Python for AI – Course Outline

Duration: 3 Months (12 Weeks)
Format: Online (Theory + Practical + Projects)

Month 1 – Python Fundamentals & AI Basics

  • Week 1: Getting Started

    • Intro to Agentic AI & AI in the real world
    • Intro to Programming & Python
    • Python Installation (Windows) + Understanding the terminal
    • Running Python in terminal (print() basics)
    • Installing & understanding VS Code
    • Running Python in VS Code
    • Google Colab intro (alternative setup)

  • Week 2: Python Basics

    • Variables & Memory
    • Comments (single-line, multi-line)
    • Strings & Integers
    • Concatenation, f-strings, docstrings
    • Built-in functions: id(), type()

  • Week 3: Operators & Inputs

    • Arithmetic Operators
    • Boolean values
    • Comparison Operators
    • Logical Operators
    • input(), int() for user input
    • Mini-project: Calculator program

  • Week 4: Flow Control & Lists

    • If-else statements
    • Lists & important list methods
    • Intro to Functions
    • Lambda functions
    • Dummy call to LLM (string return)

Month 2 – Data Structures, Functions & Projects

  • Week 5: Dictionaries & Functions in AI

    • Dictionaries (key-value pairs)
    • Dummy call to LLM returning a dictionary
    • More on Functions & Parameters
    • Decorators

  • Week 6: Loops & Comprehensions

    • For loop, While loop
    • range() function
    • List Comprehension
    • Mini-project: Word Counter using loops

  • Week 7: Natural Language Programming + Mini AI

    • Intro to Natural Language Programming in Colab
    • AI-driven text processing example
    • Project: Create a simple chatbot-like function

  • Week 8: Modules & Randomness

    • Python Modules
    • import random module usage
    • Try & Except (Error handling)
    • Set & Tuple basics

Month 3 – Advanced Python & AI Integration

  • Week 9: OOP Concepts

    • Classes & Objects
    • Attributes & Methods
    • Encapsulation, Inheritance, Polymorphism, Abstraction (overview)
    • Project: Bank Account simulation

  • Week 10: AI Tools & Gemini

    • Connecting Gemini LLM (API key, packages, environment setup)
    • First LLM call in Python
    • Revise process in multiple examples

  • Week 11: Streamlit for AI Apps

    • Installing Streamlit
    • Basic Streamlit app (text input/output)
    • Integrating Gemini LLM with Streamlit

  • Week 12: Final Project & Wrap-up

    • Build a Python Game with Gemini
    • AI Assistant project using Gemini + Streamlit
    • Course Recap & Future Path in AI
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