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Udemy - Complete RAG Bootcamp Build, Optimize, and Deploy AI Apps 2025-10

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Title: UdemyGroup: 10Year: 2025Source: Udemy
Info Hash
D24A84FC8A191AD4AA82F349225A0D057C490740
Source
Unverified
Total Size
3.98 GB
Total Files
61
Seeders
1
Leechers
0
Health
1.00
Score
2
Type
Bookware

File List

FileSize
Readme.txt148 B
1 - Introduction to Retrieval-Augmented Generation/4 - Hands on Lab.html4.69 KB
2 - Foundations of RAG Architecture/4 - Hands on Lab.html4.93 KB
3 - Working with Embeddings and Vector Databases/4 - Hands on Lab.html6.1 KB
4 - Section 4 Building RAG Pipelines with LangChain/4 - Hands on Lab.html6.35 KB
6 - Deploying RAG Systems/4 - Hands on Lab.html6.9 KB
5 - Enhancing RAG Performance/4 - Hands on Lab.html7.34 KB
8 - Real-World Use Cases/4 - Hands on Lab.html7.39 KB
7 - Advanced & Hybrid RAG Techniques/4 - Hands on Lab.html8.29 KB
1 - Introduction to Retrieval-Augmented Generation/2 - 1.2 RAG System Overview.en_US.vtt8.91 KB
2 - Foundations of RAG Architecture/2 - 2.2 The Generation Process.en_US.vtt9.17 KB
2 - Foundations of RAG Architecture/1 - 2.1 The Retrieval Process.en_US.vtt10.02 KB
4 - Section 4 Building RAG Pipelines with LangChain/3 - 4.3 Adding Context and Metadata.en_US.vtt10.58 KB
1 - Introduction to Retrieval-Augmented Generation/1 - 1.1 What is RAG.en_US.vtt10.75 KB
1 - Introduction to Retrieval-Augmented Generation/3 - 1.3 Applications of RAG.en_US.vtt10.97 KB
5 - Enhancing RAG Performance/1 - 5.1 Advanced Retrieval Techniques.en_US.vtt11.1 KB
4 - Section 4 Building RAG Pipelines with LangChain/2 - 4.2 RAG Implementation with LangChain.en_US.vtt11.54 KB
5 - Enhancing RAG Performance/2 - 5.2 Optimizing Context and Prompts.en_US.vtt11.84 KB
4 - Section 4 Building RAG Pipelines with LangChain/1 - 4.1 LangChain Core Concepts.en_US.vtt12.25 KB
3 - Working with Embeddings and Vector Databases/3 - 3.3 Building and Querying Vector Stores.en_US.vtt12.26 KB
3 - Working with Embeddings and Vector Databases/1 - 3.1 What Are Embeddings.en_US.vtt12.55 KB
5 - Enhancing RAG Performance/3 - 5.3 Evaluation and Metrics.en_US.vtt12.89 KB
2 - Foundations of RAG Architecture/3 - 2.3 Putting It Together.en_US.vtt13.18 KB
3 - Working with Embeddings and Vector Databases/2 - 3.2 Introduction to Vector Databases.en_US.vtt13.41 KB
6 - Deploying RAG Systems/3 - 6.3 Deployment & Scalability.en_US.vtt14.78 KB
6 - Deploying RAG Systems/2 - 6.2 Backend APIs.en_US.vtt14.9 KB
6 - Deploying RAG Systems/1 - 6.1 Front-End Integration.en_US.vtt15 KB
7 - Advanced & Hybrid RAG Techniques/1 - 7.1 Hybrid Search (Keyword + Vector).en_US.vtt15.78 KB
9 - Section 9/1 - 9.1 RAG for Developers & Data Scientists.en_US.vtt21.59 KB
8 - Real-World Use Cases/3 - 8.3 Integrating RAG into Workflows.en_US.vtt23.5 KB
8 - Real-World Use Cases/1 - 8.1 Enterprise & Industry RAG Solutions.en_US.vtt24.15 KB
8 - Real-World Use Cases/2 - 8.2 Security & Governance.en_US.vtt24.18 KB
7 - Advanced & Hybrid RAG Techniques/2 - 7.2 Multi-Modal RAG.en_US.vtt24.25 KB
7 - Advanced & Hybrid RAG Techniques/3 - 7.3 Agentic RAG.en_US.vtt24.62 KB
9 - Section 9/2 - 9.2 Capstone Project.en_US.vtt24.75 KB
1 - Introduction to Retrieval-Augmented Generation/2 - 1.2 RAG System Overview.mp488.74 MB
2 - Foundations of RAG Architecture/2 - 2.2 The Generation Process.mp494.96 MB
2 - Foundations of RAG Architecture/1 - 2.1 The Retrieval Process.mp4107.3 MB
4 - Section 4 Building RAG Pipelines with LangChain/3 - 4.3 Adding Context and Metadata.mp4109.29 MB
1 - Introduction to Retrieval-Augmented Generation/1 - 1.1 What is RAG.mp4109.41 MB
4 - Section 4 Building RAG Pipelines with LangChain/2 - 4.2 RAG Implementation with LangChain.mp4111.96 MB
1 - Introduction to Retrieval-Augmented Generation/3 - 1.3 Applications of RAG.mp4113.8 MB
5 - Enhancing RAG Performance/2 - 5.2 Optimizing Context and Prompts.mp4115.14 MB
5 - Enhancing RAG Performance/1 - 5.1 Advanced Retrieval Techniques.mp4117.03 MB
4 - Section 4 Building RAG Pipelines with LangChain/1 - 4.1 LangChain Core Concepts.mp4124.55 MB
3 - Working with Embeddings and Vector Databases/1 - 3.1 What Are Embeddings.mp4125.33 MB
3 - Working with Embeddings and Vector Databases/3 - 3.3 Building and Querying Vector Stores.mp4130.98 MB
5 - Enhancing RAG Performance/3 - 5.3 Evaluation and Metrics.mp4141.63 MB
2 - Foundations of RAG Architecture/3 - 2.3 Putting It Together.mp4142.53 MB
7 - Advanced & Hybrid RAG Techniques/1 - 7.1 Hybrid Search (Keyword + Vector).mp4149.47 MB
3 - Working with Embeddings and Vector Databases/2 - 3.2 Introduction to Vector Databases.mp4151.84 MB
6 - Deploying RAG Systems/1 - 6.1 Front-End Integration.mp4159.24 MB
6 - Deploying RAG Systems/2 - 6.2 Backend APIs.mp4160.11 MB
6 - Deploying RAG Systems/3 - 6.3 Deployment & Scalability.mp4162.62 MB
9 - Section 9/1 - 9.1 RAG for Developers & Data Scientists.mp4200.27 MB
8 - Real-World Use Cases/3 - 8.3 Integrating RAG into Workflows.mp4231.56 MB
8 - Real-World Use Cases/1 - 8.1 Enterprise & Industry RAG Solutions.mp4238.42 MB
7 - Advanced & Hybrid RAG Techniques/2 - 7.2 Multi-Modal RAG.mp4241.19 MB
9 - Section 9/2 - 9.2 Capstone Project.mp4243.24 MB
7 - Advanced & Hybrid RAG Techniques/3 - 7.3 Agentic RAG.mp4243.89 MB
8 - Real-World Use Cases/2 - 8.2 Security & Governance.mp4257.13 MB

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