى مشروعك. خلال المشروع هنعمل repository ونتعرف على commands كتيرة فى Git وازاى ممكن نستعمل Git لما نكون شغالين مع team أو حتى لو شغالين لوحدنا. المشروع دا لا غنى عنه لأى حد بيتعلم برمجة وناوى يشتغل كـDeveloper، والمشروع للمبتدئين لأننا هنمشى خطوة بخطوة كأنك أول مرة بتسبتعمل Git. Git حاجة مهمة جداً أى Software Developer محتاج يكون ملم بيها وعارفها كويس جداً، وهيكون حاجة مطلوبة منكم فى عدد كبير جداً من الشركات
IT System Engineer & Cloud System Administration
The IT System Engineering and Cloud System Administration course is designed to provide participants with comprehensive knowledge and hands-on skills required to excel in the field of managing and maintaining modern IT systems and cloud-based infrastructures. This course offers a deep dive into the fundamental concepts, best practices, and advanced techniques necessary for effective IT system engineering and cloud system administration. Course Objectives: In this course, you will get hands-on experience while completing the following tasks: 1. Fundamental IT System Concepts: Understand the foundational principles of IT systems, including hardware, software, networking, and security. 2. Operating Systems Mastery: Gain proficiency in installing, configuring, and managing various operating systems, including Windows Servers, Windows Client Operating System and virtualization technologies 3. Cloud Computing Basics: Explore the fundamentals of cloud computing, including cloud models (IaaS, PaaS, SaaS), virtualization, and cloud service providers (e.g. Azure). 4. Cloud Infrastructure Management: Acquire skills to deploy, monitor, and manage resources in cloud environments, including virtual machines, storage, and networking components. 5. Security and Compliance: Understand IT security best practices, encryption, access controls, and compliance considerations when working with IT systems and cloud services. 6. Troubleshooting and Problem Solving: Develop the skills to diagnose and resolve complex IT issues in both on-premises and cloud environments. 7. Introduction to Microsoft Intune: Understand the core concepts, features, and benefits of Microsoft Intune as a unified endpoint management solution. 8. Device Enrollment and Configuration: Learn how to enroll and configure various types of devices (Windows, iOS, Android) into Intune for seamless management. 9. Introduction to Active Directory: Understand the core concepts, components, and architecture of Microsoft Active Directory and its role in network infrastructure. 10. Domain Services and Domain Controllers: Learn how to create and manage Active Directory domains, domain controllers, and trust relationships. 11. User and Group Management: Acquire skills to create, manage, and maintain user and group accounts, including user authentication and access control. 12. Group Policy Management: Explore the creation and application of Group Policy Objects (GPOs) for centralized configuration, security policies, and software deployment. 13. Organizational Units (OUs): Understand how to design and implement OUs to organize and manage network resources efficiently. 14. DNS and Active Directory Integration: Understand the integration between Active Directory and DNS for proper name resolution and network functionality. 15. Active Directory Trusts: Explore the setup and management of different types of trusts, including cross-forest and external trusts. 16. Introduction to WSUS: Understand the importance of WSUS in maintaining system security, patch management, and software updates within a Windows network. 17. WSUS Deployment Planning: Learn how to plan for WSUS deployment, including server placement, network considerations, and integration with existing infrastructure. 18. WSUS Installation and Configuration: Acquire skills to install and configure the WSUS server, including database setup, synchronization options, and proxy server integration. 19. Target Groups and Computer Groups: Gain proficiency in organizing computers into target groups and computer groups for more efficient update management. 20. Use ChatGPT, DeepSeek, and Copilot to troubleshoot common IT problems on Windows, Linux, and network systems. And much more. Course Format: The course consists of a combination of lectures, hands-on labs, practical exercises, and real-world scenarios. Participants will have access to a dedicated lab environment to gain practical experience in configuring and managing IT systems and cloud services. The course culminates in a final project where participants will design and implement a comprehensive IT system using cloud resources. By the end of this course, participants will be well-equipped to take on roles as IT system engineers and cloud system administrators, capable of effectively managing and optimizing IT infrastructure in both traditional and cloud-based environments.
Implementing MPLS Traffic Engineering
Unlock the full potential of your networking knowledge with our comprehensive course on MPLS Traffic Engineering (TE). This course offers a deep dive into the essential components of MPLS TE, guiding you through traffic tunnel attributes, tunnel path discovery with link-state routing protocols, and tunnel setup signaling utilizing RSVP. You’ll gain hands-on experience with commands, syntax, and practical techniques for both implementing and monitoring MPLS TE tunnels, while exploring advanced topics like link attribute propagation with IGPs and constraint-based path computation. Additionally, you’ll develop expertise in path setup, path maintenance, and the assignment of traffic to MPLS TE tunnels. What sets this course apart is its focus on real-world configuration and troubleshooting: you will not only learn foundational theory, but also practice with industry-relevant commands and monitoring tools to ensure TE functionality in live MPLS networks. By the end, you’ll have the skills to confidently design, implement, and maintain MPLS TE tunnels, making you a valuable asset in any advanced networking environment.
The Complete Cyber Security Course : Hackers Exposed!
Learn a practical skill-set in defeating all online threats, including - advanced hackers, trackers, malware, zero days, exploit kits, cybercriminals and more. Become a Cyber Security Specialist - Go from a beginner to advanced in this easy to follow expert course. Covering all major platforms - Windows 7, Windows 8, Windows 10, MacOS and Linux. This course covers the fundamental building blocks of your required skill set - You will understand the threat and vulnerability landscape through threat modeling and risk assessments. We explore the Darknet and mindset of the cyber criminal. Covering malware, exploit kits, phishing, zero-day vulnerabilities and much more. You will learn about the global tracking and hacking infrastructures that nation states run. Covering the NSA, FBI, CIA, GCHQ, China’s MSS and other intelligence agencies capabilities. You will understand the foundations of operating system security and privacy functionality. A close look at the new Windows 10 privacy issues and how to best mitigate them. There is a complete easy to follow crash course on encryption, how encryption can be bypassed and what you can do to mitigate the risks. Master defenses against phishing, SMShing, vishing, identity theft, scam, cons and other social engineering threats. Finally we cover the extremely important, but underused security control of isolation and compartmentalization. Covering sandboxes, application isolation, virtual machines, Whonix and Qubes OS. This is volume 1 of 4 of your complete guide to cyber security privacy and anonymity.
