Artificial Intelligence (AI) is an overarching discipline that covers a broad range of domains and applications, and is expected to impact every field in the coming future. This curriculum focuses on building AI readiness in young minds.

1. Introduction to AI

  1. Excite
  2. Relate
  3. Purpose
  4. Possibilities
  5. AI Ethics

2. AI Project Cycle

  • Problem Scoping
  • Data Acquisition
  • Data Exploration
  • Modelling

3. Neural Network

Understand and appreciate the concept of Neural Network through gamification.

Session: Introduction to neural network

  • Relation between the neural network and nervous system in human body
  • Describing the function of neural network.

Recommended Activity: Creating a Human Neural Network

  • Students split in four teams each representing input layer (X students), hidden layer 1 (Y students), hidden layer 2 (Z students) and output layer (1 student) respectively.
  • Input layer gets data which is passed on to hidden layers after some processing. The output layer finally gets all information and gives meaningful information as output.

4. Introduction to Python

Learn basic programming skills through gamified platforms.

Recommended Activity: Introduction to programming using Online Gaming portals like Code Combat

Acquire introductory Python programming skills in a very user-friendly format.

Session: Introduction to Python language

Introducing python programming and its applications

Practical: Python Basics

  • Students go through lessons on Python Basics (Variables, Arithmetic Operators, Expressions, Data Types - integer, float, strings, using print() and input() functions)
  • Students will try some simple problem solving exercises on Python Compiler.

Practical: Python Lists

  • Students go through lessons on Python Lists (Simple operations using list) 
  • Students will try some basic problem solving exercises using lists on Python Compiler.