Complete Generative AI Bootcamp 2026: LangChain, Agents, RAG

Name: Complete Generative AI Bootcamp 2026: LangChain, Agents, RAG
Rating: 4.4 (14 reviews)

Build production-ready AI Agents with LangChain, Ollama, MCP, Google ADK, Hugging Face, and Agentic RAG from scratch.

Created byVGI Skill Lab, Aryan Agrahari

Last updated 5/2026

English

What you'll learn

Build real-world AI Agents from scratch using LangChain and the Golden Rules Framework
Deploy production-ready AI systems using Google Agent Development Kit (ADK)
Run open-source LLMs locally on your machine using Ollama without any API costs
Design and implement an Agentic RAG system powered by Vertex AI Search
Integrate Model Context Protocol (MCP) into multi-agent AI pipelines
Access models, datasets and APIs through Hugging Face for real AI projects

Course content

12 sections • 44 lectures • 7h 39m total length

Welcome message2:43
Follow Rohan's real world ai journey as the course teaches generative ai basics, llms, LangChain, agents, tools, memory, and production level ai agents.

The Ultimate 2026 Generative AI Roadmap: LLMs, Agents and RAG14:47
Hugging Face: A Guide to Models, Datasets and API Access6:56
The Ultimate Framework for Building Generative AI Applications24:33
Explore the LangChain framework by building LLM workflows with chaining, tools, and LCEL, guided by scenario-based learning, and prepare to set up a Python-driven AI assistant using API keys.
Course Materials0:01

The 6 Golden Rules of Building Generative AI Agents Steps 1 and 26:56
Define the problem, choose LangChain as the framework, select models, configure the LLM, write prompts, assemble the chain, tools, and memory to create your AI agent.
Generative AI Development Selecting and Configuring LLMs Steps 3 and 411:34
Testing Large Language Models Comparing OpenAIs GPT and DeepSeek by Hugging Face2:55
Master Prompt Engineering LangChain Golden Rule Step 59:29
Develop the prompt template in LangChain's golden rule step 5 to endow the AI with a personality. Create and load prompt templates for OpenAI and HuggingFace models using LangChain.
Materials0:01
AI Agents and Golden Rules Framework Quiz

Building Your First LLM Chain LangChain Patterns and Simple Q&A13:04
Generative AI Step 6 Level Up Your LLM with Intelligence and Tool Calling13:08
In this step 6 lecture, extend a simple chain with LangChain tools and an LLM, enabling tool calling for rating, food information, and opening hours, and introducing a React agent.
Beyond Simple Tooling Implementing ReAct Agents for Multi Step AI Reasoning10:24
Materials0:01
LLM Chains and Tool Calling Quiz

Mastering LangChain Building Pipelines with LCEL Step 76:01
Build LangChain pipelines with LCEL by initializing LLMs, defining prompts, and composing a pipeline with the pipe operator, including Hindi prompts and parsing to Hindi outputs.
Mastering Generative AI Adding Memory to Autonomous Agents Step 87:50
Building a Complete Food Agent with LangChain Memory Tools and Chaining25:22
Build a complete food agent using LangChain memory tools and chaining to answer food queries, recipes, nutrition, and restaurant information with memory across sessions.
Building AI Agents with Hugging Face and LangChain A Complete Step by Step Guide28:08
Materials0:01
Advanced LangChain and Pipelines Quiz

Why Run LLMs Locally and How Ollama Works7:42
Installing Ollama and Running Your First Local Model17:43
Install ollama on mac, windows, or linux and access a library of models. Download and run a local model (llama 3.1) offline via pull, list, run, ps, stop, and rm.
Connecting Ollama with LangChain for Local AI Apps10:50
Learn to run local AI apps with LangChain and Ollama by configuring Ollama models, writing prompts, and building tools, agents, and memory for offline, fully local conversations.
Materials0:01
Running Local LLMs with Ollama Quiz

Requirements

Basic Python knowledge like variables, functions and loops is enough to get started
A laptop or desktop with internet connection, Windows Mac or Linux all work fine

Description

Are you ready to go beyond ChatGPT prompts and actually BUILD Generative AI systems that work in the real world?

This is the most up-to-date, hands-on Generative AI course of 2026 — covering everything from LLM fundamentals to deploying production-grade AI Agents using Google ADK, LangChain, Ollama, and Agentic RAG.

Whether you're a developer, engineer, or tech enthusiast, this course gives you a complete roadmap to build, deploy, and scale AI Agent systems — the same skills top companies are hiring for right now.

What makes this course different from others out there is simple. It is built around the actual 2026 AI stack, not outdated tutorials from two years ago. It covers Model Context Protocol which is the new standard for connecting agents to tools and data. You will work with real projects using Google ADK and Vertex AI Search. You will also run LLMs on your own machine using Ollama so there are no API costs involved.

By the end of this course you will have built a complete Agentic RAG system and a portfolio project you can show to any employer or client. Every section is hands on and every concept is applied to something real.

This is not a theory course. You will write code, build agents, connect tools and deploy systems from the very first section.

Who this course is for:

Anyone who wants hands-on experience with the actual 2026 AI tools companies use today.

Complete Generative AI Bootcamp 2026: LangChain, Agents, RAG

What you'll learn

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Course content

Introduction to course1 lecture • 3min

Introduction to Generative AI4 lectures • 46min

Foundations and Setup3 lectures • 17min

Building AI Agents with the Golden Rules Framework5 lectures • 31min

LLM Chains and Tooling4 lectures • 37min

Advanced LangChain and Pipelines5 lectures • 1hr 7min

Running Models Locally with Ollama4 lectures • 36min

Introduction to Model Context Protocol (MCP)3 lectures • 38min

Building Production-Ready AI Agents with Google ADK3 lectures • 37min

Building Multi-Agent system using Google ADK3 lectures • 36min

Requirements

Description

Who this course is for: