The Complete AI & GenAI Engineer Bootcamp 2026: Zero to Hero

Descripción

Become a Modern AI Engineer & Build Real-World AI Systems (GenAI + LLMs + Agents) Unlock the power of Artificial Intelligence and Generative AI by learning how to build real-world, production-ready AI systems used in today’s industry. The Problem AI Engineers are in extremely high demand, but most learners struggle to break into this field because: * AI is taught in disconnected topics (ML, DL, NLP, LLMs separately) * Many courses focus only on theory or basic tools like ChatGPT * There is no clear roadmap from beginner to advanced * Building real-world AI applications feels overwhelming Even after learning concepts, connecting everything into real systems is where most people get stuck. The Solution This course is designed as a complete, structured AI Engineer Bootcamp. Instead of teaching isolated topics, this course takes you step-by-step through a clear roadmap: Python → Machine Learning → Deep Learning → NLP → LLMs → RAG → AI Agents → Real Projects You won’t just learn AI — you will build real AI systems. What You Will Learn Foundations of AI & Python * Python for AI (NumPy, Pandas, Data Visualization) * Data analysis and EDA (Exploratory Data Analysis) * Core AI concepts and real-world applications Machine Learning (Core) * Regression, classification, clustering * Model evaluation (accuracy, precision, recall) * Overfitting vs underfitting Projects: * House Price Prediction * Spam Email Classification * Customer Segmentation Deep Learning * Neural networks and backpropagation * CNNs for image data * RNNs and LSTMs for sequences * Introduction to Transformers Natural Language Processing (NLP) * Text preprocessing * TF-IDF vs embeddings * Word embeddings and BERT Project: * Sentiment Analysis System Generative AI & LLMs * Understanding Large Language Models (LLMs) * Tokens and context windows * GPT, Claude, LLaMA differences * Open vs closed models Transformers & Hugging Face * Self-attention and transformer architecture * Encoder vs decoder * Using Hugging Face models and tokenizers Prompt Engineering * Zero-shot and few-shot prompting * Chain-of-thought reasoning * Prompt templates Build Real AI Systems Retrieval Augmented Generation (RAG) * Chunking strategies * Embeddings and similarity search * Retrieval + generation pipelines Project: * PDF Question Answering System AI Agents (LangChain & LangGraph) * Tools, memory, and planning * Single-agent and multi-agent workflows Project: * AI Research Agent Bonus Topics * Fine-tuning LLMs (LoRA, PEFT) * Computer Vision basics * Diffusion Models (Stable Diffusion) * Build UI apps using Streamlit and Gradio Hands-On Projects This is a project-based course where you will build: * EDA Notebook * Machine Learning models * NLP systems * CNN image classifier * RAG-based AI assistant * LLM chatbot * AI agent system Who This Course Is For * Developers who want to become AI Engineers * DevOps / Cloud engineers moving into AI * Students looking for a structured roadmap * Anyone interested in Generative AI and LLMs * Professionals who want hands-on AI skills By the End of This Course You will be able to: * Build end-to-end AI applications * Work with LLMs and modern AI tools * Create AI agents and automation systems * Design real-world AI solutions * Apply for roles like AI Engineer, GenAI Engineer, and ML Engineer What You Get * Complete AI Engineer Bootcamp * Hands-on real-world projects * Lifetime access and future updates * Certificate of completion Final Note AI is not the future — it’s already here. The real question is: Will you just use AI tools… or build them? Start your journey today and become a job-ready AI Engineer.

Lo que aprenderás

• Build Machine Learning models from scratch using Python, NumPy, Pandas, and Scikit-Learn for real-world tasks like prediction, classification, and clustering.
• Understand Deep Learning and Neural Networks with TensorFlow and Keras, including CNNs for image data and RNN/LSTM for sequence data.
• Learn Natural Language Processing (NLP) including text preprocessing, embeddings, and transformer models like BERT.
• Work with modern Generative AI tools such as Hugging Face, Transformers, and advanced prompt engineering techniques.
• Build real-world GenAI applications including RAG systems, LLM chatbots, and AI agents using LangChain and LangGraph.
• Create portfolio-ready AI projects with interactive interfaces using Streamlit and Gradio.

Requisitos

• Basic knowledge of Python is helpful but not mandatory.
• No prior experience is required. We'll start from the very basics.