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Download Advance RAG : Vector to Graph RAG Neo4j Adaptive AutoGen RAG Course for Free

Download the complete Advance RAG : Vector to Graph RAG Neo4j Adaptive AutoGen RAG video course for free with high-definition MP4 video lectures, project exercise archives, and step-by-step masterclasses. Learn offline at your own pace with zero paywalls or recurring subscriptions.

21Lectures

12Total Hours

1699.1MB Total Size

MP4 / 1080p HD

Instructor: Udemy

English

beginner to advanced

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All Video Lectures Available to Download21 Videos

Direct high-speed MP4 downloads for every chapter.

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What is RAG RAG Process

MP4 HD12m•25.69 MB

Stream

Generative AI without RAG. Why RAG

MP4 HD11m•24.61 MB

Stream

Introduction to course

MP4 HD33m•73.36 MB

Stream

Tokenization, Stemming and Lemmatization

MP4 HD10m•22.43 MB

Stream

What is NLP

MP4 HD8m•16.58 MB

Stream

Evaluation of NLP

MP4 HD14m•30.57 MB

Stream

POS , NER , Chunking, BoW, TF-IDF and Embedding

MP4 HD30m•65.17 MB

Stream

Transformer Model

MP4 HD38m•82.72 MB

Stream

Create simple streamlit chatbot

MP4 HD20m•43.07 MB

Stream

Setup VS code , Python, Neo4j, Streamlit, PIP packages

MP4 HD1h 8m•149.97 MB

Stream

What is vector RAG

MP4 HD11m•23.96 MB

Stream

Develop vector RAG with Groq API and Langchain

MP4 HD53m•116.90 MB

Stream

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What You'll Master in this Free Download Course

Basics of RAG (Retrieval Augmented Generation) and NLP: Understanding the core concepts to build a strong foundation of NLP and RAG.

Understanding of NLP process like markup, embedding, POS, TF-IDF, segmentation etc.

Understanding the evaluation of NLP models from the rule-based model to the transformer model.

Understanding the transformer model with a simple RAG example.

Setting up the environment for the practical implementation of the RAG program using Python and VS Code

Learn to build a vector based RAG application with Streamlit chatbot, langchain and vectordb.

Learn advanced RAG technique with Graph RAG, LLM and Streamlit chatbot. Learn how to configure Neo4j, create Graph RAG, display graph in your chatbot.

Advanced RAG learning with hybrid search technique using Graph RAG. Self-reflexive RAG learning with Langgraph. Practical use cases with RAG Python code.

RAG re-ranking with cohere API to improve RAG retrieval process.

Practical uses in RAG.

Tests to check learning.

Building an agent-based RAG program with Autogen. Agent-oriented RAG.

About this Free Download Course

Advance RAG course: Vector to Graph RAG Neo4j Adaptive AutoGen RAG. In this course, you will learn how to master Retrieval Augmented Generation (RAG), an advanced artificial intelligence technique that combines retrieval-based methods with generative models. This course is designed for developers, data scientists, AI enthusiasts, quality engineers, students who want to build practical applications using RAG, from a simple chatbot based on vector RAG to advanced chatbot with Graph RAG and self-reflective RAG. You will explore the theoretical principles, practical implementation and real-world use cases of RAG. At the end of this course, you will have the skills to create RAG-based AI applications.

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Yes! If this course includes downloadable source code, exercise assets, or templates, they are available in the "Course Exercise Files & Project Archives" section as standard ZIP files for free download.

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