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RAG : Concept & Hands-on Vector RAG, Graph RAG, Self-Reflective RAG. RAG with Streamlit LangChain, LangGraph, Neo4J
What you will learn
Fundamentals of RAG (Retrieval-Augmented Generation) and NLP: Understand core concepts to build strong foundation of NLP and RAG.
Understand process of NLP like tokenization, embedding, POS, TF-IDF, chunking etc.
Understand evaluation of NLP models from Rule based to Transformer model.
Understand transformer model with simple RAG example.
Environment setup for hands on implementation of RAG application using Python and VS Code
Learn to build vector based RAG application with Streamlit chatbot, langchain and vectordb.
Learn advance RAG technique with Graph RAG , LLM and Streamlit chatbot. Learn how to setup Neo4j, create Graph RAG , show graph in your chatbot.
Learn advance RAG with hybrid search technique using Graph RAG. Learn self reflective RAG with Langgraph. Practical use cases with python code of RAG.
Re ranking RAG with cohere API to improve retrieval process of RAG.
Practical use cases on RAG.
Quizzes to check learning.
Why take this course?
In this course, you will learn how to master Retrieval-Augmented Generation (RAG), a cutting-edge AI technique that combines retrieval-based methods with generative models. This course is designed for developers, data scientists, and AI enthusiasts, quality engineers, Students who want to build practical applications using RAG, ranging from simple vector RAG chatbot to advanced chatbot with Graph RAG and Self Reflective RAG. You’ll explore the theoretical foundations, practical implementations, and real-world use cases of RAG. By the end of this course, you will have the skills to create RAG-based AI applications.
After completing the course, you will be able to create chatbot with multiple RAG techniques using Streamlit, LangChain, LangGraph, Groq API and many more. Along with that you will also learn fundamentals and concepts.
We are thrilled to unveil this latest course Advanced RAG : Vector to Graph RAG LangChain Neo4j AutoGen which is designed to unlock your full potential and propel you towards success. 
Whether you are an aspiring professional seeking to upskill or an enthusiast eager to explore a new passion, this course Advanced RAG : Vector to Graph RAG LangChain Neo4j AutoGen is tailor-made to cater to your unique learning journey. Enroll this course Advanced RAG : Vector to Graph RAG LangChain Neo4j AutoGen to embark on an exciting educational adventure that will redefine your capabilities and broaden your horizons. Get ready to dive into a world of knowledge, innovation, and growth! Explore our website daily to access a diverse range of free courses covering high-demand fields such as Cloud Computing, Data Analytics, and Cybersecurity. Dive into Trading insights and Real Estate investment strategies, or discover the nuances of Property management. Elevate your career with Online MBA Programs and College degrees. Explore various financial subjects like Health Insurance, Life Insurance, Credit Card tips, and Legal attorney courses. Our Health and Medical offerings cover Dentistry, Surgery, and beyond. Begin your Journey with travel-focused courses for Flight and Hotel booking know-how. Enhance your Home Improvement skills with our specialized offerings. Our platform presents learning opportunities across multiple disciplines, providing the latest insights in various industries. As you stay informed, your personal and professional growth thrives. Dive into Finance with courses on Personal Loans, Retirement Plans, Mutual Funds, and Financial Planning. Uncover insights into Health Insurance, Weight Loss Surgery, Dental Implants, Addiction or Cancer Treatment. Whether you are interested in trading or need guidance on Car or Motorcycle Insurance, our courses empower your knowledge journey.Course Objectives
- Understand the fundamental concepts of RAG and NLP.
- Understand concepts of NLP with examples like tokenization, chunking, TF-IDF, embedding.
- Understand evaluation of NLP models from rule based to transformer model.
- Understand transformer model and components with examples.
- Environment setup for hands on implementation.
- Build first chatbot with Streamlit and Langchain.
- Build a vector RAG with Streamlit chatbot with Groq API.
- Understand Graph RAG and implement Graph RAG with Neo4j.
- Understand Self Reflective or Adaptive RAG and implement with LangGraph.
- Real world use cases of RAG.
- Check your understanding with Quizzes.
Lets deep dive into world of RAG to understand it.
