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ISTQB Test Management V3.0 CTAL-TM | Certified Test Manager
Hello, future test management heroes! Welcome to our ultimate ISTQB Advanced Level Test Manager V3.0 masterclass. In this course introduction, we're going to answer 3 major questions that any test manager may have in mind: • Who is this course for? • What to expect during our CTAL-TM V3 journey? • What to expect after completing this course? - - - Who is this course for? • Software testers who want to apply for a test manager position • Current test managers aiming to improve their test management skills • Students who want to pass the ISTQB Advanced Level Test Manager exam • Other stakeholders seeking an understanding of the test management process - - - What to expect during our CTAL-TM V3 journey? • 14 hours of test management training • Thorough explanations of all test management concepts • Lectures accompanied by a lot of examples • Clear and natural pace audio for better follow-up • Solving the official ISTQB CTAL-TM V3 exam sample questions after each section • The presentation slides for each lecture are available for download (PDF Files) - - - What to expect after completing this course? • Solid understanding of all test management concepts and terminology • Deep comprehension of how a test manager should behave in different contexts • Being able to digest the essential actions required in the test process • Gain the context-awareness of a test manager in various test types, levels, and SDLCs • Revisit Risk-Based Testing and explain its various measures and considerations • Analyze and explain the typical choices for a test approach and strategy • Master the IDEAL approach for test process improvement and adaptation • Explain the tool lifecycle and best practices for tool introduction and maintenance • Using test results and metrics in test control and achieving the test objectives • Understanding the proper test estimation techniques and their influencing factors • Master the defect management process in different SDLC models • Excellence in analyzing, building, and improving a test team based on a skills matrix • Learn the basics of stakeholder relationships essential for any test manager on any project - - - Join us and become the next superstar of test management!
Logo Animation Principles for Beginners
In this course, taught by Adam Chraibi, you will be learning about the logo animation principles in Adobe After Effects CC, we will be focusing more on the techniques rather than the theory. Since people react better to videos than images, logo animation can help the designer and the brand connect deeper with their customers. So, in this course you will learn about: - Coming up with the plot and logo restrictions - The basic principles of logo animation - Making a simple but neat logo reveal and disappear - Creating a more advanced logotype animation using the principles of animation This course is for beginners in logo animation, but being familiar with Adobe After Effects is recommended in order for you to focus on the animation techniques rather than the software. You will need: - Adobe After Effects CC, the latest version - Duik Bassel Free script - Rift free script Once you download the scripts, you basically just need to unzip and place the ''.jsx'' file in the correct folder. By the end of this course, you should be able to apply these techniques to any logotypes and symbols. Instructor bio: Adam Chraibi is a designer, animator, and video editor based in Casablanca, Morocco, with over 7 years of professional experience. His motto is simple: “If you can design it, you can animate it.” Adam’s creative journey began at art school, where he studied drawing, light, and shadow before earning a bachelor’s degree in private law. Ultimately, his passion for digital art and animation led him to leave law behind and pursue a career he truly loves. He has worked as a social media manager and designer for an airline company before becoming a full-time freelancer. In his courses, Adam focuses on teaching practical, real-world skills in a clear and efficient way. His lessons are designed to be short, straightforward, and packed with value—helping learners quickly gain the tools they need to grow their creative side hustle or professional practice.
Go: The Complete Developer's Guide (Golang)
Go is an open source programming language created by Google. As one of the fastest growing languages in terms of popularity, its a great time to pick up the basics of Go! This course is designed to get you up and running as fast as possible with Go. We'll quickly cover the basics, then dive into some of the more advanced features of the language. Don't be tricked by other courses that only teach you for-loops and if-statements! This is the only course on Udemy that will teach you how to use the full power of Go's concurrency model and interface type systems. Go is designed to be easy to pick up, but tough to master. Through multiple projects, quizzes, and assignments, you'll quickly start to master the language's quirks and oddities. Go is like any other language - you have to write code to learn it! This course will give you ample opportunities to strike out on your own and start working on your own programs. In this course you will: • Understand the basic syntax and control structures of the language • Apply Go's concurrency model to build massively parallel systems • Grasp the purpose of types, which is especially important if you're coming from a dynamically typed language like Javascript or Ruby • Organize code through the use of packages • Use the Go runtime to build and compile projects • Get insight into critical design decisions in the language • Gain a sense of when to use basic language features Go is one of the fastest-growing programming languages released in the last ten years. Get job-ready with Go today by enrolling now!
Risk Management for Cyber Security Managers
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. Build the expertise to identify, assess, and mitigate cybersecurity and AI-related risks in modern organizations. You'll develop practical skills in risk analysis, governance, compliance, security controls, and executive communication while learning industry-recognized frameworks and standards that strengthen cyber resilience. The course begins with the fundamentals of cybersecurity risk management, introducing core concepts, threat landscapes, and professional practices. You'll then progress through the complete risk management lifecycle, including risk identification, assessment, mitigation, monitoring, and hands-on workshops for building risk registers and applying quantitative analysis using the FAIR framework. Next, you'll explore AI risk management, AI governance, regulatory requirements, information classification, security controls, third-party risk management, vulnerability management, ISO standards, and global compliance frameworks. The course concludes by teaching you how to communicate technical risks effectively to executives and stakeholders using business-focused reporting techniques. This course is ideal for IT professionals, cybersecurity practitioners, risk analysts, compliance specialists, security managers, and aspiring governance professionals seeking practical cybersecurity risk management skills. A basic understanding of IT and cybersecurity concepts is recommended. The course is designed for learners at the Intermediate level. By the end of the course, you will be able to identify, assess, quantify, and manage cybersecurity and AI risks, implement industry-standard risk management frameworks, develop governance policies, support regulatory compliance, communicate risks effectively to business leaders, and strengthen organizational cyber resilience.
Alteryx Bootcamp
If you work in data analysis or business intelligence, having the right tools in your arsenal is key. This course is for everyone who is either completely new or a beginner with Alteryx Designer. In this course, I'll walk you through the basics of Alteryx, from installing your free trial to connecting to various data sources, performing complex transformations, developing macros, and predictive models using R. This course does not require any prior knowledge of Alteryx. You should be comfortable with data transformation and reporting, using tools such as Microsoft Excel, everything else you'll pick up along the way in this course. This course is excellent to kickstart your path to becoming an Alteryx developer, you'll learn all the basics in just a few hours, and will be able to apply your knowledge in the real world, immediately. There’s a reason why top businesses like Amazon, Audi, and McDonald's trust Alteryx. Its easy-to-use interface and wide-spanning capabilities truly speak for themselves. By taking this course, you’ll learn the ins and outs of Alteryx through a combination of hands-on lessons, video guides, and downloadable resources. The course is designed to be flexible so that you can jump to any lesson for a refresher or to learn a specific aspect of the platform.
Create a Business proposal with Visme for businesses
At the end of this project, you will have all the basic skills to create a Business proposal using Visme, an online tool for designing and editing Marketing visuals. You will be able to design a professional Business proposal in which you describe your company and your offer in detail. This project is intended for professionals of all levels, small and medium-sized businesses, people who have never used Visme to create business content. It is ideal for those who would like to use Visme for their professional projects.
Selenium WebDriver with Java: AI-Powered Test Automation
Boost Your QA Career with Selenium WebDriver, Java, and AI-Powered Test Automation! Looking to transform your QA career and significantly increase your earnings? This Selenium WebDriver with Java course is designed for manual testers and engineers transitioning into test automation — with no prior programming experience required. The 2026 edition adds a brand new section on AI-Powered Selenium, teaching you the modern workflow that top automation engineers use today: Cursor, MCP (Model Context Protocol), AI-assisted test generation, and agentic coding for test automation. In this course, you will master the entire process of test automation using Selenium WebDriver with Java — from your first line of code to a complete, AI-augmented automation framework. Whether you want to get promoted, switch to a high-paying automation role, or stay relevant in an AI-driven industry, this course is your guide. What You'll Learn: • Selenium WebDriver from Scratch: Set up Selenium, run tests in real browsers (Chrome, Firefox, Edge, Safari), and automate web applications end-to-end. • Java Programming for Automation: Learn Java tailored specifically for test automation — perfect for beginners with no coding background. • TestNG Framework Mastery: Build, organize, and scale test suites with TestNG — groups, parameters, suites, parallel execution. • Page Object Model (POM): Design maintainable, scalable automation frameworks following industry best practices. • AI-Powered Test Automation (NEW — 2026): Learn how modern automation engineers work with AI: • Set up Cursor (free tier) for AI-assisted test development • Connect AI to a real browser using Chrome DevTools MCP • Generate Page Objects and tests from natural language prompts • Create context files, Cursor rules, and reusable AI skills • Review, debug, and refine AI-generated test code • Debugging & Exception Handling: Master WebDriver waits, common exceptions, and professional debugging techniques. • Cross-Browser Testing: Run tests reliably across Chrome, Firefox, Edge, and Safari. • Job Market Preparation: Portfolio development, resume building, job listing navigation, and interview prep for Selenium automation roles. • Quizzes & Assessments: Reinforce learning at the end of every section. • HD Video, Crystal-Clear Audio: Professional 1080p production throughout. Why This Course Stands Out in 2026: • Only Selenium course with a full AI automation section. Most Selenium courses are outdated. This one teaches you the AI-assisted workflow that hiring managers now expect. • Tool-agnostic, principles-first approach. Tools change every six months — the workflow doesn't. You'll learn concepts that transfer to any AI coding assistant: Cursor, Claude Code, GitHub Copilot, and beyond. • Beginner-friendly, senior-ready. Start with zero experience. Finish with a production-grade automation framework — manual and AI-augmented. • Immediate results. Start writing real Selenium tests in the first few lessons. Build a portfolio you can show in interviews. • Direct instructor support. Learn from Dmitry Shyshkin, a Principal SDET with 15+ years of test automation experience at Fortune 500 companies. Dmitry personally answers every question in the Q&A section — usually within hours. • Lifetime access. Enroll once, get all future updates — including upcoming AI tooling expansions. Proven Success Since 2017 Thousands of students have used this course to land automation jobs, earn promotions, and significantly increase their salaries. The 2026 edition reflects years of student feedback and reflects the current reality of test automation work — where AI is no longer optional. 100% Money-Back Guarantee Not satisfied? Get a full refund with Udemy's 30-day money-back guarantee — no questions asked. Start Today! Take the next step toward a high-paying, future-proof career in test automation. Learn Selenium WebDriver with Java the modern way — augmented with AI tools used by top automation engineers in 2026. Enroll now. Master Selenium WebDriver with Java | 2026 Edition with AI-Powered Test Automation, Cursor, MCP, TestNG, POM
Blockchain and Cryptography Overview
The Blockchain and Cryptography Overview course is a part of the Certified Blockchain Security Professional (CBSP) Exam Prep Specialization and introduces you to fundamental cryptographic principles. You will gain insight into concepts such as hash functions in blockchain, core components and advantages of blockchain, and assumptions and challenges in blockchain security. You will also learn about core blockchain concepts, highlight security measures against prevalent threats, and comprehend consensus security challenges while exploring well-known algorithms like Proof of Work and Proof of Stake. By the end of this course, you will be able to: 1. Describe the purpose of hash functions and public key cryptography in blockchain security. 2. Explore the fundamentals of blockchain technology, including blocks, chains, and network security, and identify and encounter basic threats. 3. Analyze the security of Proof of Work (PoW) and Proof of Stake (PoS) and alternative consensus methods. The courses in this specialization are designed for individuals interested in blockchain security and cybersecurity and are suitable for both coding and non-coding professionals.