Creating Routing Policies to Handle Traffic with AWS Route53
In this 2-hour long project based course, we will look at how to handle and divert website traffic to multiple servers using Routing Policies in AWS Route 53. We will look at how you can configure different types of Routing Policies. We will start off with Simple Routing Policy which can be used to divert traffic to multiple servers / IP’s randomly. Then we will look at Weight Routing Policy which allows you to split your traffic based on different weights assigned. We will then move on to Latency-based Routing which allows you to route your traffic based on the lowest network latency for your end user (fastest response time). Then we will learn to create an active/passive set up using Failover Routing Policy where you can have a primary website and a secondary Disaster Recovery site.. We will then look at Geolocation Routing Policy which will send your traffic to various servers based on the Geographic location of your users which can for example allow for custom sites based on user location. Finally, we will see Multi-Value Answer Policy which lets you configure Route53 to return multiple values along with health checks. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
IT Asset Management (ITAM) - Hardware Asset Management (HAM)
Are you an IT Professional who wants to learn about IT Asset Management? Or maybe you already know about IT Asset Management and want to brush up you're existing skills? If so, then this course is perfect for you! In this course you will learn about: • What is IT Asset Management • Role of ITAM in an Organization • Starting up an ITAM program • Executive Buy In • The Asset Repository • Asset Procurement • Install Move Add Change (IMAC) Process • The Asset Lifecycle • Asset Tagging • Vendor Management • ITAM Maturity Model • Return Merchandize Authorization (RMA) • Configuration Management Database (CMDB) • Total Cost of Ownership (TCO) • Managing your IT Asset Inventory • And many more useful topics Careers in the IT Asset Management industry are proving to be more and more common, so the need for solid skills and education is proving to be a basic requirement for all ITAM professionals. Did you know that the average salary for an IT Asset Manager in the United States is $110k? This course will enable you to kick-start your career in IT Asset Management. The course also comes free with the following: • ITAM glossary • Should You Track It? Decision Diagram • A free digital copy of my book "An IT Manager's Guide to Hardware Asset Management" • Asset Check-out form • Asset Return form • Sample Purchase Order document ITIL 4 also places a heavy focus on IT Asset Management, so maybe you are ITIL certified, and want to greater expand your knowledge into ITAM. This course focuses more on Hardware Asset Management (HAM), rather than Software Asset Management (SAM). But with that being said, this course is an excellent segway into the world of SAM. Reviews from some students that have already taken this course: ★★★★★ “...Very informative and broken down into easy to digest sections, with thorough explanations of terms and concepts. The teacher has a mastery of the material and provides helpful examples to explain concepts.” – Stuart ★★★★★ “This was a very comprehensive course - it covered all the topics expected in an Asset Management program. It was a really good refresher for me.” - Doreen Study this course today and elevate you're career to the next level! Maybe you're interested in taking the Certified Hardware Asset Management Professional (CHAMP) course by IAITAM, but don't want to pay the hefty price? Take this course today and learn the SAME information, and much more for 100x less! This course is perfect for you if you use any of the following IT Asset Management tools, and want to understand ITAM even more: • ServiceNow • Cherwell Asset Manager (CAM) • IBM Maximo • Flexera • SysAid • Manage Engine • Ivanti • SNOW • Asset Panda • FreshService • Samanage • Device42 • AssetCloud • Snipe IT • Jira ServiceDesk • Remedy • Spiceworks • Landesk • HP Asset Manager This course is also great studying material for the Hardware Asset Management Specialist Certification exam by ITAM Institute.
Encoder-Decoder Architecture - 한국어
이 과정은 기계 번역, 텍스트 요약, 질의 응답과 같은 시퀀스-투-시퀀스(Seq2Seq) 작업에 널리 사용되는 강력한 머신러닝 아키텍처인 인코더-디코더 아키텍처에 대한 개요를 제공합니다. 인코더-디코더 아키텍처의 기본 구성요소와 이러한 모델의 학습 및 서빙 방법에 대해 알아봅니다. 해당하는 실습 둘러보기에서는 TensorFlow에서 시를 짓는 인코더-디코더 아키텍처를 처음부터 간단하게 구현하는 코딩을 해봅니다.
CrowdStrike: Zero to Falcon Admin
Master the Falcon Platform from an Administrative Perspective This course is designed to provide learners with an in-depth understanding of CrowdStrike/EDR, a powerful endpoint security tool. Participants will learn how to install and configure CrowdStrike/EDR, manage hosts, create and manage prevention policies, customize IOAs, manage exclusions and quarantines, and troubleshoot issues. Module 1: What is CrowdStrike/EDR • Introduction to CrowdStrike/EDR • Understanding Endpoint Detection and Response (EDR) • Key features and benefits of CrowdStrike/EDR Module 2: Users and Roles • User and role management in CrowdStrike/EDR • Understanding permissions and access levels • Best practices for user and role management Module 3: Installation • CrowdStrike/EDR installation prerequisites • Installing CrowdStrike/EDR on endpoints • Post-installation configurations and best practices Module 4: Troubleshooting • Troubleshooting common issues with CrowdStrike/EDR • Best practices for effective troubleshooting Module 5: Uninstalling & Sensor updates • Uninstalling CrowdStrike/EDR from endpoints • Updating CrowdStrike/EDR sensors • Best practices for sensor management Module 6: Host management • Managing hosts using CrowdStrike/EDR • Understanding host groups and policies • Best practices for host management Module 7: Prevention policies • Creating and managing prevention policies in CrowdStrike/EDR • Understanding policy rules and configurations • Best practices for policy management Module 8: Custom IOAs • Creating custom Indicators of Attack (IOAs) in CrowdStrike/EDR • Understanding IOA rules and configurations • Best practices for custom IOA management Module 9: Exclusions and Quarantines • Managing exclusions and quarantines in CrowdStrike/EDR • Understanding exclusion and quarantine rules and configurations • Best practices for exclusion and quarantine management Target audience: IT professionals, cybersecurity professionals, system administrators, and anyone interested in learning how to manage and secure endpoints using CrowdStrike/EDR.
Salesforce on AWS - From Basics to Business Innovation-LATAM
A lo largo de este curso, examinará la propuesta de valor de la integración de Amazon Web Services (AWS) y Salesforce. Se centrará en cómo esta integración permite la agilidad empresarial, mejora las experiencias del cliente e impulsa la excelencia operativa. Cada lección construye sus conocimientos progresivamente. Comenzará con conceptos básicos antes de explorar aplicaciones prácticas. Al comprender estos patrones de integración, estará mejor equipado para evaluar cómo esta asociación podría beneficiar a su organización. Al final de este curso, comprenderá claramente cómo funciona la integración de Salesforce y AWS, el valor comercial que ofrece y los tipos de problemas que resuelve. Este conocimiento le ayudará a identificar oportunidades para implementar estas tecnologías en su propia organización.
