This course covers the entire syllabus of grade 9 portion. After the completion of syllabus through board paper discussion is done and startegies are discussed to do well in Exam. 

SYLLABUS-

UNIT WISE DISTRIBUTION UNIT NAME OF THE UNIT

1 INTRODUCTION TO AI

 Excite 

Session: Introduction to AI and setting up the context of the curriculum

Relate

Purpose 

      Session: Introduction to sustainable development goals

Possibilities 

Session: Theme-based research and Case Studies

AI Ethics

   Session: AI Bias and AI Access  Discussing about the possible bias in data collection  Discussing about the implications of AI technology

2 AI PROJECT CYCLE

Session: Introduction to AI Project Cycle  Problem Scoping  Data Acquisition  Data Exploration  Modelling  Evaluation

Problem Scoping 

Data Acquisition 

Data Exploration

Session: Data Visualisation  Need of visualising data  Ways to visualise data using various types of graphical tools

Modelling

Session: Decision Tree To introduce basic structure of Decision Trees to students.

3 NEURAL NETWORK 

Session: Introduction to neural network  Relation between the neural network and nervous system in human body  Describing the function of neural network

4 INTRODUCTION TO PYTHON -

Session: Introduction to Python language Introducing python programming and its applications