Learn Manual Software Testing + Agile with Jira Tool
This course is designed for beginners aspiring to kickstart a career in Software Testing. Upon completion, participants will acquire comprehensive knowledge of Software Testing Types, Real-Time Testing Processes, and hands-on experience in Agile and Scrum Projects. Key Topics Covered: Module-1: Software Testing Concepts • Understanding Software Development Life Cycle (SDLC) and Software Testing Life Cycle (STLC) • Distinguishing between Project and Product in the context of testing • Exploring V-Model and the roles of QA (Quality Assurance), QC (Quality Control), and QE (Quality Engineering) • Differentiating between White Box and Black Box Testing • Delving into Static Testing and Dynamic Testing • Conceptualizing Verification and Validation in software testing • System Testing Types, including GUI Testing and Functional vs. Non-Functional Testing • Test Design Techniques and strategies like Re-Testing, Regression Testing, Exploratory Testing, Adhoc Testing, Sanity, Smoke Testing, and End-To-End Testing • Understanding Software Testing Life Cycle (STLC) phases, including Use case, Test scenario, Test case, Test Environment, Execution, Defect Reporting, Test Closure, and Test Metrics. Module-2: Software Testing Project • Introduction to project • Extracting Functional Requirements from Functional Requirement Specifications (FRS) • Creating comprehensive Test Scenarios and Test Cases • Execution of Test Cases • Reporting and Tracking Bugs • Test Sign-off Phase-3: Agile Testing + Jira Tool Agile/Scrum Process: • Overview of Agile and Scrum methodologies • Understanding Scrum Teams, Sprints, and User Stories • Estimating User Stories and defining 'Definition of Done' and 'Definition of Ready' • Exploring Sprint Activities such as Sprint Planning, Backlog Refinement, Sprint Review, and Sprint Retrospective Jira Tool: • Installation and Configuration of JIRA • Project creation in Jira and user management • Creating Backlog, Epic, and User Stories in JIRA • Sprint creation and management • Understanding the Sprint life cycle in JIRA • Bug creation in Jira • Writing test cases in JIRA with Zephyr plugin • Creating Test Cycles and executing/updating Test Cases in Jira
API Testing with Karate Framework
Karate is an open-source framework for API Test automation that uses BDD style syntax, has a rich assertion library, built-in HTML reports. In this 2-hour long project-based course, you will learn -- 1. API testing basics and Karate framework 2. Sending GET, POST, PUT, PATCH and DELETE requests via Karate framework 3. Add assertions to write effective test scenarios via the Karate framework
DP-900 Azure Data Fundamentals Exam Preparation
LEARN AZURE DATABASE AND DATA PROCESSING TECHNOLOGIES! Complete preparation for the DP-900 Azure Data Fundamentals exam. The content of this exam was updated for the latest exam changes. • Describe core data concepts (25-30%) • Describe how to work with relational data on Azure (20-25%) • Describe how to work with non-relational data on Azure (15-20%) • Describe an analytics workload on Azure (25-30%) This course completely covers the DP-900 exam from start to finish. Always updated with the latest requirements. This course goes over each requirement of the exam in detail. If you have no background in databases and want to learn about them and want to learn more about database concepts and services within Azure, or have some background in databases and want to progress eventually to an Azure Data Engineer or Data Analyst type role, this course is a great resource for you. Microsoft Azure is still the fastest-growing large cloud platform. The opportunities for jobs in cloud computing are still out there, and finding well-qualified people is the #1 problem that businesses have. If you're looking to change your career, this would be a good entry point into cloud computing on the data side. Sign up today! Added English, Spanish, and Portuguese closed captions.
Google Workspace 핵심 서비스
이 과정은 학습자가 Google Workspace 핵심 서비스를 포괄적으로 이해할 수 있도록 설계되었습니다. 학습자는 Gmail, Calendar, Drive, Meet, Chat, Docs를 비롯한 서비스의 설정을 사용 설정, 중지, 구성하는 방법을 살펴보게 됩니다. 다음으로 Gemini를 배포하고 관리하여 사용자 역량을 강화하는 방법도 알아봅니다. 마지막으로 학습자는 AppSheet와 Apps Script의 사용 사례를 통해 작업을 자동화하고 Google Workspace 애플리케이션의 기능을 확장하는 방법을 살펴봅니다.
Python for Computer Vision with OpenCV and Deep Learning
Welcome to the ultimate online course on Python for Computer Vision! This course is your best resource for learning how to use the Python programming language for Computer Vision. We'll be exploring how to use Python and the OpenCV (Open Computer Vision) library to analyze images and video data. The most popular platforms in the world are generating never before seen amounts of image and video data. Every 60 seconds users upload more than 300 hours of video to Youtube, Netflix subscribers stream over 80,000 hours of video, and Instagram users like over 2 million photos! Now more than ever its necessary for developers to gain the necessary skills to work with image and video data using computer vision. Computer vision allows us to analyze and leverage image and video data, with applications in a variety of industries, including self-driving cars, social network apps, medical diagnostics, and many more. As the fastest growing language in popularity, Python is well suited to leverage the power of existing computer vision libraries to learn from all this image and video data. In this course we'll teach you everything you need to know to become an expert in computer vision! This $20 billion dollar industry will be one of the most important job markets in the years to come. We'll start the course by learning about numerical processing with the NumPy library and how to open and manipulate images with NumPy. Then will move on to using the OpenCV library to open and work with image basics. Then we'll start to understand how to process images and apply a variety of effects, including color mappings, blending, thresholds, gradients, and more. Then we'll move on to understanding video basics with OpenCV, including working with streaming video from a webcam. Afterwards we'll learn about direct video topics, such as optical flow and object detection. Including face detection and object tracking. Then we'll move on to an entire section of the course devoted to the latest deep learning topics, including image recognition and custom image classifications. We'll even cover the latest deep learning networks, including the YOLO (you only look once) deep learning network. This course covers all this and more, including the following topics: • NumPy • Images with NumPy • Image and Video Basics with NumPy • Color Mappings • Blending and Pasting Images • Image Thresholding • Blurring and Smoothing • Morphological Operators • Gradients • Histograms • Streaming video with OpenCV • Object Detection • Template Matching • Corner, Edge, and Grid Detection • Contour Detection • Feature Matching • WaterShed Algorithm • Face Detection • Object Tracking • Optical Flow • Deep Learning with Keras • Keras and Convolutional Networks • Customized Deep Learning Networks • State of the Art YOLO Networks • and much more! Feel free to message me on Udemy if you have any questions about the course! Thanks for checking out the course page, and I hope to see you inside! Jose
Créer des embeddings et utiliser la recherche vectorielle et le RAG avec BigQuery
Ce cours présente une solution de génération augmentée par récupération (RAG) dans BigQuery permettant de réduire les hallucinations de l'IA. Il décrit un workflow RAG qui couvre la création d'embeddings, la recherche dans un espace vectoriel et la génération de réponses améliorées. Il explique aussi les raisons conceptuelles derrière ces étapes et leur implémentation pratique avec BigQuery. À la fin du cours, les participants seront à même de créer un pipeline de RAG à l'aide de BigQuery et de modèles d'IA générative tels que Gemini, ainsi que des modèles d'embeddings pour traiter leurs propres cas d'hallucinations de l'IA.
