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Премиум
  1. Урок 1. 00:08:12
    Course Outline
  2. Урок 2. 00:06:05
    Meet Rubber Ducky! Your AI Course Assistant using RAG
  3. Урок 3. 00:04:05
    Overview: Fundamentals of Retrieval Systems
  4. Урок 4. 00:05:38
    Overview of Information Retrieval
  5. Урок 5. 00:07:21
    What is Tokenization?
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    OpenAI Tokenizer
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    Libraries and Data Handling for RAG
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    Tokenization Techniques
  9. Урок 9. 00:09:36
    Preprocessing Steps
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    Types of Retrieval Systems
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    Vector Space Model (TF-IDF)
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    Implementing TF-IDF - Part 1
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    Implementing TF-IDF - Part 2
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    TF-IDF Function and Output Analysis
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    Boolean Retrieval Model
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    Preprocessing Steps - Part 2
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    Setting a Directory
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    Boolean Retrieval Implementation
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    Probabilistic Retrieval Model
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    Probabilistic Retrieval Model Setup
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    Probabilistic Retrieval Model
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    How Google Search Works
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    Key Concepts: Indexing, Querying, and Ranking
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    What Did You Learn in This Section?
  25. Урок 25. 00:11:53
    ReAct Prompt Engineering
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    Chain of Thought Prompt Engineering
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    Overview: Generative AI Fundamentals
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    Introduction to Text Generation
  29. Урок 29. 00:12:48
    Understanding Transformers
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    Rock-Paper-Scissors, Dices and Strawberries
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    Getting a Hugging Face Key
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    Langchain and Hugging Face Setup
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    Basic Text Generation
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    Attention Mechanisms
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    Understanding Generation Model Parameters
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    System Message and Parameters
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    Text Generation with System Message
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    Text Generation with Parameters
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    OpenAI Playground - top P
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    What Did You Learn in This Section?
  41. Урок 41. 00:14:26
    LLMs, Few-shot, Scaling and Factuality
  42. Урок 42. 00:02:39
    Overview: RAG Fundamentals
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    Introduction to RAG Architecture
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    Hugging Face Setup
  45. Урок 45. 00:09:03
    Tokenization and Embeddings for RAG
  46. Урок 46. 00:04:16
    FAISS Index: Efficient Similarity Search
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    Building a Retrieval System
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    Developing a Generative Model
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    Implementing the RAG System
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    What Did You Learn in this Section?
  51. Урок 51. 00:16:41
    LongRAG and LightRAG
  52. Урок 52. 00:03:48
    Overview: Working with the OpenAI API
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    OpenAI API for Text
  54. Урок 54. 00:05:50
    Setting Up OpenAI API Key
  55. Урок 55. 00:04:32
    OpenAI API Setup
  56. Урок 56. 00:07:03
    Generating Text with OpenAI API
  57. Урок 57. 00:10:21
    OpenAI API Parameters
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    OpenAI API for Images
  59. Урок 59. 00:04:55
    With Image URL
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    Converting Images to Base64
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    Assess My Python Course Thumbnail
  62. Урок 62. 00:03:51
    What Did You Learn in this Section?
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    Project Briefing: Customer Acquisition
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    OpenAI Setup
  65. Урок 65. 00:08:22
    AI Agent System Prompt
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    Processing Images for GenAI
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    Extract Data with GenAI
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    Improving GenAI Extraction
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    GenAI with all Images
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    PDF to Images
  71. Урок 71. 00:08:17
    Wrapping Up the OpenAI GenAI Project
  72. Урок 72. 00:04:35
    Overview: RAG with OpenAI GPT Models
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    Case Study Briefing: Cooking Books
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    Converting PDF to Images
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    Reading a Single Image with GPT
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    Enhancing AI with Prompt Engineering
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    Reading All Images in a Dataset
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    Filtering Non-relevant Information
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    Understanding Embeddings in NLP
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    Generating Embeddings
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    Building FAISS Index and Metadata Integration
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    Implementing a Robust Retrieval System
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    Combining Outputs for Enhanced Results
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    Constructing a Generative Model
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    Complete RAG System Implementation
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    How to Improve RAG Systems Effectively?