Masterclass - CRISC Exam (Updated 2026)
(Note: CISA Exam is conducted by ISACA. This course is private course and not affiliated with ISACA) This course is aligned with ISACA's CRISC Review Manual (8th Edition) and updated in 2026. Please note that objective of this course is to support and supplement the content of the ISACA's official resources. This course is not meant to replace CRISC Review Manual and Question, Answer and Explanation Manual. Candidates are strongly advised to use ISACA's official resource as prime resource to study for CRISC exam. This course will help you to decipher the technicities used in official resources. This course is designed on the basis of official resources of ISACA. It covers all the 4 domains of CRISC Review Manual. Topics are arranged segment wise and aligned with latest CRISC Review Manual. Course is designed specifically for candidates from non-technical background. Video contents are designed after considering three major aspects: (1) Whether content has capability to engage the audience throughout? (2) Whether content is able to convey the meaning of CRISC Review Manual in a effective manner. (3) Whether video has capability to make audience understand and retain the key aspects for a longer duration. CRISC by Hemang Doshi Features of this course are as follow: • This course is designed on the basis of official resources of ISACA. • Course is designed specifically for candidates from non-technical background. • Topics are arranged segment wise and aligned with latest CRISC Review Manual. • Exam oriented practice questions and practical example for CRISC aspirants. • Flashcards based learning mode. • Use of smartarts for easy learning • More than 500 plus practice questions • Course also includes 2 full CRISC Mock Test (150 questions each)
The Ultimate T-SQL And Microsoft SQL Server Bootcamp
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Master the power of Microsoft SQL Server and T-SQL in this comprehensive bootcamp. You'll start with the fundamentals of SQL and relational databases, learning key concepts such as database setup, environment configuration, and the significance of SQL in data management. By the end of the introductory modules, you’ll have a strong grasp of SQL’s role in modern data-driven applications. As you progress, you'll gain hands-on experience in writing SQL queries, filtering and sorting data, and combining multiple tables using JOINs. You'll explore advanced query techniques such as subqueries, window functions, and aggregate operations. Additionally, you’ll learn to insert, update, and delete data while maintaining database integrity and performance. The course also covers T-SQL routines, including stored procedures, triggers, and cursors, as well as transaction management and concurrency control. You'll get practical insights into SQL Server management tools like SQL Management Studio and Azure Data Studio, ensuring you're well-equipped for real-world database administration. Whether you're a beginner looking to start a career in database management, a developer aiming to improve your SQL skills, or a data analyst seeking to enhance data retrieval efficiency, this course provides a structured learning path. No prior SQL experience is necessary, making it accessible for beginners, but some familiarity with databases will be helpful.
AI Engineer Bootcamp 2026: LLMs, RAG, AI Agents & Vector DBs
Become a job-ready AI Engineer and master the skills companies expect in 2026: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and vector databases. You will follow an AI-engineer roadmap from foundations to deployment, so you can design, build, and ship production-grade AI features instead of just calling APIs. This course is built for developers who want to transition into AI engineering roles and need a single, practical path that covers LLM concepts, RAG pipelines, agents, evaluation, and deployment. Every module ties skills directly to what AI engineer roadmaps and job descriptions list as must-have capabilities in 2026. What you'll be able to do as an AI Engineer • Understand and explain the AI engineer skill stack: LLMs, RAG, AI agents, evaluation, and deployment. • Build LLM-powered applications with modern APIs and frameworks, using patterns you can discuss in interviews. • Design and implement RAG pipelines with embeddings, vector databases, and retrieval strategies that ground models in real data. • Create AI agents that use tools, plan multi-step workflows, and interact with external APIs like a real product feature. • Evaluate and debug AI systems using practical metrics - accuracy, hallucinations, latency, reliability - that matter in production. • Deploy AI services and integrate them into web backends or existing products so your work looks production-ready on a CV and portfolio. Projects you'll add to your portfolio • An LLM-powered Q&A assistant grounded in your own documents using RAG and a vector database. • An AI agent that calls external tools and APIs to complete multi-step tasks, showcasing planning and tool-use. • A production-style AI microservice that exposes LLM and RAG functionality over an API, ready to plug into a real app. • Additional mini-projects that demonstrate prompt engineering, evaluation workflows, and AI-powered automation. You can reference these projects in interviews, GitHub, and LinkedIn to prove you can design and ship full AI workflows, not just toy demos. Who this course is for • Software Engineers and Backend or Full-Stack Developers targeting AI Engineer roles. • Data Scientists and ML Engineers who want to move into LLM and agent-centric work. • Career-switchers and motivated beginners who want a guided AI engineer roadmap instead of random tutorials. • Tech professionals who want to add AI Engineer skills to their current role and stand out in 2026. Requirements • Comfortable with basic Python (loops, functions, packages); some API experience is helpful but not required. • No prior deep learning experience necessary; we cover the essentials as they relate to AI engineer work. • A computer with internet access to run notebooks, call APIs, and connect to vector databases. If your goal is to apply for AI Engineer roles, talk confidently about RAG, agents, and vector databases, and ship projects that match modern roadmaps, this course is designed to get you there.
CompTIA A+ Core 1 V15: Mobile Devices
This course is ideal for those preparing for certification exams or starting out in IT. You’ll learn the key hardware and connectivity concepts for laptops, smartphones, and tablets. The course covers installation and configuration of laptop components, advanced features, and display technologies. You’ll also get hands-on experience connecting and setting up various mobile devices, working with mobile networking and wireless technologies, and managing device synchronization. Real-world topics like smartphone-to-car integration and mobile device management (MDM) are included.