Oracle Database SQL Certified Associate 1Z0-071
ORACLE is database number one in the world . if you know Oracle SQL, then you can learn any SQL easily ( mysql, sql server,PostgreSQL, ..). This is one of the most amazing Udemy courses in Oracle SQL. The course covers the oracle university track 100% for : “Oracle Database SQL Certified Associate 1Z0-071” The course starts from zero level to Expert Level, I guarantee for you that you will understand every single lesson in this course because it was created in a very attractive way, you will not feel bored in any lesson in this course. Just watch the videos and do the examples and you will be ready passing the exam. You will find all the presentations and all the SQL scripts attached in every chapter, so no need to waste your time repeating any example I did. Become an Oracle Database SQL Certified Associate and demonstrate understanding of fundamental SQL concepts needed to undertake any database project. Passing the exam illustrates depth of knowledge of SQL and its use when working with the Oracle Database server. Gain a working knowledge of queries , insert, update and delete SQL statements as well as some Data Definition language and Data Control Language, the optimizer, tales and indexes, data modeling and normalization. By passing this exam, a certified individual proves fluency in and a solid understanding of SQL language, data modeling and using SQL to create amd manipulate tables in an Oracle Database. Qualified candidates have knowledge of general computing concepts, knowledge of command line interfaces and experience working in command line. Simply this course is the best….
Introduction to Virtual Reality
This course will introduce you to Virtual Reality (VR). The course will teach you everything from the basics of VR- the hardware and the history of VR- to different applications of VR, the psychology of Virtual Reality, and the challenges of the medium. The course is designed for people who are new to VR as a medium. You may have experienced some virtual reality before, and may have some hardware- but this course is suitable to individuals who have never experienced VR and those who do not have much hardware- we will explain Mobile VR as well as devices such as the Oculus Rift and HTC Vive. Introduction to Virtual Reality is the first course in the Virtual Reality Specialisation. A learner with no previous experience in Virtual Reality and/or game programming will be able to evaluate existing VR applications, and design, test, and implement their own VR experiences/games using Unity by the end of the specialisation.
Backend Master Class [Golang + Postgres + Kubernetes + gRPC]
In this course, you will learn step-by-step how to design, develop and deploy a backend web service from scratch. I believe the best way to learn programming is to build a real application. Therefore, throughout the course, you will learn how to build a backend web service for a simple bank. It will provide APIs for the frontend to do the following things: • Create and manage bank accounts. • Record all balance changes to each of the accounts. • Perform a money transfer between 2 accounts. The programming language we will use to develop the service is Golang, but the course is not just about coding in Go. You will learn a lot of different topics regarding backend web development. They are presented in 6 sections: • In the 1st section, you will learn deeply about how to design the database, generate codes to talk to the DB in a consistent and reliable way using transactions, understand the DB isolation levels, and how to use it correctly in production. Besides the database, you will also learn how to use docker for local development, how to use Git to manage your codes, and how to use GitHub Action to run unit tests automatically. • In the 2nd section, you will learn how to build a set of RESTful HTTP APIs using Gin - one of the most popular Golang frameworks for building web services. This includes everything from loading app configs, mocking DB for more robust unit tests, handling errors, authenticating users, and securing the APIs with JWT and PASETO access tokens. • In the 3rd section, you will learn how to build your app with Docker and deploy it to a production Kubernetes cluster on AWS. The lectures are very detailed with a step-by-step guide, from how to build a minimal docker image, set up a free-tier AWS account, create a production database, store and retrieve production secrets, create a Kubernetes cluster with EKS, use GitHub Action to automatically build and deploy the image to the EKS cluster, buy a domain name and route the traffics to the service, secure the connection with HTTPS and auto-renew TLS certificate from Let's Encrypt. • In the 4th section, we will discuss several advanced backend topics such as managing user sessions, building gRPC APIs, using gRPC gateway to serve both gRPC and HTTP requests at the same time, embedding Swagger documentation as part of the backend service, partially updating a record using optional parameters, and writing structured logger HTTP middlewares and gRPC interceptors. • Then the 5th section will introduce you to asynchronous processing in Golang using background workers and Redis as its message queue. We'll also learn how to create and send emails to users via Gmail SMTP server. Along the way, we'll learn more about writing unit tests for our gRPC services that might involve mocking multiple dependencies at once. • The final section 6th concludes the course with lectures about how to improve the stability and security of the server. We'll keep updating dependency packages to the latest version, use Cookies to make the refresh token more secure, and learn how to gracefully shut down the server to protect the processing resources. As this part is still a work in progress, we will keep making and uploading new videos about new topics in the future. So please come back here to check them out from time to time. This course is designed with a lot of details, so that everyone, even those with very little programming experience can understand and do it by themselves. I firmly believe that after the course, you will be able to work much more confidently and effectively on your projects.
User Research Methods and Practices
This course introduces the fundamentals of user research methods and practices. Understanding users, identifying their concerns, and addressing their frustrations are key to designing usable, engaging, and persuasive UX products. The course explores various techniques for gathering insightful user data, offering participants the opportunity to delve into user behavior and learn how to interpret this data to uncover opportunities for design improvement. Learning Outcomes -Identify User Needs: Understand user concerns to design engaging solutions. -Apply Research Methods: Learn techniques to gather and analyze user data. -Analyze Behavior: Interpret user behavior to uncover design opportunities.
Unity C# Scripting : Complete C# For Unity Game Development
This Course will Teach You everything that you need to get started with C# scripting in Unity. You will learn step by step from scratch every feature of the C# language as well as how to implement it in Unity's API for building Games. All The Content works fine in Unity 6, Unity 2023, 2022 and older versions. List of Things You Will Learn: • Learn C# Language from absolute basics • Master basic Programming concepts • Learn Unity's API • Learn Object Oriented Programming Concepts • Create Ready To Use C# Scripts • Apply Your C# Skills for Building Android / Mobile Games • Implement Basic AI Features With C# • Learn Version Controlling With Github, Bitbucket, Source Tree I have taught C# Scripting to thousands of people on my Youtube Channel: Charger Games. I love teaching complex concepts in a simple way, so even if you have no previous coding experience, no need to worry, I'm gonna teach you everything step by step in the perfect order. Learn the basic concepts, tools, and functions that you will need to build fully functional Games with C# and the Unity game engine. Build a strong foundation in C# Scripting and Unity Game Development with this course. • Get Started With C# programming • Learn fundamentals of Unity API • Learn Object Oriented Programming Concepts • Create Reusable C# scripts • Learn Intermediate C# Concepts in Unity • Take Your C# Skills to the next level A Powerful Skill at Your Fingertips Learning the fundamentals of C# Scripting in Unity puts a powerful and very useful tool at your fingertips. Unity is free, easy to learn, has excellent documentation, and is the game engine used for building games. Jobs in unity game development are plentiful, and being able to learn C# Scripting along with Unity game development will give you a strong background to more easily build awesome games. Content and Overview Suitable for beginning programmers, through this course of 100+ lectures and 20+ hours of content, you’ll learn all of the Unity C# Scripting fundamentals and establish a strong understanding of the concept behind C# programming. Each chapter closes with quizes, putting your new learned skills into practical use immediately. Starting with the installation of the Unity , Visual Studio , this course will take you through various C# language features and how to use them. By creating example C# Scripts, you’ll a establish a strong understanding of unity game development. With these basics mastered, the course will take you through building different example games with unity to learn more about the process of creating mobile android games with unity. Students completing the course will have the knowledge to create fully functional Games with C# or use their C# skills to Build any other useful thing that they want. Complete with working files, you’ll be able to work alongside the author as you work through each concept, and will receive a verifiable certificate of completion upon finishing the course.
JavaScript, jQuery, and JSON
In this course, we'll look at the JavaScript language, and how it supports the Object-Oriented pattern, with a focus on the unique aspect of how JavaScript approaches OO. We'll explore a brief introduction to the jQuery library, which is widely used to do in-browser manipulation of the Document Object Model (DOM) and event handling. You'll also learn more about JavaScript Object Notation (JSON), which is commonly used as a syntax to exchange data between code running on the server (i.e. in PHP) and code running in the browser (JavaScript/jQuery). It is assumed that learners have already taken the Building Web Applications and Building Database Applications in PHP courses in this specialization.
Playwright Automation Testing 2026: TypeScript, AI & MCP
Build a production-grade Playwright framework — and let AI agents do half the work. Updated August 2026: Playwright Agents, MCP servers and AI-editor workflows Most Playwright courses teach you to write tests. This one teaches you to build the framework a real QA team ships — and then shows you how to generate, refactor and document it with AI agents in a fraction of the time. No 60-hour lecture marathon. No theory you'll never use. In focused, hands-on sessions you go from npm init to a complete, CI-integrated automation framework — every line of code written on screen, every project source code is available to download What you'll actually build: Project 1 — E2E banking app suite: login/logout flows, feedback forms, search, fund transfers, transaction filtering, payments and a currency-exchange challenge you solve yourself. Project 2 — REST API test suite: full CRUD coverage, token authentication, JSON assertions and a CI pipeline that runs it on every commit. Project 3 — AI-generated framework: a complete Playwright project scaffolded, refactored to the Page Object Model, converted from JavaScript to TypeScript and documented — driven almost entirely by prompts. You'll finish this course able to: Set up Playwright with TypeScript on any project, correctly, in under 10 minutes Write tests that don't break every sprint Structure a framework that scales past large tests suites Use AI agents to do the repetitive 80% — and know when not to trust them Who this is for? Manual testers moving into automation (JavaScript basics are covered from scratch) Selenium, Cypress or Puppeteer users migrating to Playwright QA engineers and SDETs who need a framework, not a tutorial Developers who want reliable E2E coverage without hiring a QA team Is Playwright worth learning if I already know Cypress or Selenium? Yes. Playwright runs on Chromium, Firefox and WebKit from one API, auto-waits by default, tests APIs natively and now ships its own AI agents. Job postings have followed. There's a dedicated migration lecture for Cypress and Selenium users. What if it's not for me? Udemy's 30-day money-back guarantee. No questions, no forms. Enroll now, open your editor, and have your first Playwright test running in the next 15 minutes.
