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Complete Gen AI: Basic to Agent AI, RAG, Bedrock, Vertex AI
Rating: 4.1 out of 5(48 ratings)
394 students

Complete Gen AI: Basic to Agent AI, RAG, Bedrock, Vertex AI

Complete guide Gen AI with fundamentals of NLP, LangChain, LCEL, LangSmith, Agentic AI, RAG, Neo4J, Bedrock, Vertex AI
Created bySoumen Kumar Mondal
Last updated 8/2025
English

What you'll learn

  • Master the fundamentals of NLP: Tokenization, embedding, POS tagging, TF-IDF, chunking, and more.
  • Understand the fundamentals of Generative AI: Explore key concepts like autoencoders, VAEs, GANs, and Transformer models
  • Master Prompt Engineering: Learn techniques to design effective prompts for models like ChatGPT, including zero-shot, one-shot, and few-shot prompting.
  • Work with industry-leading tools: Explore cutting-edge Generative AI platforms like ChatGPT, Google Gemini, and Microsoft CoPilot for real-world applications.
  • Set up the environment for hands-on Generative AI applications: Implement RAG using Python, VS Code, and LangChain.
  • Work with LangChain and LangChain Ecosystem Libraries (LCEL): Build real-world Generative AI applications and explore the LangChain ecosystem.
  • Develop AI Agents: Understand and implement agents like Crew AI and AutoGen to automate complex tasks.
  • Implement Vector RAG and Graph RAG: Use Neo4j for advanced retrieval and data augmentation techniques.
  • Learn Self-Reflective RAG techniques: Understand how AI can reason and reflect on its own processes.
  • Practical Python skills for Generative AI: Start from the basics and progress to advanced AI development with Python and libraries like NLTK.
  • Build AI solutions from the ground up: Gain end-to-end knowledge of Generative AI, from basics to advanced implementations with LangChain and LCEL.
  • Generative AI with AWS Bedrock
  • Generative AI with Google Cloud Vertex AI
  • Hands on use case implementation with AWS Bedrock BOTO3
  • Google Cloud Vertex AI use case impelementation

Course content

24 sections • 99 lectures • 14h 48m total length

  • Introduction7:23

    This comprehensive Generative AI Course covers a range of essential topics, from the Fundamentals of NLP and Generative AI to Python basics for beginners. You'll get hands-on experience with LangChain, LangSmith, and LangGraph, building real-world AI solutions. The course delves into advanced concepts like Agents (Crew AI, AutoGen) and Retrieval-Augmented Generation (RAG), including Vector RAG and Graph RAG with Neo4j, and explores Self-Reflective RAG. Interactive quizzes reinforce learning and provide a practical approach to mastering these cutting-edge AI technologies.

Requirements

  • Basic understanding of Python but dont worry the course will cover fundamental of Python.

Description

Unlock the full potential of Generative AI in this comprehensive, hands-on course tailored for students, developers, and AI enthusiasts. Whether you're a beginner or looking to deepen your expertise, this course offers an immersive experience, starting with the Fundamentals of Natural Language Processing (NLP) and Generative AI, giving you the foundational knowledge needed to excel. You will learn the basics of Python, ensuring even those new to programming can participate fully. From there, we dive into advanced LangChain implementations, where you'll build real-world applications. You'll also gain practical experience with LangSmith and LangGraph, key tools in the AI ecosystem.

Explore the power of AI Agents, including Crew AI and AutoGen, and see how these autonomous systems can transform tasks like customer service, automation, and more. The course also covers cutting-edge Retrieval-Augmented Generation (RAG) techniques, including Vector RAG and Graph RAG using Neo4j for enhanced search and data retrieval. A special focus on Self-Reflective RAG will introduce you to the next frontier of AI-driven reasoning.

With quizzes, practical coding challenges, and hands-on projects, this course ensures you gain both theoretical understanding and practical experience in the most important areas of Generative AI. Get ready to build AI solutions from the ground up!

Who this course is for:

  • Data Scientists
  • Machine Learning Engineers
  • AI and NLP Enthusiasts
  • Developers and Software Engineers
  • Researchers and Academics
  • Product Managers and Technical Leads
  • Students and Learners
  • AI Practitioners and Consultants
  • Quality Engineers

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