The Complete AI & GenAI Engineer Bootcamp 2026: Zero to Hero (Udemy.com)
Machine Learning, Deep Learning, NLP, LLMs, RAG, AI Agents, Hugging Face, LangChain, LangGraph, Build Real AI Projects
Created by: AI University
Last updated May 2026
What you will learn
- 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.
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.2 out of 5higher than 13% of them
- Reviews63#1,074 of 1,183 by number of reviews
- Length48.7 hourslonger than 97% of them
- Last updatedMay 2026more recently than 73% of them
Course Description
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.
Instructor Details
- 4.2 Rating
63 Reviews
AI University
AI University is a dedicated education initiative built around one goal: making Artificial Intelligence genuinely usable in everyday life, work, and engineering practice. Founded by an AI professional with hands-on industry and applied research experience across Generative AI, Prompt Engineering, Machine Learning, and real-world AI systems - bridging the gap between AI theory and practical application.
We specialize in a comprehensive range of AI and data-driven disciplines, including:
1. AI for Everyday Life & Work – Practical use of ChatGPT, Claude, Gemini, and other leading AI tools for real tasks: writing, summarizing, research, brainstorming, and daily productivity, no coding required
2. Prompt Engineering & Applied AI – In-depth training on designing, evaluating, and optimizing prompts for accuracy, reliability, and scalability across real-world use cases
3. Generative AI & Modern Tools – Working with text, image, and multimodal AI systems using industry-standard platforms and workflows
4. AI Engineering & Data Science – Python, Machine Learning, Deep Learning, NLP, LLMs, RAG, AI Agents, and engineering-grade practices used to build and deploy production-ready AI systems
All of our courses are:
- Hands-on and project-based
- Grounded in real industry practice, not just theory
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Reviews
By Morishetti Raghu on 9/12/2026
good the way she teach
By Sachin Ramshetty on 9/11/2026
Excellent course with a clear learning path for Python and ML to LLMs, RAG and AI Agents. Very practical and easy to follow.
By Madhumitha R on 8/31/2026
Good course for beginners as well, but it needs more practical explanations in a step-by-step approach. It is like simply typing the code and repeating it. Most of the content is repeated.
By Soumya67 on 8/5/2026
It looks like the instructor is reading from a prompt. The tone is monotonous, which is keeping me from focusing. Also, there is a problem with the video.
By Nagaraju Korada on 6/25/2026
content so far is good. looks like they are reading a text instead of explaining and suddenly pausing in between. other than those, content so far is and informative
By YAHYA AHMED AMIN on 6/20/2026
English language not clear
By Malvika Raj on 4/19/2026
The course is very project-focused, which helped me understand how things work in real-world scenarios instead of just theory. Building things like chatbots, NLP systems, and AI agents gave me confidence that I can actually apply these skills. If you’re serious about becoming an AI/GenAI engineer and want a practical, end-to-end learning path, this course is definitely worth it. It’s not just about learning AI — it’s about building real AI systems.
By Sam Carl on 4/2/2026
Great course for anyone starting or switching into AI/ML/GenAI. The best part is the focus on real-world projects like chatbots and AI applications, not just theory. Concepts are explained clearly and are easy to follow even for beginners.
By Nikhil H R on 3/31/2026
Very well-structured AI course. Easy to understand and hands-on learning made it even better. Good for starting ML & GenAI. Highly recommended.
Quality Score
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Overall Score : 84 / 100






