Master Python, RAG & Agentic AI - Launch Your AI Career
Program Overview
An intensive 6-week internship program designed to give you hands-on experience with cutting-edge AI technologies. Learn Python programming, build RAG (Retrieval-Augmented Generation) systems, and create Agentic AI models that can autonomously perform tasks. This program is perfect for students and professionals looking to break into the AI industry.
Duration
4-6 Weeks (12-18 hours/month)
Level
Beginners / Freshers
Cost
100% AI
Format
Online + Hands-on Projects
WEEK 1: Python Fundamentals
Building Your Programming Foundation
Day 1-2: Python Basics & Environment Setup
Objective: Set up development environment and learn Python fundamentals
Installing Python, VS Code, and essential extensions
Variables, data types, and operators
Control flow: if-else, loops (for, while)
Functions and modular programming
Working with strings and string methods
Day 3-4: Data Structures & File Handling
Objective: Master Python data structures for AI applications
Lists, tuples, and list comprehensions
Dictionaries and sets for data organization
File I/O operations (reading/writing files)
Working with JSON and CSV data
Exception handling and debugging
Day 5-7: Object-Oriented Python & Libraries
Objective: Learn OOP concepts and essential libraries
Classes, objects, and inheritance
Introduction to NumPy for numerical computing
Pandas basics for data manipulation
Working with APIs using requests library
Mini Project: Build a data processing script
WEEK 2: RAG (Retrieval-Augmented Generation)
Building Intelligent Document Q&A Systems
Day 1-2: Understanding RAG Architecture
Objective: Learn the fundamentals of RAG systems
What is RAG and why it matters
Vector embeddings and semantic search
Introduction to LangChain framework
Setting up OpenAI/Gemini API integration
Understanding tokens, context windows, and prompts
Day 3-4: Building a Complete RAG Application
Objective: Create a production-ready RAG system
Designing effective prompts for Q&A
Implementing retrieval chains
Adding conversation memory
Building a Streamlit web interface
Project: Document Q&A Chatbot
WEEK 3: Agentic AI Models
Creating Autonomous AI Agents
Day 1-2: Introduction to AI Agents
Objective: Understand agent architectures and capabilities
What are AI Agents and how they differ from chatbots
Agent components: Planning, Memory, Tools
ReAct (Reasoning + Acting) framework
Introduction to LangGraph for agent workflows
Understanding agent loops and decision making
Day 3-4: Tools & Function Calling
Objective: Equip agents with real-world capabilities
Creating custom tools for agents
Web search and browsing tools
Code execution tools (Python REPL)
API integration tools
File management and database tools
WEEK 4: Integration & Real-World Applications
Bringing It All Together
What You'll Learn
Python Programming: From basics to AI-ready development skills