AWS Networking Zero to Hero : Masterclass
This is your complete guide to mastering AWS Networking — from foundational concepts to advanced architecture and real-world automation. Whether you’re a beginner or an IT professional transitioning to the cloud, this course is designed to take you from zero to expert in building and managing AWS network infrastructure. The course starts with the basics and gradually progresses into deep, production-grade scenarios used by enterprises and DevOps teams. By taking this course, you will: • Start from the ground up — no prior networking or AWS experience is needed • Understand the core components of AWS networking: VPCs, subnets, route tables, Internet Gateways, and NAT Gateways • Learn how to launch and manage EC2 instances in both public and private subnets • Configure and manage key networking services such as Security Groups, Network ACLs, and VPC Endpoints • Build resilient and scalable systems using Application Load Balancer (ALB), Network Load Balancer (NLB), and Gateway Load Balancer • Implement inter-VPC and cross-region connectivity using VPC Peering and Transit Gateway • Explore AWS Global Accelerator for low-latency, global networking performance • Learn how to use Amazon Route 53 for DNS routing, domain registration, and advanced routing policies (weighted, geolocation, failover) • Secure your applications with AWS WAF and AWS Shield for DDoS protection • Analyze and monitor traffic using VPC Flow Logs and CloudWatch metrics • Work on an end-to-end DevOps + Networking project using EC2, Jenkins, Load Balancers, and Route53 • Automate all infrastructure using Terraform — building reusable, production-ready IaC modules • Gain cloud-ready, job-ready skills applicable for AWS certification (Solutions Architect, SysOps, DevOps) and real-world enterprise roles This course is ideal for Cloud Practitioners, DevOps Engineers, System Administrators, Solutions Architects, and anyone serious about building a career in cloud networking. By the end, you’ll be equipped to design, build, secure, and automate complex networking topologies in AWS with confidence and clarity.
Mastering Microsoft Azure AI Fundamentals
This course provides a comprehensive understanding of Azure AI, Machine Learning, and Data Science, integrating fundamental concepts with advanced tools and solutions. You will explore core principles of Azure Machine Learning, delve into powerful Computer Vision and Natural Language Processing (NLP) features, and unlock generative AI capabilities with Azure OpenAI and Azure AI Foundry. The course emphasizes practical knowledge, guiding you through real-world applications to build intelligent solutions. The AI-900 course introduces the fundamental concepts of AI and the services available in Microsoft Azure to create AI solutions. It focuses on building awareness of common AI workloads and identifying Azure services to support them. The course includes: This course facilitates learners with approximately 6:30-7:00 Hours of Video lectures that provide both Theory and Hands-On knowledge. The course is divided into 5 Modules, each further divided into lessons. To test learners' understanding, every module includes Assignments in the form of Quizzes and In-Video Questions. Module 1: Azure AI, ML, and Data Science: Fundamentals Module 2: Azure Machine Learning Principles Module 3: Azure Computer Vision: Solutions and Tools Module 4: Azure Natural Language Processing (NLP): Scenarios, Features, and Tools Module 5: Generative AI workloads on Azure [Azure OpenAI - Azure AI Foundry]
Electronics in Biomedical Engineering: Theory & Repair
" ONE HOUR WORTH OF NEW CONTENT WERE ADDED UNDER THE SECTION (Diode Operation and Applications) " The course "Electronics in Biomedical Engineering: Theory & Repair" provides a comprehensive and immersive learning experience for individuals interested in the intersection of electronics and biomedical engineering. The content covers a range of essential topics, starting with the fundamentals of electronics components and circuits, ensuring students grasp the core principles. Moving forward, the course delves into the applications of electronics in biomedical instrumentation. Students will explore how various medical devices function, enabling accurate measurement and monitoring of vital signs and bioelectric signals. They will gain an understanding of sensors, transducers, and amplifiers used in medical devices and how to optimize their performance. A key focus of the course is troubleshooting methodologies. Students will learn structured approaches to diagnose and rectify malfunctions in electronic systems and medical devices. Practical skills will be honed in repairing and maintaining medical equipment, adhering to safety protocols to ensure proper functionality and patient well-being. The course also introduces students to the concept of digital electronics and microcontrollers. They will discover how these components play a vital role in medical device development, allowing for precise control and automation. Biomedical signal processing is another crucial aspect of the course, where students will learn how to analyze and process bioelectric signals. Understanding signal processing techniques will enable them to extract valuable information from biomedical signals, crucial for medical diagnosis and research. Furthermore, the course presents an overview of medical device technology and classifications. Students will become familiar with the regulatory framework and safety standards guiding the design and use of medical devices. In addition to theoretical knowledge, the course emphasizes practical application. Students will engage in hands-on projects, integrating electronics and biomedical engineering principles to create innovative solutions for healthcare challenges. In summary, "Electronics in Biomedical Engineering: Theory & Repair" equips students with a diverse skill set, empowering them to excel in biomedical electronics. Whether pursuing careers in the medical device industry, healthcare settings, or research, students will be well-prepared to make a positive impact in this rapidly evolving field.
Introduction to Technical Support
Technical Support professionals are in great demand! This is the first course in the IBM IT Support Professional Certificate program, designed to prepare you for a rewarding career in technical support. You will begin this self-paced course by learning what Informational Technology (IT) support is all about. You'll find out the roles and responsibilities of Technical Support professionals and become familiar with all the different career paths you can take in Technical Support. You will also hear from experts in the IT industry about getting started in the field and how you can pursue this career without prior experience or degrees. You'll also learn some basics about the technology that technical support professionals use. You will hear from industry insiders about how you can develop a customer support mindset and how to talk with customers and solve their problems. You will gain insights into performance evaluation, career paths, and the industry-recognized certifications that can propel your technical support career forward. You'll then gain a comprehensive understanding of support tools and support channels and how they streamline issue resolution. You will also learn about the importance of Service-Level Agreements (SLAs) and how they contribute to delivering exceptional support experiences. Next you will explore ticketing systems, a fundamental component of modern technical support. You'll learn about their features, benefits, and the lifecycle of a ticket or a support issue. Moreover, you'll immerse yourself in tech support methodologies, frameworks, and the art of effective documentation. The course wraps up with a project that provides you with the opportunity to use a ticketing system hands-on and simulate the work that IT Support Specialists and Helpdesk Technician’s perform.
