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Complete Generative AI Course: Agentic AI & Langchain
Rating: 4.1 out of 5(2 ratings)
12 students

Complete Generative AI Course: Agentic AI & Langchain

Master LLMs, RAG, LangChain, Agentic AI, Fine Tuning, MCP, Prompt Engineering | Create Gen AI Chatbot | Create real apps
Last updated 7/2026
English

What you'll 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

Course content

7 sections49 lectures5h 54m total length
  • Introduction to AI7:06
  • Supervised vs Unsupervised ML3:32
  • What are Neural Networks?3:26
  • Natural Language Processing (NLP) vs Generative AI2:58
  • What is meant by Attention Mechanism?6:35
  • Understanding the Generative AI ecosystem13:51
  • Basics of Python36:33
  • Working with LangChain APIs12:03
  • Prompt Engineering9:37
  • Different types of Instructions4:27
  • Practice Quiz

Requirements

  • No programming experience needed. We teach Python basics and provide code walkthroughs for building apps with LLM APIs. While much of this can be vibe coded, understanding how these integrations work helps you truly stand out.
  • A willingness to learn and grow beyond just vibe coding.

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.

Who this course is for:

  • Students aiming to kickstart a career in AI
  • Product Managers looking to stay relevant in the AI era
  • Working professionals planning to transition into AI roles
  • Developers who want to build practical Generative AI skills