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LifestyleComplete Generative AI Course: Foundations, Agentic AI & RAG (Udemy.com)
Master LLMs, RAG, LangChain, Agentic AI, Fine Tuning, MCP, Prompt Engineering | Create Gen AI Chatbot | Create real apps
Created by: Kaushik Annambhotla
Last updated September 2026
What you will learn
- Master the basics of Machine Learning, Neural Networks, Generative AI, Python
- Connect with LLMs using LangChain APIs
- Learn the complete RAG pipeline, including data ingestion and retrieval processes and working with Vector Databases
- Build agentic workflows using OpenAI Agent Builder and n8n
- Explore ReAct Agents, Crew AI, and the Model Context Protocol (MCP)
- Go beyond text with Speech-To-Text (STT) and Text-To-Speech (TTS) models
- Create and deploy apps using GitHub, Streamlit, Supabase and Vercel V0
- Experience "Vibe Coding" with Claude and Cursor IDE
- Explore model customization, LLM Fine-tuning, and advanced architectures like GANs, VAEs, and Diffusion
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating5.0 out of 5higher than 100% of them
- Reviews62#1,077 of 1,183 by number of reviews
- Length5.9 hourslonger than 52% of them
- Last updatedSeptember 2026more recently than 94% of them
Course Description
Welcome to the Complete Generative AI Bootcamp, where you will learn how to build real-world AI applications using the latest tools, frameworks, and workflows used in the industry today.
This course is designed for beginners, students, developers, product managers, and working professionals who want to gain practical Generative AI skills and stay ahead in the AI era. You do not need prior AI experience to get started. We cover the fundamentals step by step while focusing heavily on hands-on implementation.
Throughout the course, you will learn how Large Language Models (LLMs) work, how to write effective prompts, and how to build AI-powered applications using Python and modern AI frameworks.
You will learn:
Fundamentals of Generative AI and LLMs
Prompt Engineering techniques
Tokens, embeddings, transformers, and attention mechanisms
Building AI apps using OpenAI APIs and LangChain
Creating and deploying apps using Cursor, Streamlit, Supabase, Vercel, GitHub
Retrieval-Augmented Generation (RAG) systems
Vector Databases and semantic search
AI Agents and tool calling
Fine-tuning an LLM
Real-world AI workflows and automation
Create a personal portfolio of AI apps
This course is highly practical and project-driven. Instead of only learning theory, you will build multiple AI applications that strengthen your understanding and help you create a strong portfolio for internships, jobs, and freelance opportunities.
By the end of this course, you will be able to confidently build, understand, and deploy modern AI applications using industry-relevant tools and workflows.
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Instructor Details
- 5.0 Rating
62 Reviews
Kaushik Annambhotla
With about 11 years of experience in product management, I have a passion for solving user problems with technology and delivering innovative solutions. I am currently working as a Lead AI Product Manager. I am also a passionate builder using AI. I feel learning AI in 2026 is like learning computer skills 20 years back.
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Reviews
By Mavis Woltz on 8/19/2026
I really appreciated the debugging tips when working with LangChain. It can be a finicky framework, and the course provided great strategies for tracking down issues in complex Agent chains.
By Jenny Rippy on 8/19/2026
Very comprehensive. You could easily split this into three different courses (Prompt Engineering, RAG/Langchain, and Agents/Fine-Tuning), but getting it all in one cohesive curriculum is amazing.
By Emily Starr on 8/19/2026
The pacing is fantastic. The instructor doesn't rush through the complex parts of building agents, but also doesn't waste time on python basics. It hits the sweet spot for intermediate developers.
By Audrey Lucero on 8/18/2026
Excellent breakdown of MCP! There isn't a lot of structured material out there on this topic yet, so having it included alongside standard LLM and RAG concepts makes this a very complete package.
By Thomas Wilcox on 8/18/2026
I've recommended this to my entire dev team. The sections on MCP and Agentic AI gave us so many ideas for internal tools. The instructor's voice is also very engaging, which helps for a long course
By Bella Avila on 8/18/2026
The prompt engineering section isn't just basic "how to write a good sentence" stuff—it gets into systemic prompting and controlling LLM outputs for apps. Really valuable insights that I'm already using.
By Isaiah Cordova on 8/18/2026
As a product manager, I took this to understand what my engineering team is actually doing. Even though some of the coding was advanced for me, the architectural overviews of LangChain and Fine Tuning were incredibly illuminating.
By Andrew Mosley on 8/17/2026
Finally, a course that focuses on creating real apps! The theoretical aspect is kept brief and you spend most of your time actually coding. i recommend it to anyone who learns best by doing.
By Brooklyn Novak on 8/17/2026
Outstanding course. I was specifically looking for content on Fine Tuning and MCP, and it did not disappoint. The code snippets are clean, modern, and actually work without needing a ton of debugging.
By Lucy Winters on 8/17/2026
As a traditional software engineer, the AI landscape felt overwhelming. This course structures everything perfectly. Starting from Prompt Engineering and ramping up to LangChain and RAG made the learning curve feel completely manageable.
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 100 / 100
- Video Duration:
5.9h - Price: $10.99
- Provider: Udemy
- Updated:
September 2026 - Level:
All Levels - Language:
English - Certificate:
Yes
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