AIGP Cert Masterclass - Prepare for the Exam in 2026
This course contains the use of artificial intelligence. However, every lecture recording involves me reading the scripts, and I am fully involved in scripting and production. Be careful buying courses with instructors that don't appear in person. AI courses are becoming quite common on learning platforms. This course is a complete, structured study program for the IAPP Artificial Intelligence Governance Professional (AIGP) exam. Built domain by domain against the official exam blueprint, it covers every topic area you need to understand before sitting for the exam. Each lesson is a narrated video that explains how concepts connect to each other and to real-world practice — not just what the definition is, but how a practitioner applies it. D1 — Understanding the foundations of AI governance (21% of the exam) — covers define ai and identify types of ai systems including machine learning, deep learning, generative ai, and large language models, identify types of risk and harm associated with ai systems including performance risk, bias risk, privacy risk, security risk, and societal harm, explain unique characteristics of ai that require governance including opacity, autonomy, scalability, and emergent behavior, describe common principles of responsible ai including fairness, transparency, accountability, human oversight, non-maleficence, privacy, and autonomy, identify roles and responsibilities for ai governance including ai owner, model owner, ai risk officer, ethics board, and board-level oversight, describe how cross-functional collaboration among legal, privacy, security, data management, hr, and business teams supports effective ai governance, explain how training and awareness programs communicate ai governance expectations to employees, contractors, and affected stakeholders, differentiate governance approaches appropriate to different company sizes and ai maturity levels, distinguish obligations and accountability of ai developers, providers, deployers, and users across the ai value chain, identify the policies and procedures needed to establish oversight and accountability across each ai lifecycle stage from design through decommissioning, describe how to evaluate and update existing organizational policies covering privacy, security, data governance, and intellectual property to address ai-specific requirements, explain third-party risk policies covering ai procurement, supply chain due diligence, hr practices, and acceptable use requirements for ai tools. You will understand how each of these areas is tested on the exam and how they connect to real-world practice. D2 — Understanding how laws, standards and frameworks apply to AI (25% of the exam) — covers explain how transparency, choice, lawful basis, and purpose limitation requirements under gdpr and other privacy laws apply to ai systems, describe how data minimization and privacy by design principles constrain ai training data selection and system architecture, identify controller obligations relevant to ai including data protection impact assessments, processor agreements, cross-border transfer mechanisms, data subject access requests, automated decision-making restrictions under gdpr article 22, and data breach notification, explain how special categories of personal data including health, biometric, and genetic data attract heightened obligations when used in ai systems, describe how intellectual property laws including copyright, trade secret, and patent apply to ai-generated content, training data, and model outputs, explain how nondiscrimination laws apply to ai-driven decisions in employment, credit, housing, and other regulated domains including disparate impact liability, identify how consumer protection laws and regulations apply to ai claims, disclosures, and automated practices, describe how product liability frameworks apply to ai systems including provider and deployer exposure for harm caused by ai outputs, classify ai systems under risk-tiered regulatory frameworks including the prohibited, high-risk, limited-risk, and minimal-risk categories of the eu ai act, describe requirements for high-risk ai systems including risk management systems, data governance, technical documentation, and conformity assessment procedures, explain human oversight requirements, transparency obligations, and quality management system requirements for high-risk ai systems, identify obligations applicable to general-purpose ai (gpai) models including transparency requirements, copyright compliance, technical documentation, and systemic risk designation thresholds, describe enforcement mechanisms, penalties, and market surveillance powers under ai-specific laws, identify how organizational context including provider, deployer, importer, and distributor roles affects compliance obligations under ai-specific laws, describe the oecd ai principles and how they inform voluntary and regulatory ai governance approaches across jurisdictions, explain the nist ai rmf core functions (govern, map, measure, manage), categories, subcategories, and the nist ai rmf playbook as an implementation tool, identify the purpose and scope of core iso standards relevant to ai governance including iso 22989 (ai concepts and terminology), iso 42001 (ai management systems), and iso 42005 (ai system impact assessment). You will understand how each of these areas is tested on the exam and how they connect to real-world practice. D3 — Understanding how to govern AI development (27% of the exam) — covers describe how to define and document an ai use case including intended purpose, success criteria, stakeholder requirements, and constraints prior to design, explain how to conduct an impact assessment during the design phase to identify potential harms to individuals, groups, and society, identify how to apply organizational policies and best practices to ai system design including privacy by design, security by design, and responsible ai principles, describe how to identify and manage internal and external risks during the design and build phases including bias, security vulnerabilities, and dependency risks, explain requirements for documenting the design and build process including architecture decisions, data sources, training approaches, and known limitations, identify data governance requirements applicable to ai training and testing data including lawful basis, data minimization, purpose limitation, and quality standards, describe data lineage and provenance requirements for training and testing datasets including source documentation, consent records, and licensing terms, explain how to plan and execute training and testing activities including dataset splitting, evaluation methodology, and acceptance criteria definition, identify common training and testing issues and risks including data imbalance, leakage, overfitting, and benchmark gaming, describe documentation requirements for training and testing activities including datasheets for datasets, training run records, and test results, identify production readiness requirements including conformity assessment, model cards, deployment authorization gates, and rollback procedures, explain how to design and operate a continuous monitoring program for deployed ai systems covering performance, bias, drift, and security, describe periodic assessment activities including audits, red-teaming, threat modeling, and adversarial testing, identify incident management requirements for ai systems including classification criteria, containment options, regulatory notification obligations, and evidence preservation, explain how to collaborate with technical teams on incident root cause analysis and remediation to prevent recurrence, describe public disclosure requirements including technical documentation for users, instructions for use, and post-market monitoring plans. You will understand how each of these areas is tested on the exam and how they connect to real-world practice. D4 — Understanding how to govern AI deployment and use (27% of the exam) — covers describe the ai use case context factors relevant to a deployment decision including affected populations, regulatory environment, data sensitivity, and organizational risk appetite, distinguish ai model types relevant to deployment decisions including classical machine learning versus generative ai, proprietary versus open-source models, and foundation models versus task-specific models, identify ai deployment options and their governance implications including cloud versus on-premises versus edge deployment, and fine-tuning versus retrieval-augmented generation versus agentic architectures, explain how to conduct an impact assessment prior to deployment including evaluating potential harms, affected populations, and mitigation options, describe how to review vendor documentation and licensing terms including model cards, technical specifications, data use restrictions, and liability allocations, identify unique risks