  87. Урок 87. 00:03:37
    Overview: Working With Unstructured Data
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    Introduction to Langchain Library
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    Excel Data: Best Practices for Data Handling
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    Python - Initial Setup for Data Processing
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    Loading Data and Implementing Chunking Strategies
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    Developing a Retrieval System for Unstructured Data
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    Building a Generation System for Dynamic Content
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    Building Retrieval and Generation Functions
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    Working with Word Documents
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    Setting Up Word Documents for RAG
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    Implementing RAG for Word Documents
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    Working with PowerPoint Presentations
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    PowerPoint Setup for RAG
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    RAG Implementation for PowerPoint
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    Working with EPUB Files
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    EPUB Setup for RAG
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    RAG Implementation for EPUB Files
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    Working with PDF Files
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    PDF Setup for RAG
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    RAG Implementation for PDF Files
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    What Did You Learn in This Section?
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    Exercise: Imposter Syndrome
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    Overview: Multimodal RAG
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    Introduction to Multimodal RAG
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    Setup and Video Processing
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    Extracting Audio from Video
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    Compressing Audio Files
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    Transcribing Audio with OpenAI Whisper
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    Whisper Model
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    Extracting Frames from Video
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    Introduction to Contrastive Learning
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    Understanding the CLIP Model
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    Tokenizing Text for Multimodal Tasks
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    Chunking and Embedding Text
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    Embedding Images for Multimodal Analysis
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    Understanding Cosine Similarity in Multimodal Contexts
  123. Урок 123. 00:10:27
    Applying Contrastive Learning and Cosine Similarity
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    Visualizing Text and Image Embeddings
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    Query Embedding Techniques
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    Calculating Cosine Similarity for Query and Text
  127. Урок 127. 00:04:56
    GenAI Model Setup for Multimodal Tasks
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    Building a GenAI Model
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    What Did You Learn in This Section?
  130. Урок 130. 00:05:28
    Project Briefing: Starbucks Financial Data
  131. Урок 131. 00:11:23
    Transcribing Audio with OpenAI Whisper
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    Embedding Transcription with CLIP
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    Converting PDF to Images
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    Embedding Images for Multimodal Analysis
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    Retrieval System
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    Preparing Context
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    Generative System
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    RAG with OpenAI File Search
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    Vector Stores in OpenAI
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    Setting a Vector Store in the OpenAI API
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    Responses Endpoint with File Search
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    RAG with GPT-4.1-mini
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    RAG with System Developper / Messages
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    Overview: Agentic RAG
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    AI Agents
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    Agentic RAG
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    Setup and Data Loading
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    State Management and Memory in Agentic Systems
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    AgentState Class
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    Greeting the Customer
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    AI Agent that Checks the Question
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    AI Agent that Assesses the Validity of the question
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    Retrieving the Documents
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    Testing the App
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    Generate Answers
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    AI Agent that Improves the Answer
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    Asking User For More Questions
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    Agentic RAG Recap - Key Learnings and Next Steps
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    Game Plan for Knowledge Graphs with LightRAG
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    Knowledge Graphs
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    Knowledge Graphs vs Embeddings
  162. Урок 162. 00:07:36
    LightRAG Setup
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    What is LightRAG?
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    Setting the Working Directory
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    Data Prep
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    Naive RAG
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    Implementing LightRAG
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    Knowledge Graph Visualization
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    Local Knowledge Graph Visualization
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    Game Plan for RAGAS
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    Assessing RAG with RAGAS
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    RAGAS Setup
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    Embedding and Facebook AI Similarity Search (FAISS)
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    Python - RAG
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    Synthetic Data
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    Generating Synthetic Data
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    Python - Answering Synthetic Dataset
  178. Урок 178. 00:05:33
    ROUGE (Recall-Oriented Understudy for Gisting Evaluation) Score
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    ROUGE
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    LLM-Based Assessment
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    Simple Criteria Score - Part 1
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    Simple Criteria Score - Part 2
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    Factual Correctness
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    Rubrics Score
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    Semantic Similarity
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    Factual Correctness
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    Context Precision
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    Semantic Similarity
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    Context Recall
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    Context Precision
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    Response Relevancy
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    Context Recall
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    Response Relevancy
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    Key Learnings and Outcomes: RAGAS
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    Thank You!