Scene Detailing, Prop Creation, and Rendering
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. In this course, you will learn the complete process of scene detailing, prop creation, and rendering in Blender, focusing on creating visually appealing 3D environments. From balcony designs and architectural details to props and realistic textures, this course covers a broad range of techniques to help you enhance the aesthetics and functionality of your models. By the end of the course, you'll have a solid understanding of how to apply textures, craft realistic props, and optimize your scenes for rendering. The journey begins with learning how to create intricate balcony designs, such as stylized tile patterns, rounded roofs, and functional attachments. You’ll move on to mastering the creation of props like plant vases, woven baskets, fabric bags, and structural supports, focusing on modeling, texturing, and reusing elements in different spaces. With a comprehensive approach, you’ll tackle each prop and scene enhancement step-by-step, focusing on techniques that help you create both stylized and realistic objects. The course progresses with advanced techniques for creating detailed props such as barrels, crates, and carpets, as well as optimizing your scene’s layout for the best rendering outcome. You’ll explore how to use geometry nodes for dynamic foliage, integrate decorative elements for visual appeal, and finalize compositions for high-quality renders. Additionally, you will learn how to refine textures, manage light sources, and enhance terrain realism, ensuring that every detail of your scene contributes to the overall visual impact. This course is ideal for anyone interested in architectural visualization, 3D modeling, and rendering. If you're an intermediate user looking to expand your skills, this course provides the advanced tools required to elevate your 3D design projects. Basic knowledge of Blender, including navigation and essential modeling tools, is recommended.
RAG Agents: Build Apps & GPTs with APIs/MCP, LangChain & n8n
One of the most important concepts in the AI world is "RAG" / Retrieval-Augmented Generation. You need to give LLMs knowledge! But how do you build powerful RAG chatbots and intelligent AI agents to optimize your business processes and personal projects? In this course, you’ll learn exactly that—comprehensively and clearly explained—using ChatGPT, Claude, Google Gemini, open‑source LLMs, Flowise, n8n, and more! Fundamentals: LLMs, RAG & Vector Databases Build a solid foundation for your AI projects: • Deepen your knowledge of LLMs: ChatGPT, Claude, Gemini, Deepseek, Llama, Mistral, and many more. • Understand how Function Calling and API communication work in LLMs. • Learn why vector databases and embedding models are the heart of RAG. • Master the ChatGPT interface, GPT models, settings, and the OpenAI Playground. • Explore key concepts like Test‑Time Compute (e.g. OpenAI o1, o3; Deepseek R1). • Discover how Google’s NotebookLM works and leverage it effectively for RAG projects. Simple RAG Implementations with ChatGPT & Custom GPTs Get your first AI applications up and running quickly and easily: • Create your very first RAG bot from PDFs using Custom GPTs. • Turn HTML web pages and YouTube videos into interactive RAG chatbots. • Train ChatGPT on your personal writing style via RAG. • Use CSV data to build smart chatbots and explore the full potential of Custom GPTs. RAG with Open‑Source LLMs: AnythingLLM & Ollama Dive into the world of local AI: • Install and use Ollama: learn about models, commands, and hardware requirements. • Integrate AnythingLLM effectively with Ollama—optimize chunking and embeddings. • Build local RAG chatbots and precisely control language and behavior with system prompts and temperature settings. • Leverage agent capabilities like web search, scraping, and more. Flowise: RAG with LangChain & LangGraph Made Easy Harness the power of the OpenAI API for professional applications: • Master the OpenAI API, pricing models, GDPR compliance, and project setup. • Build efficient RAG applications via the OpenAI Playground and response APIs. • Install Flowise, manage updates, and become proficient with its interface—including the Marketplace and OpenAI Assistant. • Create comprehensive RAG chatflows with web scraping, embeddings, HTML splitters, and vector databases. • Develop your own chatbot UI and handle Flowise’s technical details. • Implement local AI security with Ollama & LangChain and use Flowise’s tool‑agent nodes (e.g. email, calendar, Airtable). • Combine Pinecone vector databases with Supabase and Postgres. • Master prompt engineering and sequential agents with human‑in‑the‑loop workflows. n8n: Building AI Automations & RAG Agents Use n8n as a powerful automation platform for your AI projects: • Learn local installation, updates, and n8n basics. • Automate Pinecone database updates via Google Drive. • Develop RAG chatbots with AI‑agent nodes, vector databases, and supplementary tools. • Create automated chatbots from websites using HTML requests and scraping. Hosting, Selling & Monetizing Your RAG Agents Take your AI projects to market professionally: • Host Flowise and n8n apps on platforms like Render and embed them in websites (HTML, WordPress). • Design branded, professional chatbots and offer them as services or standalone products. • Develop effective marketing and sales strategies for your AI agents. Advanced Workflows & Specialized RAG Techniques Adopt professional, cutting‑edge technologies: • Learn advanced techniques like webhooks, MCPs with Claude, GPT Actions, and n8n integration. • Understand the Model Context Protocol (MCP) and build both MCP servers and clients in n8n and Claude Desktop. • Explore innovative RAG strategies such as Cache‑Augmented Generation (CAG), GraphRAG (Microsoft), LightRAG, and Anthropic’s Contextual Retrieval. • Optimize chunking, embedding, and Top‑K retrieval for your RAG apps. • Choose the right strategy for your projects and maximize your RAG outcomes. Security, Privacy & Legal Foundations Protect your AI projects effectively: • Recognize security risks (Telegram exploits, jailbreaks, prompt injections, data poisoning). • Secure your AI against attacks and respect copyrights in generated content. • Deepen your understanding of GDPR and the upcoming EU AI Act to ensure legal compliance. Become an expert in AI automations, AI agents & RAG! By the end of this course, you will be fully equipped to build, optimize, and successfully market RAG chatbots, AI agents, and automations.
C Programming: Using Linux Tools and Libraries - 7
Learn how to use professional tools and libraries to write and build C programs within the Linux operating system. This seventh and final course in the C Programming with Linux Specialization will allow you to develop and use your C code within the Linux operating system. Using libraries in C is a fundamental concept when it comes to sharing code with others. In addition to compiling and linking, you will also learn how to pass arguments to an executable program. As you embark on your future career as a programmer, you will be able to continue your coding adventures with professional coding environments used by C programmers around the world. Why learn C and not another programming language? Did you know that smartphones, your car’s navigation system, robots, drones, trains, and almost all electronic devices have some C-code running under the hood? C is used in any circumstance where speed and flexibility are important, such as in embedded systems or high-performance computing. At the end of this course, you will reach the last milestone in the C Programming with Linux Specialization, unlocking the door to a career in computer engineering. Your job Outlook: - Programmers, developers, engineers, managers, and related industries within scientific computing and data science; - Embedded systems such as transportation, utility networks, and aerospace; - Robotics industry and manufacturing; - IoT (Internet of Things) used in smart homes, automation, and wearables. - IEEE, the world’s largest technical professional organization for the advancement of technology, ranks C as third of the top programming languages of 2021 in demand by employers. (Source: IEEE Spectrum) This course has received financial support from the Patrick & Lina Drahi Foundation.
AI System Design & MLOps: From Raw Data to AWS Kubernetes
AI System Design & MLOps: From Raw Data to AWS Kubernetes (End-to-End Project) Stop Learning Machine Learning in Isolation Most machine learning courses focus on building models in isolation. You train a model, evaluate accuracy, and consider the job done. But in real-world systems, that is only a small part of the problem. Organizations do not need models. They need systems that can: • ingest and process real-world data • generate reliable predictions • serve those predictions through APIs • monitor performance over time • adapt when data changes This course is designed to bridge that gap. The Story Behind This Capstone Imagine a large hospital network handling thousands of patients every day. Patients arrive with different conditions. Some cases are routine, while others escalate into high-risk situations requiring immediate attention. At the same time, every visit generates billing records, which are later submitted to insurance providers. Some claims are approved quickly, while others are delayed or rejected, leading to revenue loss and operational inefficiencies. Now consider the questions hospital leadership is asking: • Can we identify high-risk patient visits early so that resources can be allocated proactively? • Can we predict which claims are likely to be rejected before they are submitted? • Can we continuously monitor the system and adapt when patient patterns or insurance behaviors change? These are not just modeling questions. They require a complete, well-designed system. In this course, you will build that system from the ground up. What You Will Build You will design and implement a complete healthcare AI platform that includes: 1. Data Layer You will start with raw datasets such as patients, visits, and billing records. Instead of working directly on CSV files, you will create a structured analytics layer using SQL, ensuring that data can be queried, validated, and joined properly. You will then perform exploratory data analysis and build meaningful features such as visit frequency, average length of stay, and provider rejection rates. 2. Machine Learning Layer You will build two real-world models: • A visit risk classifier that predicts whether a patient visit is low, medium, or high risk • A claim outcome predictor that determines whether a claim will be paid, pending, or rejected You will implement multiple algorithms, including Logistic Regression, Random Forest, and XGBoost, and evaluate them using proper metrics such as precision, recall, and F1 score. More importantly, you will understand how data quality impacts model performance and how fixing labels can dramatically improve outcomes. 3. MLOps Layer This is where the system becomes production-ready. You will integrate: • MLflow for experiment tracking and model versioning • DVC for data versioning and reproducible pipelines You will define clear artifacts such as trained models, feature schemas, and prediction logs, ensuring that every step in the pipeline is traceable and repeatable. 4. Serving Layer You will expose your models through a FastAPI-based service with well-defined endpoints for prediction. You will enforce input validation using Pydantic and build a browser-based interface using Gradio for demonstration purposes. You will also implement monitoring mechanisms such as PSI-based drift detection to identify when the system starts behaving differently due to changes in incoming data. 5. Cloud Deployment Layer You will containerize your application using Docker and push images to AWS Elastic Container Registry. You will then deploy the system on AWS EKS using Kubernetes, enabling scalability, high availability, and zero-downtime updates. A complete CI/CD pipeline using GitHub Actions will automate build, test, and deployment steps. 6. Continuous Retraining Loop The system does not stop after deployment. You will implement a feedback loop where: • predictions are logged • drift is detected • retraining is triggered using DVC pipelines This ensures that the system continuously improves as new data flows in. How This Course Connects the Dots One of the biggest challenges in learning AI and machine learning is fragmentation. You learn SQL in one place, modeling in another, APIs somewhere else, and cloud deployment separately. This course connects all of these pieces into a single, coherent system. You will see how: • raw data flows into structured analytics • features feed into models • models are tracked and versioned • predictions are served via APIs • systems are deployed to the cloud • monitoring drives retraining By the end, you will not just understand individual tools. You will understand how they work together. Who This Course Is For This course is ideal for: • software engineers who want to transition into AI/ML systems • machine learning practitioners who want to learn production deployment • backend developers interested in building AI-powered APIs • architects who want to understand end-to-end AI system design What You Will Walk Away With By the end of this course, you will have: • built a complete end-to-end AI system • deployed it on AWS using modern cloud practices • implemented monitoring and retraining mechanisms • developed a strong understanding of production-first architecture More importantly, you will develop the ability to think beyond models and design systems that deliver real business value. Final Note This is not a course about isolated concepts. It is about building something that resembles real-world systems. If your goal is to move from learning machine learning to applying it in production, this course is designed for you. Production-first architecture is not an advanced topic. It is the standard.