faced by deployers of proprietary ai models including dependency on provider transparency, limited auditability, and inherited compliance obligations, explain how to apply organizational deployment policies including acceptable use requirements, access controls, and human oversight configurations, describe how to design and operate a continuous monitoring program for deployed ai systems covering performance degradation, fairness drift, and misuse detection, identify periodic assessment activities for deployed systems including compliance audits, penetration testing, and bias re-evaluation, explain incident documentation requirements for deployment-phase incidents including logs, root-cause records, and regulatory notification artifacts, describe methods for forecasting secondary and unintended uses of a deployed ai system and governance controls to prevent misuse, explain how to develop external communications plans covering ai disclosures to users, regulators, and the public, identify deactivation and localization controls including procedures to suspend ai decision-making, restrict geographic scope, and manage data residency requirements. You will understand how each of these areas is tested on the exam and how they connect to real-world practice. Every domain includes practice questions designed to mirror the style and difficulty of AIGP exam scenarios, covering not just recall but application and analysis. The course closes with full-length practice exams with detailed answer explanations, so you can measure your readiness and focus your remaining study time where it matters most. Major topics covered: define ai and identify types of ai systems including machine learning, deep learning, generative ai, and large language models, identify types of risk and harm associated with ai systems including performance risk, bias risk, privacy risk, security risk, and societal harm, explain unique characteristics of ai that require governance including opacity, autonomy, scalability, and emergent behavior, describe common principles of responsible ai including fairness, transparency, accountability, human oversight, non-maleficence, privacy, and autonomy, identify roles and responsibilities for ai governance including ai owner, model owner, ai risk officer, ethics board, and board-level oversight, describe how cross-functional collaboration among legal, privacy, security, data management, hr, and business teams supports effective ai governance, explain how training and awareness programs communicate ai governance expectations to employees, contractors, and affected stakeholders, differentiate governance approaches appropriate to different company sizes and ai maturity levels, distinguish obligations and accountability of ai developers, providers, deployers, and users across the ai value chain, identify the policies and procedures needed to establish oversight and accountability across each ai lifecycle stage from design through decommissioning, describe how to evaluate and update existing organizational policies covering privacy, security, data governance, and intellectual property to address ai-specific requirements, explain third-party risk policies covering ai procurement, supply chain due diligence, hr practices, and acceptable use requirements for ai tools, explain how transparency, choice, lawful basis, and purpose limitation requirements under gdpr and other privacy laws apply to ai systems, describe how data minimization and privacy by design principles constrain ai training data selection and system architecture, identify controller obligations relevant to ai including data protection impact assessments, processor agreements, cross-border transfer mechanisms, data subject access requests, automated decision-making restrictions under gdpr article 22, and data breach notification, explain how special categories of personal data including health, biometric, and genetic data attract heightened obligations when used in ai systems, describe how intellectual property laws including copyright, trade secret, and patent apply to ai-generated content, training data, and model outputs, explain how nondiscrimination laws apply to ai-driven decisions in employment, credit, housing, and other regulated domains including disparate impact liability, identify how consumer protection laws and regulations apply to ai claims, disclosures, and automated practices, describe how product liability frameworks apply to ai systems including provider and deployer exposure for harm caused by ai outputs, classify ai systems under risk-tiered regulatory frameworks including the prohibited, high-risk, limited-risk, and minimal-risk categories of the eu ai act, describe requirements for high-risk ai systems including risk management systems, data governance, technical documentation, and conformity assessment procedures, explain human oversight requirements, transparency obligations, and quality management system requirements for high-risk ai systems, identify obligations applicable to general-purpose ai (gpai) models including transparency requirements, copyright compliance, technical documentation, and systemic risk designation thresholds, describe enforcement mechanisms, penalties, and market surveillance powers under ai-specific laws, identify how organizational context including provider, deployer, importer, and distributor roles affects compliance obligations under ai-specific laws, describe the oecd ai principles and how they inform voluntary and regulatory ai governance approaches across jurisdictions, explain the nist ai rmf core functions (govern, map, measure, manage), categories, subcategories, and the nist ai rmf playbook as an implementation tool, identify the purpose and scope of core iso standards relevant to ai governance including iso 22989 (ai concepts and terminology), iso 42001 (ai management systems), and iso 42005 (ai system impact assessment), describe how to define and document an ai use case including intended purpose, success criteria, stakeholder requirements, and constraints prior to design, AIGP exam prep.
Introduction to Large Language Models - Italiano
Questo è un corso di microlearning di livello introduttivo che esplora cosa sono i modelli linguistici di grandi dimensioni (LLM), i casi d'uso in cui possono essere utilizzati e come è possibile utilizzare l'ottimizzazione dei prompt per migliorare le prestazioni dei modelli LLM. Descrive inoltre gli strumenti Google per aiutarti a sviluppare le tue app Gen AI.
AI for Beginners @ Work - ChatGPT, Claude, Gemini + Copilot
This beginner-friendly course will help you build real confidence with artificial intelligence by showing you how to use the most popular AI tools in practical, everyday ways at work and beyond. You will start with the foundations of AI, learning the difference between predictive AI and generative AI, and seeing how large language models produce text one token at a time. You will also discover why context matters and how providing better context improves accuracy and usefulness. From there you will go hands-on. You will set up free accounts for ChatGPT, Claude, Microsoft Copilot, and Google Gemini with AI Mode. ChatGPT will be the main platform for practice, but you will also explore how other tools compare so you can decide which best fits your work. You will learn the essentials of prompt engineering and context engineering. You will practice writing prompts for real tasks such as drafting emails, summarizing articles, planning projects, and brainstorming ideas. You will also learn how retrieval-augmented generation (RAG) helps AI provide more reliable answers. Throughout the course, you will see how AI is embedded in search engines, writing software, and productivity platforms. You will explore advanced features like custom GPTs, projects, operators, and agents at an introductory level so you know what is possible. You will apply AI to real-world workflows, boosting productivity, doing deeper research, writing more efficiently, and generating creative output. You will also learn how to check AI responses for accuracy, how to fact-check answers with tools like Gemini or Perplexity, and how to use AI responsibly and ethically. By the end of this course, you will have a strong foundation in AI literacy and the confidence to integrate AI tools into your daily life and work. You will also know the next steps you can take, including more advanced courses on prompt engineering, accuracy and hallucination mitigation, no-code agents, and AI-powered communication and collaboration.
Tencent Cloud Practitioner
This course is primarily aimed at cloud professionals who are interested in learning about Tencent Cloud's products and services. It equips learners with a foundational knowledge in cloud computing and prepares them to take the Tencent Cloud Practitioner examination. After completing this course, learners will be able to explain the different features, advantages, uses cases, and billing methods of several core Tencent Cloud products.
