+91 96452 47165

Lessons > Introduction to RAG

Introduction to RAG

Course Content
Day 1
0/5
Introduction to AI
Introduction to Generative AI
Introduction to Large Language Models
Popular LLM Examples
How LLM works
Day 2
0/4
Setting up Google Colab
Installing AI Libraries
Managing API Keys
Using Colab Features
Day 3
0/5
Introduction to Prompt Engineering
Basic Prompt Creation
Types of Prompts
Improving Prompt Quality
Optimizing AI Performance
Day 4
0/4
Natural Language Processing
Building NLP Pipelines
Advanced NLP Applications
Understanding Model Ethics
Day 5
0/4
Introduction to AI Image Generation
Using Image Generation Models
Creating Images from Text
Understanding Image AI Technology
Day 6
0/4
Introduction to Audio AI
Text-to-Speech Technology
Speech-to-Text Processing
Video Generation Basics
Day 7
0/4
Building Your First AI Bot
Designing Conversations
Improving Bot Performance
Understanding RAG
Day 8
0/3
Introduction to AI Agents
Agent Components
Introduction to Agentic AI
Day 9
0/4
Introduction to Fine-tuning
Fine-tuning Parameters
Adapting Models for Specific Tasks
Fine-tuning Types
Day 10
0/4
Understanding LLM Fine-tuning
Pre-training vs Fine-tuning
Hands-on Fine-tuning Practice
Fine-tuning Ethics
Day 11
0/4
Introduction to RAG
Building RAG Systems
Introduction to LangChain
LangChain Applications
Day 12
0/4
Introduction to AI Code Generation
Code Generation Models
Working with Different AI Models
AI Developer Assistants
AI Accelerator Program – 1 to 1

Review how combining retrieval systems with LLMs enhances factual accuracy.

Previous
Next