Agile Retrospective: Kaizen with Scrum
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. This course is your gateway to mastering the art of Sprint Retrospectives, a crucial aspect of Agile practices that can significantly enhance your team's efficiency. Starting with an overview of Agile Scrum, you'll be introduced to the core concepts of Sprint Retrospectives. Each lesson is carefully crafted to simplify complex ideas, making it accessible to both beginners and seasoned professionals. You'll learn the essential elements of a successful retrospective, how to timebox effectively, and the importance of focusing on team needs. As you progress, the course delves deeper into advanced strategies for conducting retrospectives. You'll explore tips and techniques that challenge the mundane, encourage creative thinking, and promote continuous improvement. Real-world examples and case studies will provide you with a practical understanding of how to implement these strategies in your team. Whether it's switching up facilitation styles or involving remote teams, this course ensures you're equipped with the tools needed to foster a productive retrospective environment. By the end of this course, you’ll be able to lead Sprint Retrospectives with confidence, ensuring that each session is not just a routine meeting, but a powerful tool for driving your team’s success. With actionable takeaways and practical tips, this course empowers you to make every retrospective count, ultimately leading to sustained team improvement and project success. This course is useful for Scrum masters, product owners, business owners, support teams, maintenance teams, service and sales teams, development support teams, and anyone who wants a complete overview of Agile Scrum Retrospectives.
Clean Code
As a developer, you should be able to write code which works - of course! A lot of developers write bad code nonetheless - even though the code works. Because "working code" is not the same as "clean code"! This course teaches you how to write clean code - code that is easy to read and understand by humans, not just computers! In this course, you'll learn what exactly clean code is and, more importantly, how you can write clean code. Because if your code is written in a clean way, it's easier to read and understand and therefore easier to maintain. Because it's NOT just the computer who needs to understand your code - your colleagues and your future self needs to be able to understand it as well! In this course, we'll dive into all the main "pain points" related to clean code (or bad code - depending on how you look at it) and you will not just learn what makes up bad code but of course also how to turn it into clean code. Specifically, you will learn about: • Naming "things" (variables, properties, classes, functions, ...) properly and in a clean way • Common pitfalls and mistakes you should avoid when naming things • Comments and that most of them are bad • Good comments you might consider adding to your code • Code formatting - both horizontal and vertical formatting • Functions and how to limit the number of function parameters • How to write clean functions by focusing on "one thing" • How levels of abstraction help you split functions and keep them small • How to write DRY functions and avoid unexpected side effects • Avoiding deeply nested control structures with guards and by extracting functionality into functions • Errors and error handling as a replacement for if-statements • Objects & data containers/ data structures and why that differentiation could matter • Cohesion and how to write good (small!) classes • The Law of Demeter and why it matters for clean code • What the SOLID principles are and why they matter when it comes to writing clean code • Much more! This course is a compilation of common patterns, best practices, principles and rules related to writing clean code. In this course, you'll learn about a broad variety of concepts, rules, ideas, thoughts and principles and by the end of course, you'll have a good idea of what to keep in mind when it comes to writing clean code. This is not a design patterns or general patterns course though - we will entirely focus on patterns, rules and concepts that help with writing clean code specifically. All these concepts and rules are backed up by examples, code snippets and demos. And to ensure that you get the most out of this course, and you don't just learn a bunch of theory which you forget soon after, there also are plenty of challenges for you to apply what you learned! This course uses Python, JavaScript and TypeScript for code examples but you don't need to know these languages to follow along and get a lot out of the course. In addition, the course does not focus on a specific programming style or paradigm (like functional programming, object-oriented programming etc) but instead covers general concepts and techniques which will always apply. What are the course prerequisites? • Basic programming knowledge (no matter which language) is required! • You don't need to know any specific programming language or programming paradigm to follow along • NO prior experience with writing clean code is required
Структуры данных Python
В данном курсе описываются основные структуры данных языка программирования Python. Будут рассмотрены основы процедурного программирования, а также способы использования встроенных структур данных Python, например, списков, словарей и кортежей для выполнения сложного анализа данных. В данном курсе рассматриваются главы 6-10 учебника «Python для всех». В этом курсе речь идет о языке Python 3.
Ollama & Local LLMs: Fine-Tune, Deploy, Build Python AI Apps
If you are tired of black-box cloud APIs and want AI that runs on your hardware, keeps your data local, and still ships like a real product, this course gives you a complete path from first Python call to a deployable model and a capstone app you can show in a portfolio. You start with Olloma + Python (chat, streaming, generation patterns you reuse everywhere), then move into Streamlit apps, RAG-style assistants, multi-agent workflows, Unsloth + QLoRA fine-tuning, export into Ollama, and finish with a full local coding assistant (browser, editor, diffs, run code, shell, optional web research and vision hooks). Theory never floats alone: every idea maps to working code and a clear next step. What makes this course practical You build, not only watch. Expect real tools: chat UIs, PDF Q&A, embedding search, personal note and diary apps, CrewAI agent teams, Whisper + Ollama video Q&A, and a large Streamlit coding IDE powered by Ollama. You also fine-tune a small instruct model, compare base vs fine-tuned answers, merge adapters, and ship the result through Ollama, including straight talk on quantization and quality so your exports behave the way you expect. In this course, you will • Wire up Ollama from Python using chat, streaming, and generation patterns that repeat across the whole curriculum. • Ship Streamlit front ends on top of local models, including vision demos and media flows (frames, Whisper transcription, questions over audio). • Build retrieval-style assistants: PDF context, LangChain templates and chains, chunking for long text, and spaCy embedding search from similarity through full chunk retrieval. • Orchestrate multi-step AI with LangChain and CrewAI (Ollama-backed agents, sequential workflows, domain-style examples). • Run Hugging Face models locally and stretch into extra modalities when your hardware allows (text-to-speech, text-to-video runners). • Train a personalized small LLM with Unsloth + QLoRA, watch validation for catastrophic forgetting, test against the base model, merge adapters, and package for Ollama with a Modelfile and export notes you can follow on a real machine. • Finish a capstone: a local LLM-assisted coding environment (project browser, editor, streaming chat, apply changes with diff review, run code and shell, optional web research, planning, persistence, and more). Why local LLMs matter You own your stack: privacy, predictable cost, and the freedom to specialize a model on your data and ship prototypes without betting everything on one cloud provider. Why learn from this course You get numbered, file-based progression, copy-paste-friendly projects, and troubleshooting for real setups (CUDA PyTorch, Windows compiler and Triton notes, protobuf conflicts, pip and Hugging Face caches). The goal is fewer weekends lost to environment issues and more time shipping. Before you enroll Comfortable Python basics (install packages, run scripts, read errors). A recent NVIDIA GPU is strongly recommended for fine-tuning, Unsloth work, and several advanced demos. Some lessons need ffmpeg or large downloads; plan disk space and time for first-time model pulls. How to get the most from the course Watch the promo, sample the free preview. When you enroll, your outcome is simple: private AI on your PC that you run, train, export, and productize yourself.
