Productionizing RAG System

What you'll be able to do

• Data preparation and setup fundamentals
• Chunking strategy comparison building
• AWS S3 knowledge management design
• Bedrock Knowledge Base integration development
• Retrieval performance evaluation
• Multi-strategy retrieval building retrieval
• Advanced RAG pipeline design patterns
• AWS deployment with Fargate

Skills you will practise

• RAG Architecture
• Chunking Strategies
• AWS Bedrock Knowledge Base
• S3 Knowledge Management
• Retrieval Evaluation
• Multi-Strategy Retrieval
• AWS Fargate Deployment
• Docker Containerization
• AWS ECR
• Data Preparation for RAG
• Production Chatbot Architecture
• Vector Search
• Prompt Engineering for RAG
• Chi-Square test ANOVA test
• Scalable API Deployment

1. 01Initial Setup6 lessons · 13 min

   1. Install DependenciesPreview3:25
   2. Download ResourcesReading
   3. Configure AWS CredentialsPreview3:13
   4. Test AWS Connection1:08
   5. Test Bedrock Model Access1:09
   6. Setup E-Commerce FAQ Database3:58
2. 02Understanding the Data4 lessons · 21 min

   1. Environment SetupPreview3:53
   2. Chunking Methods and Techniques – Part 16:27
   3. Chunking Methods and Techniques – Part 25:43
   4. Evaluating Chunking Strategies4:28
3. 03Upload Knowledge Base to S32 lessons · 14 min

   1. Setup & Upload to S38:37
   2. Bedrock Knowledge Base5:09
4. 04Bedrock Knowledge Base8 lessons · 16 min

   1. Setup and Configuration2:31
   2. Advanced RAG Pipeline0:35
   3. Ingestion Job Overview1:11
   4. Trigger New Ingestion Job3:33
   5. Test Knowledge Base Retrieval1:47
   6. Indexed Data Structure1:22
   7. Compare Retrieval Across Multiple Queries1:32
   8. Understanding Vector Search3:11
5. 05Deploying RAG Chatbot to AWS (ECR + ECS Fargate)9 lessons · 34 min

   1. Preview of the Streamlit AppPreview1:29
   2. Building the UI3:12
   3. Containerizing Streamlit App with Docker5:42
   4. Configuring environment variables on AWS4:59
   5. Pushing Docker Images to AWS ECR1:07
   6. ECR Push Commands6:50
   7. Create ECS Cluster2:37
   8. Create Task Definition2:27
   9. Create and Deploy Service5:14

What you need

• Basics of Python
• Foundational knowledge of Data Science
• High school maths

Who this course is for

• Data Science Aspirants
• Data Science Professionals
• Software/Data engineers interested in quantitative analysis
• Professionals working with large datasets
• Data analysts, economists, researchers

Your instructor

Prabhakaran S

Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this course!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I've deployed 20+ global products. I'm also the Founder and Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I've put up the series of courses and projects with detailed explanations, just like on-the-job experience. Hope you love it!

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