Course overview
Total duration: 24 hours
Schedule: Flexible, 3 hours/week over 8 weeks
Programming language: Python
Focused learning groups: 5 to 10 students per batch
Course format: Structured curriculum plus hands-on projects
Course content: Download the course flyer (PDF)
Course objectives
Introduce and advance students' understanding of Python programming
Develop strong logical thinking and problem-solving skills
Encourage hands-on coding and project-based learning
Build real-world applications using Python
Nurture future-ready technology skills from an early age
Course modules
Level 1: Python basics for beginners
Goal: Learn core Python concepts through visual and gamified learning.
What is Python? Installing and using IDLE / Thonny
Print statements and text output
Variables and data types
Simple math operations and input functions
Basic conditional statements (if/else)
Introduction to loops (while, for)
Fun activities: build a simple calculator; create a "Guess the Number" game.
Mini project: math quiz app or interactive story game.
Level 2: Foundational Python programming
Goal: Strengthen problem-solving skills and coding confidence.
Review of Level 1 concepts
Advanced data types: lists, tuples, dictionaries
Nested conditions and loops
Introduction to functions
Error handling (try/except)
Working with strings and user input
File handling basics
Logic puzzles and coding challenges
Mini projects: rock-paper-scissors game; contact book using file handling.
Level 3: Intermediate Python with real-world applications
Goal: Build real-world applications using intermediate Python concepts.
Deep dive into functions and recursion
Working with files (txt, csv)
Object-Oriented Programming (classes and objects)
Python libraries: random, datetime, math, os
Basic GUI development using Tkinter
Introduction to modules and packages
Mini projects: to-do app with GUI; expense tracker; random password generator.
Level 4: Advanced Python for high schoolers
Goal: Prepare students for advanced topics, career paths, and innovation.
Advanced OOP (inheritance, polymorphism)
Exception handling and logging
Web scraping (BeautifulSoup / Requests)
Working with APIs
Introduction to data science with Python
Libraries: Pandas, NumPy, Matplotlib
Data cleaning, visualization and CSV/Excel analysis
Intro to AI/ML (optional extension): simple machine learning models (Teachable Machine / scikit-learn).
Capstone projects
Personal budget application
Student performance dashboard
Data analysis project (movie ratings / weather trends)
Course features
Theory plus hands-on labs
Engaging examples and interactive coding activities
Homework and real-world projects
Multiple programming levels to choose from
Curriculum aligned with middle and high school standards
Special summer and winter batches
Fun events and coding challenges