CBSE Class 9th A.I Syllabus 2022-23

CBSE Class 9th A.I Syllabus 2022-23

The Central Board of Secondary Education(CBSE) introduced Artificial Intelligence in collaboration with the IBM AI program in the year 2019. To teach more than 5000 students and 1000 teachers to enable the younger generation to keep up with modern technology.

Artificial Intelligence will help students to build a strong  foundation for the modern digital world by learning advance coding program like Python and basics of daily digital problems.

Table of Contents

Check here the CBSE Class 9th Artificial Intelligence Syllabus 2022-23

Unit No Unit Name Sub-Unit Duration/Periods

Unit 1

Introduction to AI

Excite

2 Hours 40  mins/4 Periods

Relate

2 Hours/ 3 Periods

Purpose

2 Hours/ 3 Periods

Possibilities

2 Hours/ 3 Periods

AI Ethics

3 Hours 20 mins/ 5 Periods

UNIT 2

AI Project Cycle

Project Scoping

14 hours/ 21 Periods

Data Acquisition

2 Hours/ 3 Periods

Data Exploration

4 Hours/ 6 Periods

Modeling

6 Hours/ 9 Periods

UNIT 3

Neural Network

---

4 Hours/ 6 Periods

UNIT 4

Introduction To Python

---

70 Hours/ 105 Periods

Total

112 Hours/168 Periods

Unit 1: Introduction To A.I

Excite

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

Ice Breaker Activity: Dream Smart Home idea Learners to design a rough layout of floor plan of their dream smart home

Recommended Activity: The Al Game

Learners to participate in three games based on different Al domains

  • Game 1: Rock, Paper and Scissors (based on data)
  • Game 2: Mystery Animal (based on Natural Language Processing -NLP)
  •  Game 3. Emoji Scavenger Hunt (based on Computer Vision – CV) Recommended Activity: Al Quiz (Paper Pen/Online Quiz)

Recommended Activity: To write a letter to one’s future self

Learners will have to write a letter to self-keeping the future in context. They will describe what they have learnt so far or what they would like to learn someday.

Relate

Video Session: To watch a video

Introducing the concept of Smart Cities, Smart Schools and Smart Homes

Recommended Activity: Write an Interactive Story

Learners to draw a floor plan of a Home/School/City and write an interactive story around it using Story Speaker extension in Google docs.

Purpose

Session: Introduction to sustainable development goals

Recommended Activity: Go Goals Board Game

Learners to answer questions on Sustainable Development Goals

Possibilities

Session: Theme-based research and Case Studies

  • Learners will listen to various case studies of inspiring start-ups, companies or communities where Al has been involved in real-life.
  • Learners will be allotted a theme around which they need to search for present Al trends and have to visualize the future of Al in and around their respective theme

Recommended Activity: Job Ad Creating activity.

Learners to create a job advertisement for a firm describing the nature of job available and the skill-set required for it 10 years down the line. They need to figure out how At is going to transform the nature of jobs and create the Ad accordingly.

Al Ethics

Video Session: Discussing about Al Ethics

Recommended Activity: Ethics Awareness

Students play the role of major stakeholders and they have to decide what is ethical and what is not for a given scenario

Session: Al Bias and Al Access

  • Discussing about the possible bias in data collection
  • Discussing about the implications of Al technology

Recommended Activity: Balloon Debate

Students divide in teams of 3 and 2 teams are given same theme. One team goes in affirmation to Al for their section while the other one goes against it. They have to come up with their points as to why Al is beneficial/ harmful for the society.

Unit 2: A.I Project Cycle

Problem Scoping

Session: Introduction to Al Project Cycle

  • Problem Scoping
  • Data Acquisition
  • Data Exploration
  • Modelling
  • Evaluation

Activity: Brainstorm around the theme provided and set a goal for the Al Project

  • Discuss various topics within the given theme and select one.
  • List down/ Draw a mind-map of problems related to the selected topic and choose one problem to be the goal for the project.

Activity: To set actions around the goal

  • List down the stakeholders involved in the problem
  • Search on the current actions taken to solve this problem
  • Think around the ethics involved in the goal of your project

Activity: Data and Analysis

  • What are the data features needed?
  • Where can you get the data?
  • How frequent do you have to collect the data?
  • What happens if you don’t have enough data?
  • What kind of analysis needs to be done?
  • How will it be validated?
  • How does the analysis inform the action?

Presentation: Presenting the goal, actions and data

Data Acquisition

Activity: Introduction to data and its types

Students work around the scenarios given to them and think of ways to acquire data

Data Exploration

Session: Data Visualization

  • Need of visualizing data
  • Ways to visualize data using various types of graphical tools

Recommended Activity: Let’s use Graphical Tools

  • To decide what kind of data is required for a given scenario and acquire the same. 
  • To select an appropriate graphical format to represent the data acquired.
  • Presenting the graph sketched

Modelling

Session: Decision Tree

To introduce basic structure of Decision Trees to students

Recommended Activity: Decision Tree

To design a Decision Tree based on the data given

Recommended Activity: Pixel It

  • To create an “Al Model” to classify handwritten letters
  • Students develop a model to classify handwritten letters by diving the alphabets into pixels
  • Pixels are then joined together to analyze a pattern among same alphabets and to differentiate the different ones

Unit 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

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

Unit 4: Introduction To Python

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

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

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