.Net平台下的软件开发技术毕业项目
毕业设计项目将综合5门课程所学知识，设计完成一个基于.Net平台的小型软件项目，以验证你是否具备了.Net应用程序开发的基本能力。 项目具体要求如下： 1. 该系统应该包括客户端和管理端； 2. 客户端包括以下功能： ①用户登录； ②用户注册； ③菜品订购； ④购物车功能； ⑤订单增、删、改、查功能； 3. 管理端包括以下功能： ①用户管理； ②订单管理（增、删、改、查）； ③菜品管理（增、删、改、查）； ④统计管理（日销量、月销量、用户订餐细节）。 如果你能够在.Net环境下利用C#语言独立完成毕设项目，说明你已经达到面向.Net框架的初级程序员水平。
Master Git and GitHub in 5 Days: Go from Zero to Hero
Understanding how to use Git and GitHub is now a basic requirement for any developer, but so many courses take forever to teach you anything of value! Unlike those other courses, we've specifically designed this course to teach you the 10% of Git commands that you use 90% of the time! When you're just starting off with git you don't want to waste time learning about commands you hardly ever use, especially when you could always easily look them up later. Instead this course focuses on giving you a Bootcamp style approach to turn you into a PRO in just ONE WEEK! Why learn Git and GitHub? Git and GitHub allow you to easily keep different versions of a large codebase organized. When working almost any job as a developer, understanding git and GitHub is an essential skill. It's also one of the very first things you need to know to hit the ground running at a new position, which is why this course is specifically designed to get you from zero to hero in just 5 days! We've designed the course in a 5 day format so you can get up and running in just one work week. Why choose this course? Many other courses waste time covering the same topics over and over again in a dull and repetitive format, instead of focusing on what you need to know in the real world! We've designed this course for someone who just started a new developer role and needs to get up to speed on git and GitHub in their first week, which is why the sections are organized in a 5 day format. With just approximately one hour a day you can go from Zero to Hero with git and GitHub! What's covered in this course? We cover a wide variety of the most important topics in git and GitHub, including: • Understanding Version Control • Git and GitHub Setup • Code Repository Basics • Snapshots and Applications • Basic git commands • Working with Branches • Merges and Changes • Cloning Repos • Understanding git stash • Checking for differences between commits • Using git as an organization Throughout the course you'll be provided with example code, diagrams, and slides so you have easy to understand references you can come back to whenever you need. Enroll today and we'll see you inside the course!
Data Collection and Processing with Python
This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a “tag recommender” for the flickr photo sharing site. The course is well-suited for you if you have already taken the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). If you are already familiar with Python fundamentals but want practice at retrieving and processing complex nested data from Internet services, you can also benefit from this course without taking the previous two. This is the third of five courses in the Python 3 Programming Specialization.
Git & GitHub - The Practical Guide
No matter if you're just getting started with (web) development, if you're applying for a developer job or if you just need to refresh your knowledge - version control is a core skill you need to succeed as a developer! Git (a version control system) and Github (a cloud provider for Git managed projects) form an outstanding combination to provide the best possible experience to create and maintain a clearly structured project history! This course guides everyone (no prior knowledge is required!) through the core steps to use these tools in your daily projects with ease. What is Version Control? Saving & accessing data and tracking changes is what version control is all about. No matter if you're working on a private or a professional development project, code evolves, changes and continuously gets improved. A clean version management structure is therefore key to successfully manage the progress of your projects. What is Git? Git is a 100% free version management tool, specifically created for and used by developers all over the world to manage project code history locally on their machines (Windows, macOS, Linux/Unix). What is GitHub? GitHub is an online service, it is also free for many use cases (an account is all you need) and brings Git's local "file-tracking" strengths to the cloud. Storing project code online, updating code, accessing other team members' code or collaborating on large scale projects inside your organization - all possible with the help of GitHub! Why Should I Know these Tools? Version control is key to manage projects efficiently so not knowing Git and GitHub makes your daily developer life a lot more complicated. The same apply if you're currently looking for a new job in the industry, version control is required in any developer projects these days, so not knowing Git & GitHub puts you behind your competition! Although Git and GitHub are user friendly, both come with their own logic and "language". Getting started can therefore be a bit cumbersome and this is where this course comes into play! What do I Learn in this Course? This course starts at the very basics, no prior Git or GitHub knowledge is required! You'll learn how to use Git and how to write Git commands in the Mac Terminal or the Windows Command Prompt (optional refreshers on both are also part of the course). Starting with the first initialization of a so-called Git repository, we'll build up your knowledge step-by-step and understand the what & why behind concepts like branches, commits, the staging area, merging & rebasing, cloning, pushing & pulling branches and a lot more! What's Inside this Course? • An optional Command Line Crash Course for both Windows & MacOS users • Git Download & Installation • Git Theory - Working Directory, Staging Area (Index) and Repository explained • Creating Git Repositories • Working with Commits • Understanding Branches • Understanding the HEAD and the detached HEAD • Newly Introduced Git Commands with Git Version 2.23 • Deleting Data (Staged & Unstaged, Commits & Branches) • Ignoring Files • The Stash • Merging, Rebasing and Cherry Picking • Bringing Back Deleted Data with the Reflog • Connecting Local Git Repositories to Remote GitHub Repositories • Git Push & Pull (+ Fetch) • Local, Remote Tracking & Remote Branches • GitHub Collaborators & Contributors • Forks & Pull Requests • GitHub Issues • Github Projects • and so much more! All covered, explained and applied in easy to understand examples in the course! - In this course we'll find answers to questions like: "How can I delete my last commit?" "What is the Stash?" "What is the difference between a merge and a rebase (and what is cherry-picking actually)?" "How to bring back a deleted commit?" "What is the difference between a local tracking branch and a remote tracking branch?" - What are you waiting for, jump and board and let's GIT started :)
Building Agentic RAG with LlamaIndex
Join our new short course and learn from Jerry Liu, co-founder and CEO at LlamaIndex to start using agentic RAG, a framework designed to build research agents skilled in tool use, reasoning, and decision-making with your data. In this course: 1. Build the simplest form of agentic RAG – a router. Given a query, the router will pick one of two query engines, Q&A or summarization, to execute a query over a single document. 2. Add tool calling to your router agent where you will use an LLM to not only pick a function to execute but also infer an argument to pass to the function. 3. Build a research assistant agent. Instead of tool calling in a single-shot setting, an agent is able to reason over tools in multiple steps. 4. Build a multi-document agent where you will learn how to extend the research agent to handle multiple documents. Unlike the standard RAG pipeline—suitable for simple queries across a few documents—this intelligent approach adapts based on initial findings to enhance further data retrieval. You’ll learn to develop an autonomous research agent, enhancing your ability to engage with and analyze your data comprehensively. You’ll practice building agents capable of intelligently navigating, summarizing, and comparing information across multiple research papers from arXiv. Additionally, you’ll learn how to debug these agents, ensuring you can guide their actions effectively. Explore one of the most rapidly advancing applications of agentic AI!
DevOps MasterClass: Terraform Kubernetes Ansible Docker
Ready to take your career to new heights? Look no further! Our comprehensive DevOps MasterClass is your gateway to becoming a sought-after DevOps professional. With a robust curriculum encompassing Terraform, Git, Ansible, Jenkins, Docker, Docker Swarm, Kubernetes, and much more, this course equips you with the essential skills to excel in the dynamic world of DevOps. Disclaimer: This course requires you to download [Jenkins, Docker Desktop]. If you are a Udemy Business user, please check with your employer before downloading any software to ensure compliance with your organization’s policies. What You'll Learn: Terraform: Master the art of infrastructure as code and orchestrate resources effortlessly. Git and GitHub: Gain proficiency in version control and collaborative software development. Ansible: Automate your infrastructure and configuration management for streamlined operations. Jenkins: Unleash the power of continuous integration and continuous deployment (CI/CD). Docker: Containerize your applications for easy deployment and scaling. Docker Swarm: Learn container orchestration to manage and scale containers efficiently. Kubernetes: Dive into the world of container orchestration with hands-on Kubernetes expertise. Why Choose Our DevOps MasterClass? Comprehensive Curriculum: Covering the entire DevOps spectrum, you'll acquire the skills you need to excel in this dynamic field. Expert Instructors: Learn from industry professionals with years of practical experience in DevOps. Real-world Projects: Apply your knowledge to real projects and build a portfolio that showcases your skills. Community Support: Join a network of like-minded learners and interact with peers and instructors. Career Advancement: Unlock endless career opportunities with in-demand DevOps skills. Certification: Receive a prestigious certificate upon course completion to add to your resume. Don't miss out on this opportunity to transform your career and become a DevOps pro. Enroll today and take the first step towards a brighter future. Become the DevOps expert companies are looking for – enroll now!
Monitoring and Observability for Development and DevOps
Application developers and DevOps professionals must ensure their app works at its best. However, these app may need help with bugs, slow speed, or subpar performance. Professionals need to monitor and observe its performance continually. Application monitoring involves identifying, measuring, and evaluating the effectiveness of an application. On the other hand, Observability refers to how well an app can be monitored by the data obtained from monitoring. Both monitoring and observability are necessary to gain insights into the system and ensure its proper functioning. This course thoroughly introduces monitoring and observability, covering fundamental concepts and popular tools like Prometheus, Grafana, Mezmo (LogDNA), and Instana. You will also learn about the three pillars of observability and tracing for container applications and gain hands-on experience with the OpenTelemetry framework. Throughout the course, you will complete interactive hands-on labs to apply your knowledge, and gain experience with the tools and techniques used by software and DevOps professionals. By the end of this course, you will be able to demonstrate your knowledge of monitoring and observability, and you will gain the confidence to perform these tasks in a practical setting.
