Build Intelligent AI Apps with Retrieval-Augmented Generation (RAG)
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Course Overview
Table of Contents
Workshop Registration End Date :2025-05-15
Limited SeatsClosing Soon
Build Intelligent AI Apps with Retrieval-Augmented Generation (RAG)
Professional Certification Program
🎥
FormatLive + Recorded
📅
Duration8 Weeks
📜
CertificationVerified
Program Syllabus
Module 1
About
Build Intelligent AI Apps with Retrieval-Augmented Generation (RAG) is a cutting-edge international workshop focused on one of the most powerful emerging techniques in AI today. RAG combines the generative power of LLMs with retrieval systems like vector databases to deliver contextually relevant, up-to-date, and verifiable outputs.
Participants will learn to architect and implement RAG pipelines, work with tools like LangChain, Haystack, Pinecone, FAISS, and integrate them with LLMs (OpenAI, Cohere, DeepSeek, or Hugging Face models) for real-world use cases in enterprise automation, research assistants, chatbots, legal tech, and knowledge engines.
Module 2
Aim
To empower participants with the practical skills and conceptual understanding needed to design, build, and deploy Retrieval-Augmented Generation (RAG) pipelines that combine Large Language Models (LLMs) with dynamic, up-to-date data sources for intelligent, trustworthy AI applications.
Module 3
Workshop Objectives
- Demystify Retrieval-Augmented Generation and its components
- Enable real-world implementation with popular AI toolkits
- Teach prompt injection prevention, grounding, and retrieval optimization
- Stimulate innovation in building knowledge-enhanced LLM apps
- Guide participants to build and deploy a fully functional AI app with RAG
Module 4
Workshop Structure
Module 5
Day 1: Introduction & Fundamentals of RAG
Title: RAG 101 – Foundation of Retrieval-Augmented Generation
- Overview of Language Models (LLMs) & Limitations
- Why RAG? – Bridging LLMs with External Knowledge
- Anatomy of a RAG System: Retriever + Generator
- Tools: FAISS, ChromaDB, LangChain, HuggingFace, OpenAI
Hands-on:
- Build a vector store using FAISS/Chroma
- Embed documents using SentenceTransformers or OpenAI Embeddings
Module 6
Day 2: Building the RAG Pipeline
Title: Designing the RAG Workflow
- Types of Retrievers: Dense vs Sparse
- Query Rewriting, Chunking & Indexing
- LangChain vs Haystack vs Custom RAG Pipelines
- Prompt Engineering in RAG
Hands-on:
- Build a RAG pipeline using LangChain
- Query documents and generate contextual answers using GPT
Module 7
Day 3: Advanced Features & Deployment
Title: Productizing Your RAG Application
- Evaluation Metrics for RAG Systems (EM, BLEU, Recall@k)
- Caching, Logging, and Observability
- Securing APIs & Cost Management
- Open-source RAG use cases (e.g., DocChat, Chat with PDF, Legal AI, Academic Copilots)
Hands-on:
- Deploy a working RAG chatbot on Gradio
- Custom PDF/CSV Q&A assistant (bring-your-own-data)
Module 8
Intended For
- AI/ML developers and data scientists
- Backend or full-stack developers building AI integrations
- NLP researchers and LLM enthusiasts
- LegalTech, HealthTech, and EdTech innovators
- Students with a working knowledge of Python and NLP
Module 9
Important Dates
Module 10
Registration Ends
2025-05-15
Indian Standard Timing 6:00 PM
Module 11
Workshop Dates
2025-05-15 to 2025-05-17
Indian Standard Timing 7 PM
Module 12
Workshop Outcomes
- Master RAG pipeline design and deployment
- Learn to embed documents and retrieve relevant context dynamically
- Combine search and generation seamlessly for fact-rich AI applications
- Build an intelligent AI assistant that can reason over documents or databases
- Gain hands-on experience with LangChain, FAISS, Pinecone, and Hugging Face
- Receive international workshop certification and reusable project templates
Module 13
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Mentor Profile
Module 14
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
List of Currencies
Fee Structure
Module 18
Industry Professional
INR. 5999
USD. 75
List of Currencies
Module 19
FOR QUERIES, FEEDBACK OR ASSISTANCE
Module 20
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Key Takeaways
- Access to Live Lectures
- Access to Recorded Sessions
- e-Certificate
- Query Solving Post Workshop
Module 21
Future Career Prospects
Participants will be equipped for dynamic roles such as:
- RAG Application Engineer
- AI Product Developer (LLM-integrated)
- NLP Architect
- AI Solutions Engineer
- Conversational AI Developer
- Intelligent Automation Specialist
Module 22
Job Opportunities
- Generative AI startups and product companies
- Enterprises building knowledge assistants and intelligent chatbots
- Legal, education, and healthcare organizations deploying internal AI tools
- SaaS platforms enhancing LLM reliability and groundedness
- Government and research institutions focused on open-source AI systems
Module 25
Enter the Hall of Fame!
Take your research to the next level!
Publication Opportunity
Potentially earn a place in our coveted Hall of Fame.
Centre of Excellence
Join the esteemed Centre of Excellence.
Networking and Learning
Network with industry leaders, access ongoing learning opportunities.
Hall of Fame
Get your groundbreaking work considered for publication in a prestigious Open Access Journal (worth ₹20,000/USD 1,000).
Achieve excellence and solidify your reputation among the elite!
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Module 26
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Lead Instructor
Dr. Sarah Chen
PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
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