Oscilloscopes for beginners
Oscilloscopes are incredible: They can capture, display, and analyse an electrical input signal. They can automatically produce all kinds of measurements, like the period, rise time, width, duty cycle, max and min voltages, and lots more, and even decode communications protocols like RS232, and I2C. Are you working with electronics and are interested in using an oscilloscope to gain a better understanding of what is happening inside your circuits as they operate? Perhaps you already have an oscilloscope but are confused by all its buttons, knobs and menu options? Perhaps you are thinking of getting one but not sure if its worth it, or not sure what to look for? This course is dedicated to the oscilloscope, and it will help you answer these questions, plus lots more. It will teach you how to use the oscilloscope that you already have, or are planning to get. After the multimeter, the oscilloscope is the most useful test instrument for makers. Over the last few years, their prices have dropped by a lot, and it is now very common for students and hobbyists to be able to afford one. Today, budget scopes offer a full array of capabilities. You are probably familiar with the multimeter. This test instrument gives you a snapshot of what is happening in your circuit in a specific moment in time. For example, it will tell you that the voltage on a certain pin is 5.1 Volts. The multimeter works in a single dimension. The oscilloscope works in two dimensions. On its screen, it will plot the voltage of your test circuit over time. You can see how voltage changes over time, and get the measurements that describe various aspects of its operation. You can use this information to dive deep into the inner workings of your circuit. This is a course for people who are already familiar with basic electronics. To make the most from this course, you will need to have a working understanding of things like Volt, Hz and duty cycle. Because I use the Arduino and the ESP32 to create experiments based on which I demonstrate various features and capabilities of the oscilloscope, you should also have a basic understanding of those two technologies. In the course, first I’ll talk about the various aspects of an oscilloscope, such as the most important features, functions, and controls. Second, I’ll help you get comfortable with your oscilloscope, calibrate it and get it ready for use. And third, I’ll show you how to use the oscilloscope by guiding you through multiple experiments. Each experiment is an opportunity to learn and practice several new workflows and operations. This third part, the experimental, consists the bulk of the course. So I invite you to enrol in this course right now, and learn how to use your oscilloscope. You can also have a look at the free lectures for more information about the objectives and structure of this course.
Azure AI and Healthcare Cloud Fundamentals
Azure AI and Healthcare Cloud Fundamentals is a beginner-friendly course that introduces you to Azure services specifically relevant to healthcare applications, including compute, storage, and AI services. You'll learn healthcare data requirements, explore Azure's health-specific tools, and understand cloud architecture for medical environments. Through hands-on labs, you'll deploy basic Azure resources, configure security settings, and work with healthcare data scenarios. It is perfect for healthcare professionals transitioning to technology roles or IT professionals entering the healthcare sector. You can build foundational knowledge for Azure certifications while gaining practical skills in cloud computing for healthcare.
Mastering Data Modeling Fundamentals
If you are a current or aspiring IT professional in search of sound, practical techniques to analyze and model data as part of the overall data management lifecycle, this is the course for you. During the course, you’ll put what you learn to work and define sample data model segments in both “classic” entity-relationship notation and also the “crow’s foot” notation to help emphasize the best practices and techniques covered in this course. Each section has either scenario based quiz questions or hands on assignments that emphasizes key learning objectives for that section’s material. This way, you can be confident as you move through the course that you’re picking up the key points about data modeling. To build this course, I drew from more than 30 years of my own work involving data modeling and related disciplines. Long ago, in the late 1980s, I was a software engineer at what was then the world’s second largest computer systems vendor, Digital Equipment Corporation. I wrote software for a “conceptual and logical database design tool” - in other words, a data modeling tool. My own consulting firm, Thinking Helmet, Inc., specializes in data management and analytics-focused disciplines for which data modeling is essential. I’ve rolled up my sleeves and personally tackled every aspect of what you’ll learn in this course. I’ve even learned a few painful lessons, and have built a healthy share of “lessons learned” into the course material. In this course, I take you from the fundamentals and concepts of data modeling all the way through a number of best practices and techniques that you’ll need to build data models in your organization. You’ll find many examples that clearly demonstrate the key concepts and techniques covered throughout the course. By the end of the course, you’ll be all set to not only put these principles to work, but also to make the key data modeling and design decisions required by the “art” of data modeling that transcend the nuts-and-bolts techniques and design patterns. Specifically, this course will cover: • Foundational data modeling concepts and fundamentals • The symbiotic relationship between data modeling and database design (Hint: the two are not exactly the same!) • Different modeling approaches, techniques, and notations that you can put to work • The fundamentals of entities, attributes, and relationships, as well as how to express these concepts in multiple modeling notations • How we incorporate real-world complexities into our entities, attributes, and relationships • The data modeling lifecycle that includes forward engineering a conceptual data model to a logical and then a physical model, as well as how we reverse-engineer a physical data model back to the conceptual level • Different software-based approaches for data modeling tools Data modeling is both an art and a science. While we have developed a large body of best practices over the years, we still have to make this-or-that types of decisions throughout our data modeling work, often based on deep experience rather than specific rules. That’s what I’ve instilled into this course: the fusion of data modeling art and science that you can bring to your organization and your own work. So come join me on this journey through the world of data modeling!
Linux System Administration with IBM Power Systems
This course introduces administrative tasks that a system administrator can perform with Linux hosted on IBM Power servers. This includes virtualization concepts such as logical partitioning, installation of Linux, command-line operations, and more interesting administration and device management tasks. This course includes hands-on exercises with systems from an IBM data center.
OpenShift for the Absolute Beginners
Learn the fundamentals and basic concepts of OpenShift, which you will need to build a simple OpenShift cluster, and start deploying and managing applications. Content and Overview This course introduces OpenShift to an Absolute Beginner using simple and easy-to-understand lectures. Lectures are followed by demos showing how to set up and start with OpenShift. Build a strong foundation in OpenShift and container orchestration with this tutorial for beginners. • Deploy OpenShift with CodeReady Containers (OpenShift local), Dev Sandbox, and a full production-level cluster • Understand Projects, Users • Understand Builds, Build Triggers, Image streams, Deployments • Understand Network, Services and Routes • Configure integration between OpenShift and GitLab SCM • Storage configurations, including CSI’s, volumes, and more. • Deploy a sample Multi-services application on OpenShift • Configure security practices with hardening guidelines and RBAC A much required skill for anyone in DevOps and Cloud Learning the fundamentals of OpenShift (and Kubernetes) puts the knowledge of a powerful Platform-as-a-Service (PaaS) offering at your fingertips. OpenShift is the next-generation Application Hosting platform by Red Hat. Legal Notice: Openshift and the OpenShift logo are trademarks or registered trademarks of Red Hat, Inc. in the United States and/or other countries. Re Hat, Inc. and other parties may also have trademark rights in other terms used herein. This course is not certified, accredited, affiliated with, nor endorsed by OpenShift or Red Hat, Inc.