The Advanced SQL Course
If you have some experience with SQL and want to develop your query skills to the next level from intermediate to advanced then this is the perfect course for you! No downloads or software installation required. We will be using Oracle APEX which is a web-based application – you will be set up with your own virtual database hosted on the cloud! Although we will be using Oracle APEX the course has been designed to highlight key differences between some of the main Database Management Systems such as MySQL and Microsoft SQL Server, so what you learn in this course can be applied across all platforms supporting SQL. This course will cover: • Analytical (Window) Functions • Regular Expressions (RegEx) • Materialized Views • Extensions to Group By • Correlated Subqueries • Common Table Expressions • Hierarchical Queries • Data Cleansing • Data Manipulation The lectures in this course are arranged into short, bite-sized chunks. The course is designed to be comprehensive, but also concise in order to make the learning experience as easy as possible. Each section of the course has been specifically tailored to give the optimal learning experience, sections are packed with quizzes, assignments and real world type scenarios to give you an opportunity to develop your practical skills. As your instructor I have 10+ years of professional experience consulting and working for a range of publicly listed companies. I have worked extensively across multiple database management systems including Oracle, MySQL and Microsoft SQL Server. I hope to see you enrolled in the course!
SCHC : A new era of interoperability
Welcome to "SCHC: A New Era of Interoperability" Are you ready to explore the cutting edge of IoT communications? We're about to embark on a fascinating journey into Static Context Header Compression (SCHC), a groundbreaking technology that's revolutionizing how IoT devices communicate across networks. This comprehensive course combines theoretical foundations with hands-on practical experience, offering you a unique opportunity to master a technology that's shaping the future of device interconnectivity. Throughout this course, you'll discover how SCHC optimizes network communications, making IoT deployments more efficient and scalable than ever before. You'll explore into the architecture of SCHC, understand its implementation in real-world scenarios, and gain practical experience through our carefully designed hands-on exercises. Whether you're an IoT developer looking to enhance your skills, a network engineer seeking to optimize your infrastructure, or a technical professional eager to stay ahead of industry trends, this course will equip you with the knowledge and practical skills you need. Our interactive learning approach combines engaging lectures with real-world demonstrations and practical laboratories, ensuring you not only understand the concepts but can apply them confidently in your own projects. By the end of this course, you'll be well-prepared to implement SCHC in your IoT solutions and contribute to the evolving landscape of connected devices. Join us as we step into the future of IoT interoperability and discover how SCHC is transforming the way our connected world communicates.
ISTQB® Test Analyst Advanced Level (CTAL-TA) 2026
This course maps to the latest ISTQB® advanced level test analyst syllabus v4.0. The course is up to date with the latest syllabus from ISTQB® The ISTQB® Advanced Tester Certification—Test Analyst training course expands on the test design techniques and methods introduced in the ISTQB® Foundation certification course. The course focuses on the key areas that are vital for successful test analysis and design: the testing process, test management, test design techniques, software quality characteristics, reviews, defect management and test tools. It is very tough to prepare for the exam by yourself because of the lack of ISTQB® Advanced Level Test Analyst resources but this course is here to help you overcome this issue. I have included everything you might need to know to understand the syllabus of the CTAL-TA fully. I have included explanations to every topic in separate short videos plus sample questions for you to practice for the exam, The course is filled with hands-on exercises to help you practice the methods and techniques taught in this course. Video explanations of the sample questions of why and how to pick the right answer in a short time. I have also included extra videos that I thought will help in speeding up the process of comprehending the syllabus. My name is Maged Koshty, the managing director of ExpertWave. I have over than 30 years of experience in the software industry. I have a solid record in helping 1000s of students pass the ISTQB® Foundation exam and I am here to help you pass the ISTQB® advanced level test Analyst certification exam. I will teach you everything you need to know to pass the exam from the first trail, I will provide you with 100s of sample questions and I will answer any of your questions 24 x 7 This course covers the syllabus for the Advanced Test ِAnalyst certification and will help you prepare for the exam. "This material is not accredited with the ISTQB®". ISTQB® is a registered trademark of the International Software Testing Qualifications Board.
Data Engineering Workflow Orchestration with Airflow
Modern data platforms rely on automated, reliable workflows to move and process data at scale. Data Engineering Workflow Orchestration with Apache Airflow equips you with the skills to design, build, monitor, and deploy production-ready data pipelines using one of the industry’s leading orchestration tools. As organizations shift toward scalable and fault-tolerant data systems, mastering workflow orchestration has become essential for data engineers and backend developers. Through structured lessons and hands-on demonstrations, you’ll learn how Apache Airflow schedules, executes, and monitors workflows across distributed systems. The course covers workflow architecture, task scheduling, operators, sensors, TaskFlow API, data pipeline design, monitoring, retries, logging, debugging, dynamic workflows, performance optimization, and CI/CD-based production deployment practices. By the end of this course, you will be able to: • Design and build scalable data pipelines using Apache Airflow. • Implement workflow orchestration with operators, sensors, and task dependencies. • Monitor, debug, and optimize pipelines using logging, retries, and performance controls. • Deploy and manage production-ready workflows with version control and CI/CD integration. • Apply reliability and data quality best practices in real-world environments. This course is ideal for aspiring data engineers, backend developers, DevOps professionals, analytics engineers, and software engineers looking to strengthen their workflow automation and production data management skills. A basic understanding of Python programming, databases, and data concepts is recommended, though prior experience with Apache Airflow is not required. Join us to master workflow orchestration and build reliable, production-grade data systems with confidence.
Flutter BLoC - From Zero to Hero Complete Course
Hello, everyone! By following this BLoC - From Zero to Hero course, you will successfully learn the BLoC State Management solution, so if you have doubts in understanding or practicing all of its concepts, I really recommend checking it out right here! Before you check it out though, I would like to tell you that this series is designed with both the theoretical and most importantly, practical (coding) parts of every discussed topic. All of the project files can be found on my github page. Also, the series was carefully monitored by the amazing creator of bloc_library, Felix Angelov. On the other hand, without without the slightest restraint I feel like my series is the best bloc_library playlist on the entire internet. Don't take my word for it, try it by yourself! A briefing of everything that's been covered in this playlist, so you know what to expect: • Why BLoC? In this video I explained why I chose bloc_library for both the state management solution and the architectural structure of my apps • BLoC Core Concepts - In this tutorial I got really in-depth in explaining streams, and the concepts of blocs & cubits. • Flutter BLoc Concepts - Here, I discussed each and every single one of bloc_library's concept like BlocProvider, BlocBuilder, BlocListener and many many more. These concepts are obviously explained and tested in every tutorial, since they are the base of bloc_library. • BLoC Architecture - In this tutorial I made a short introduction on what I believe it's the best architecture to follow in order to structure and scale your code over time! This video has no code inside my github page, since I'm planning on using it extensively on my follow-up tutorial series on building real world apps! • BLoC Testing - Testing is one of the most important pillars of programming, oftenly omitted by developers. In this video I'll explain what are the basics of testing a bloc-built small application. • BLoC Access & Navigation - In this tutorial I got really in-depth on what are the routing options on which you can successfully provide a cubit/bloc to the widget tree. • Bloc-to-bloc Communication - Here I wanted all my viewers to understand how important it is to know how to make 2 blocs/cubit communicate one with another. • BuildContext In-Depth - This tutorial is not really related to the bloc_library, but since build contexts are used everywhere inside a flutter app, I realised that most of people didn't understand how they really work. This video is also useful as it spreads out the knowledge gained from tutorial number 3 and 6. • Bloc 6.1.0 - During my tutorial series, a new version of bloc_library got released, containing some important changes like context.watch, context.read and context.select. All of these are covered in this video, as always, with intuitive examples. • Bloc State not Updating - In this video, I explained why most of the new developers encounter this popular issue of a state of a bloc/cubit not updating. • Maintaining State with Hydrated_Bloc - In this tutorial I got really in-depth about how you can store the state of multiple blocs/cubits on the app's internal storage on your device. This is a key concept in developing a successful Flutter app, having bloc_library as the state management feature. • Debugging Blocs/Cubits, Naming Conventions and other tips and tricks is the last video of this series, covering other important topics found inside the flutter_bloc library. Thank you and hopefully you are as excited as I am! WCKD
Introduction to Data Engineering on Google Cloud - Bahasa Indonesia
Dalam kursus ini, Anda akan belajar tentang data engineering on Google Cloud, peran dan tanggung jawab data engineer, dan bagaimana hal tersebut terhubung dengan penawaran yang disediakan oleh Google Cloud. Anda juga akan mempelajari cara untuk mengatasi tantangan terkait data engineering.
Modern Redis Unleashed
You can avoid vendor lock-in with your cloud services by using Redis. Redis has become much more than just a distributed cache; its new Redis Modules architecture runs on any cloud provider and enables true multi-cloud and hybrid cloud deployments. Using Redis, you can distribute systems across many cloud providers, making you immune to outages in any one of them. Redis Modules, Redis Cloud, and Redis Enterprise are important new technologies to know about when designing your cloud computing architecture. This compact course wastes no time! You'll learn by doing, using Redis Stack with a real e-commerce data set to: • Stream data in real time using Redis Streams • Store structured, persistent data into a distributed NoSQL document store with RedisJSON • Index and query structured data with RediSearch • Analyze time series data with RedisTimeSeries and Redis Insight • Create a real-time topseller leaderboard with RedisBloom We will use a free Redis Cloud account and scripts written in Python to illustrate the use of each system. We'll walk you through setting it all up. Redis makes it possible to build a complete technology stack that does not rely on a specific cloud computing vendor. Your colleagues probably still think Redis is just a caching technology; you can be the first to tell them about this new alternative for storing and processing data at massive scale. This concise yet complete training will get you up an running with Redis in the cloud, or on your own cluster. Your instructor is Frank Kane, a former senior manager at Amazon specializing in distributed systems. Frank has taught over 1,000,000 students around the world. * Development of this course was sponsored by Redis Ltd.
