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Generative AI Bootcamp: LLM Engineering, RAG & AI Agents
Highest Rated
Rating: 4.7 out of 5(265 ratings)
14,337 students

Generative AI Bootcamp: LLM Engineering, RAG & AI Agents

LLM Engineering, RAG & Agents. Build Apps with Llama 3.2, OpenAI, QLoRA & Fine-Tuning. Become an Generative AI Engineer.
Last updated 5/2026
English

What you'll learn

  • Build and Deploy 8 Production-Ready LLM Apps ranging from intelligent web scrapers to autonomous multi-agent systems.
  • Master Advanced RAG Architecture including Query Expansion, Semantic Re-ranking, and GraphRAG for enterprise-grade accuracy.
  • Fine-Tune Open Source Models using QLoRA and SFT to outperform frontier models like GPT-4o on specialized tasks.
  • Architect Autonomous AI Agents that can reason, plan, and use external tools to execute complex multi-step workflows.
  • Optimize LLM Performance by porting Python to C++ for up to a 60,000x speedup in execution.
  • Master the OpenAI & Llama 3.1 Stack using the latest 2026 API features, Tool Calling, and Structured Outputs.
  • Implement Serverless AI Deployment on Modal, allowing you to run heavy LLM workloads in the cloud with zero infrastructure overhead.
  • Evaluate AI Systems Like a Pro using "LLM-as-a-Judge" metrics, RAGAS, and custom evaluation benchmarks.
  • Bridge the Gap to AI Engineer by mastering Transformers, Tokenization, and Context Window management.
  • Create Voice-to-Action Tools using Whisper and Open-Source models to automate meeting minutes and corporate tasks.

Coding Exercises

This course includes our updated coding exercises so you can practice your skills as you learn.

See a demo
Image of coding exercise example

Course content

24 sections128 lectures30h 19m total length
  • Becoming a Generative AI Engineer: What This Course Is Really About7:25
  • Course Chat with Students and Tech Community0:22
  • Code Location: Hands-On Setup0:07

Requirements

  • Familiarity with Python programming language, including basic syntax, data structures, and functions.
  • Basic understanding of software development concepts
  • A computer with internet access (Windows, macOS, or Linux)
  • Willingness to learn and experiment (curiosity matters more than prior AI experience)

Description

Stop being an AI User. Start being an AI Engineer.

In 2026, the gap between those who "prompt" and those who "build" is widening. Companies aren’t looking for people who can talk to AI; they are hiring LLM Engineers who can architect, fine-tune, and deploy autonomous systems that solve multi-million dollar problems.

Welcome to the AI Engineer Bootcamp—the most comprehensive, project-driven track on Udemy. This isn’t a collection of theory slides. It is a 33.5-hour technical deep dive designed to take you from a Python developer to a specialized AI Architect in 8 weeks.

Why This Course is Different

While other courses stay at the surface level using basic APIs, we go under the hood. You will master QLoRA for efficient fine-tuning, build Agentic RAG pipelines that actually scale, and orchestrate Multi-Agent Systems that work autonomously.

The 8-Week / 8-Project Portfolio

You won't just learn; you will build. By the end of this course, you will have a professional GitHub portfolio featuring:

  1. Smart Scraper: An AI brochure generator that navigates websites intelligently.

  2. Multi-Modal Support Agent: A functional airline assistant with UI and tool-calling.

  3. Meeting Intelligence: Convert audio to action items using Whisper & Llama 3.2.

  4. The Performance Booster: An AI that optimizes Python code into C++ (60,000x speedup).

  5. Enterprise Knowledge Worker: A production-grade RAG system for company data.

  6. Capstone (Part A-C): Build a "Price Prediction" engine, fine-tune an Open Source model to beat GPT-4o, and deploy an autonomous Deal-Scanner Agent System.

What You Will Master

  • LLM Engineering: Understand Transformers, Tokenization, and Context Windows.

  • Advanced RAG: Move beyond simple embeddings to Query Expansion, Re-ranking, and GraphRAG.

  • Fine-Tuning (QLoRA): Learn to train Llama 3.2 on Google Colab GPUs to outperform frontier models.

  • Agentic AI: Orchestrate planning agents and multi-tool workflows (LangChain & CrewAI).

  • Deployment: Ship your apps to the cloud using Modal and Serverless AI architecture.

Who Is This For?

  • Software Engineers: Ready to pivot into the highest-paying role in tech.

  • Data Scientists: Who want to move from training models to building full AI products.

  • Tech Enthusiasts: Who have the Python basics and want to reach the "Frontier" of Generative AI.

The AI Revolution is here, and the "AI Engineer" is the most in-demand role of the decade. Are you ready to build the future?

Enroll now and start your 8-week journey to mastery.

Who this course is for:

  • Software Developers and Backend Engineers who want to transition into AI Engineer or LLM Engineer roles
  • Python developers looking to build production-ready Generative AI applications
  • Data Scientists and ML Engineers who want to master modern LLM engineering, RAG, and agentic AI
  • Engineers and technical professionals who want a deep, hands-on understanding of how LLM systems work
  • Startup founders and product builders building AI-powered products or platforms
  • Developers preparing for AI Engineer interviews or real-world AI system design roles