Cybersecurity in Healthcare (Hospitals & Care Centres)
The Cybersecurity in Healthcare MOOC was developed as part the SecureHospitals.eu project. This project has received funding from the European Union’s Horizon 2020 Coordination Research and Innovation Action under Grant Agreement No. 826497. The course "Cybersecurity in Healthcare" has been developed to raise awareness and understanding the role of cybersecurity in healthcare (e.g., hospitals, care centres, clinics, other medical or social care institutions and service organisations) and the challenges that surround it. In this course, we will cover both theoretical and practical aspects of cybersecurity. We look at both social aspects as technical aspects that come into play. Furthermore, we offer helpful resources that cover different aspects of cybersecurity. Even if you are not active in the healthcare domain, you will find helpful tips and insights to deal with cybersecurity challenges within any other organisation or in personal contexts as well. This course begins by introducing the opportunities and challenges that digitalisation of healthcare services has created. It explains how the rise of technologies and proliferation of (medical) data has become an attractive target to cybercriminals, which is essential in understanding why adequate cybersecurity measures are critical within the healthcare environment. In later modules, course contents cover the threats, both inside and outside of healthcare organisations like e.g. social engineering and hacking. Module 4 on Cyber Hygiene describes how to improve cybersecurity within healthcare organisations in practical ways. Module 5 looks deeper into how organisational culture affects cybersecurity, the cybersecurity culture, focusing on the interaction between human behaviour and technology and how organisational factors can boost or diminish the level and attention to cybersecurity in healthcare. Do you work for a hospital, clinic, medical practice, care centre, care provider, social care organisation, or nursing home? Do you want to improve your personal or your organisation’s cybersecurity (cyber security, IT security, information security, network security, computer security, awareness)? Then please visit https://www.securehospitals.eu to gain access to a range of resources. You can also join the Security providers and Trainers platform (see: https://www.securehospitals.eu/for-providers-and-trainers/) or our Community of Practice (see: https://www.securehospitals.eu/community/).
SAP FICO (Finance & Controlling ) Simplified For Beginners
Dear Students, Complete Notes available for reference.Please check lecture-17 of section-2 for notes. This course is designed in such a way that any beginners or freshers from any different domain can learn SAP FICO S/4-HANA Concept ,Configuration, and End-User Activities to crack any sap fico interview. If you observe many faculties are putting more stress on explaining "how to do the configuration" but when you go for interview, the interviewer will asks you about “why to do” i.e. logic behind configuration. In this Course both are covered "how to do" and "why to do" To explore further ,please check preview videos. Who this course is for: • Anyone who wants to learn SAP FICO configuration ,End-user Activities, implementation in detail • SAP Users who want to extend their knowledge to configure to become SAP FICO • Any ERP Consultants who want to learn SAP FICO configuration and implementation SAP FICO ECC Notes Attached to Section-2 Videos Resources . SAP S/4 HANA Notes Attached to Section-20 Video Resource. PLEASE CHECK FROM PC NOT FROM UDEMY MOBILE APP This Course is designed to become Successful SAP FICO Consultant with practical understanding of All Typical Business Process in SAP FICO Complete Configuration Notes will be Provided for your reference. SAP FI stands for Financial Accounting and it is one of important modules of SAP ERP. It is used to store the financial data of an organization. SAP FI helps to analyze the financial conditions of a company in the market. It can integrate with other SAP modules like SAP SD, SAP PP, SAP MM, SAP SCM, etc. SAP Controlling (CO) is another important SAP module offered to an organization. It supports coordination, monitoring, and optimization of all the processes in an organization. SAP CO includes managing and configuring master data that covers cost and profit centers, internal orders, and other cost elements and functional areas. This tutorial will be extremely useful for professionals who aspire to learn the ropes of SAP FICO and implement it in practice. It is especially going to help consultants who are mainly responsible for implementing Financial Accounting and Cost Accounting with SAP ERP Financials. ** Disclaimer ** • SAP is a registered trademark of SAP AG in Germany and many other countries. I am NOT associated with SAP. • SAP software and SAP GUI are proprietary SAP software. Neither Udemy nor me are authorized to provide SAP Access.
Create a Custom Network and Apply Firewall Rules
This is a self-paced lab that takes place in the Google Cloud console. Use the gcloud command line to set up a VPN and 3 subnetworks, then apply firewalls.
Grafana
Welcome to my course on Grafana Grafana is an analytics platform for all of your metrics. Grafana allows you to query, visualize, alert on and understand your metrics no matter where they are stored. Create, explore, and share dashboards with your team and foster a data driven culture. Trusted and loved by the community. This is a Learn by example course, where I demonstrate all the concepts discussed so that you can see them working, and you can try them out for yourself as well. With this course, comes accompanying documentation that you can access for free. You will then be able to match what you see in the videos and copy/paste directly from my documentation and see the same result. In this course we will, • Install Grafana from Packages • Create a domain name, install an SSL certificate and change the default port • Explore the Graph, Stat, Gauge, Bar Gauge, Table, Text, Heatmap and Logs Panels • Create many different types of Data Sources from MySQL, Zabbix, InfluxDB, Prometheus and Loki • We will configure their various collection processes such as MySQL Event Scheduler, Telegraf, Node Exporters, SNMP agents, Alloy and Beats • We will look at graphing Time Series data versus Non Time Series data • We will also install dashboards for each of the Data Sources, experimenting with community created dashboards plus experimenting with our own • We will create Annotation Queries and link the Log and Graphs panels together • We will look at Dynamic Dashboard Variables, Dynamic Tables and Graphs • We will look at creating Value Groups/Tags and how to use them with different kinds of data sources • We will set up Alerting Channels/Contact Points and understand the different alerting options, configure an example to detect offline SNMP devices and demonstrate receiving email alerts via a local SMTP server At the end of the course, you will have your own dedicated working Grafana Server, which will be in the cloud, with SSL, a domain name, with many example Data Sources and collectors configured, that you can call your own, ready for you to take it to the next level. Once again, this is a Learn by example course, with all the example commands available for you to copy and paste. I demonstrate them working, and you will be able to do that to. You are now ready to continue. Thanks for taking part in my course, and i'll see you there.
Monitoring and Managing Bigtable Health and Performance
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you monitor disk and CPU usage in a Bigtable instance, update an existing cluster to apply node autoscaling, implement replication in an instance, and back up and restore data in Bigtable.