Advanced Prompting & AI Tooling
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 advanced course, you'll deepen your expertise in prompt engineering and learn how to craft highly effective prompts for sophisticated AI models. The course covers a range of advanced techniques, such as the "Flip the Script" pattern, self-consistency, function calling, and more. With practical labs, you’ll experiment with these techniques, refining AI-generated prompts, and building more dynamic, flexible, and high-performing AI systems. You'll also dive into function calling and applying it to real-world tasks, as well as improving response quality through decomposition and self-critique. The course also includes a comprehensive project where you will build an AI-powered code reviewer, allowing you to apply your prompt engineering skills in a practical setting. Throughout the project, you’ll enhance the tool with features like Git integration, code logic and syntax checking, self-critique, and the creation of expert personas. The project will culminate with the migration to structured output, improving the tool’s data management and its interaction with other systems. This course is ideal for learners who have a solid understanding of AI models and prompt engineering, and wish to take their skills to the next level by designing more powerful, efficient, and customized AI-driven tools. The course requires experience in programming and basic familiarity with AI principles. By the end of the course, you will be able to build sophisticated AI-powered tools, refine and optimize prompts for complex tasks, and integrate advanced techniques like function calling and self-consistency into your AI systems.
Introduction to AI Automation with n8n & LangChain (no-code)
In today's fast-paced digital landscape, automating repetitive tasks and leveraging the power of artificial intelligence (AI) has become increasingly crucial. This course, "Introduction to AI Automation with n8n and LangChain," is designed to equip you with the skills and knowledge needed to harness the potential of these cutting-edge technologies. Taught by the 2024 n8n Community Award winner for AI Automation Template Creator, this course brings battle-tested automation expertise from a recognized leader in the n8n community. The instructor's templates and automation solutions have been acknowledged by n8n, a powerful platform with over 51,000 GitHub stars, for their innovation and practical value. Whether you're an aspiring automation enthusiast, an entrepreneur struggling to keep up with the demands of a growing business, a corporate innovator seeking to drive digital transformation, or a tech-savvy individual passionate about the intersection of AI and workflow automation, this course has something for you. Throughout this comprehensive program, you'll dive into the versatile n8n platform, a low-code, open-source tool that empowers users to connect various applications and services, streamlining workflows and unlocking new possibilities. You'll learn to leverage n8n's extensive integration capabilities and visual interface to build intelligent automation solutions tailored to your needs. Key highlights of this course include: • Become a Workflow Wizard: Harness the versatility of the n8n platform to create dynamic, interconnected workflows that automate your most time-consuming tasks, freeing you up to focus on higher-value activities. • Unleash the Power of Conversational AI: Dive into chatbots and learn how to build your intelligent virtual assistant, capable of engaging in natural language interactions and providing instant, personalized responses. • Transcend Language Barriers: Explore the Traveler Co-Pilot project and master the art of speech-to-speech translation and image-to-text conversion, which will empower you to navigate foreign environments with confidence and ease. • Empower Your Documents: Dive into the "Chat with Docs" project and learn how to integrate your custom documents with Slack, enabling seamless collaboration and instant access to critical information right at your fingertips. • Unlock the Secrets of Stock Analysis: Assemble a team of AI agents to automate the complex stock analysis process, leveraging the wealth of data in SEC 10K reports to make informed investment decisions and stay ahead of the curve. • Learning Support: Q&A forum to engage with learner community and instructor • Paid n8n templates included: $225 USD worth of templates fully included in the course. • Easy 1 click n8n self-hosting : step-by-step guide to self-host n8n on cloud Throughout the course, you'll have the opportunity to apply the n8n platform to real-world automation challenges, giving you a solid foundation to continue exploring the capabilities of this versatile tool. Additionally, you'll gain hands-on experience in integrating LangChain, a robust framework for building applications with large language models (LLMs), further expanding your AI automation skillset. This course uses the frontier OpenAI API for the exercises, which is a paid API. Completing all the exercises costs less than $1 USD using the gpt4o-mini model. Embark on this exciting journey and unlock new possibilities in streamlining workflows and driving innovation. Enroll in the Introduction to AI Automation with n8n and LangChain course today and become a master of AI-powered automation.
Unreal Engine: Design & Control Game Materials for Beginners
Learn how to design, customize, and control materials in Unreal Engine through a structured, hands-on learning experience. This course guides you from creating basic materials with colors, textures, and nodes to building flexible material systems using masks, vector operations, emissive effects, and material instances. As you progress, you'll explore parameterized materials and discover how to create dynamic material instances that respond during gameplay through Blueprint integration. You'll also learn how to organize material parameters, apply texture maps with UV tiling, and modify visual properties such as color, opacity, and emissiveness efficiently at runtime. Designed for developers and technical artists, this course is ideal for learners who want to strengthen their Unreal Engine material creation skills for games and interactive applications. The three-module structure gradually builds your understanding from material fundamentals to advanced runtime control, making it easier to apply each concept in practice. By the end of the course, you'll be able to create organized node-based materials, build layered visual effects using masks and vectors, configure material instances for efficient workflows, and implement interactive material behavior using Blueprints. If you want to develop more responsive and visually engaging Unreal Engine experiences, this course provides the practical techniques needed to achieve that goal.
No-Code AI & ML: From Data to Deployment Without Coding
Are you eager to dive into the world of machine learning but wary of complex coding? This course is your gateway to understanding and applying machine learning concepts—without writing a single line of code. Designed for beginners and professionals alike, you’ll explore both the theory and practical applications of machine learning through a dynamic blend of lectures and hands-on demos. What You’ll Learn: • Core Concepts & Foundations: Gain a thorough grounding in machine learning fundamentals, including an overview of deep learning, the differences between ML and DL, and the key components that drive these technologies. Explore the nuances between rule-based and data-driven systems and understand how to define problems and collect data effectively. • Data Preparation & Model Building: Learn essential data preprocessing techniques such as normalization, standardization, and feature engineering. Dive into practical demos using platforms like Kaggle and Dataiku to see real-world applications—from model building and training to evaluation techniques including confusion matrices, ROC curves, and more. • No-Code Tools & Deployment: Discover the transformative power of no-code machine learning tools. Understand how to build, test, deploy, and monitor models seamlessly without traditional programming. Explore advanced topics such as model fairness and learn to generate comprehensive model fairness reports. Who Should Enroll: • Aspiring Machine Learning Enthusiasts: If you’re new to machine learning and want a clear, accessible introduction without the coding barrier, this course is for you. • Data Analysts & Professionals: Enhance your skill set by learning to implement and deploy machine learning solutions quickly using no-code platforms. • Business Leaders & Innovators: Gain insights into leveraging AI to drive better decision-making and innovation within your organization. By the end of this course, you’ll be equipped with the knowledge and practical skills to create robust machine learning models using intuitive, no-code platforms. Whether you’re aiming to upskill in your current role or pivot into the rapidly growing field of AI, this course will empower you to transform data challenges into strategic opportunities. Enroll now and take your first step toward mastering the future of technology—all without writing a single line of code!
Build an AI-powered Translation App with OpenAI
The AI Translation App is a guided project aimed at building a smart, interactive application that helps users translate text between different languages. Using a simple and user-friendly interface, users can easily input text and choose the target language for translation. The AI-powered app will integrate with a translation API to: - Provide accurate translations into multiple languages 🌍 - Allow users to switch between languages instantly 🔄 - Display real-time translation results ⚡ - Handle and display translation errors or unsupported languages 🚫 By working on this project, you'll gain practical experience in API integration and asynchronous JavaScript, while building an app that makes language translation simple and intuitive for users — perfect for showcasing in your portfolio!
Salesforce Real-Time Project: Service Cloud and Agentforce
This course is a hands-on, real-time Salesforce project where we build Service Craft, a complete service experience powered by Service Cloud, Experience Cloud, and Agentforce. Throughout this project-based learning journey, you’ll gain practical experience designing, configuring, and implementing Salesforce solutions exactly as you would in a real-world enterprise environment. You’ll start by understanding how to structure support processes, including Case Assignment Rules, Support Processes, and Omni-Channel Routing, ensuring cases are efficiently directed to the right agents. You’ll then build a fully functional Experience Cloud Site, complete with custom Lightning Web Components (LWCs), enabling customers to create, track, and manage their cases in a user-friendly interface. The course also guides you through enabling live chat and messaging, allowing seamless communication between customers and both Agentforce Service Agents and human agents. You’ll configure Email-to-Case, Entitlements, Knowledge Base, and Slack integration, creating a fully connected support ecosystem. With Agentforce AI capabilities, you’ll explore how to enhance routing, automate routine service tasks, and boost agent productivity, giving your service teams the edge in efficiency and customer satisfaction. By the end of this course, you’ll have built a real-time, end-to-end Salesforce project, demonstrating the full lifecycle of modern, AI-powered customer service operations. You’ll also gain the confidence to implement similar solutions in your organization, bridging the gap between theory and practical application. This course ensures you not only understand Salesforce features but can also apply them strategically to solve real-world business challenges.
Algorithmic Thinking (Part 2)
Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems. In part 2 of this course, we will study advanced algorithmic techniques such as divide-and-conquer and dynamic programming. As the central part of the course, students will implement several algorithms in Python that incorporate these techniques and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms. Once students have completed this class, they will have both the mathematical and programming skills to analyze, design, and program solutions to a wide range of computational problems. While this class will use Python as its vehicle of choice to practice Algorithmic Thinking, the concepts that you will learn in this class transcend any particular programming language.