CBSE Sample Papers, Worksheets , Revision Notes

Artificial Intelligence Syllabus for CBSE Class 9

ARTIFICIAL INTELLIGENCE (CODE 417)
CURRICULUM FOR CLASS IX (INSPIRE AND ACQUIRE MODULE)

OBJECTIVE

The objective of this module/curriculum – which combines both Inspire and Acquire modules is to develop a readiness for understanding and appreciating Artificial Intelligence and its application in our lives. This module/curriculum focuses on:

  • Helping learners understand the world 
    of Artificial Intelligence and its applications
    through games, activities and multi-sensorial 
    learning to become AI-Ready.
  • Introducing the learners to three domains
    of AI in an age appropriate manner.
  • Allowing the learners to construct meaning
    of AI through interactive participation and 
    engaging hands-on activities.
  • Introducing the learners to AI Project Cycle.
  • Introducing the learners to programming 
    skills - Basic python coding

LEARNING OUTCOMES

Learners will be able to

  • Identify and appreciate Artificial Intelligence and describe 
    its applications in daily life
  • Relate, apply and reflect on the Human-Machine Interactions to 
    identify and interact with the three domains of AI: Data, 
    Computer Vision and Natural Language Processing and Undergo 
    assessment for analysing their progress towards acquired 
    AI-Readiness skills.
  • Imagine, examine and reflect on the skills required for 
    futuristic job opportunities.
  • Unleash their imagination towards smart homes and build an 
    interactive story around it.
  • Understand the impact of Artificial Intelligence on 
    Sustainable Development Goals to develop responsible 
    citizenship.
  • Research and develop awareness of skills required for jobs 
    of the future.
  • Gain awareness about AI bias and AI access and describe 
    the potential ethical considerations of AI.
  • Develop effective communication and collaborative 
    work skills.
  • Get familiar and motivated towards Artificial Intelligence
    and Identify the AI Project Cycle framework.
  • Learn problem scoping and ways to set goals for 
    an AI project and understand the iterative nature 
    of problem scoping in the AI project cycle.
  • Brainstorm on the ethical issues involved around the problem 
    selected.
  • Foresee the kind of data required and the kind of analysis to 
    be done, identify data requirements  and find reliable sources
    to obtain relevant data.
  • Use various types of graphs to visualise acquired data.
  • Understand, create and implement the concept of Decision Trees.
  • Understand and visualise computer’s ability to identify 
    alphabets and handwritings
  • Understand and appreciate the concept of Neural Network through 
    gamification and learn basic programming skills through 
    gamified platforms.
  • Acquire introductory Python programming skills 
    in a very user-friendly format.

UNIT WISE DISTRIBUTION

UNITNAME OF THE UNITSUB-UNITDURATIONPERIODS
1INTRODUCTION TO AIExcite2 Hours 40 Mins.4 Periods
Relate02 Hours3 Periods
Purpose02 Hours3 Periods
Possibilities02 Hours3 Periods
AI Ethics3 Hours 20 Mins.5 Periods
2AI PROJECT CYCLEProblem Scoping14 Hours21 Periods
Data Acquisition02 Hours3 Periods
Data Exploration04 Hours6 Periods
Modelling06 Hours9 Periods
3NEURAL NETWORK04 Hours6 Periods
4INTRODUCTION TO PYTHON70 Hours105 Periods
TOTAL112 Hours168 Periods

COURSE OUTLINE

UNIT  1 : INTRODUCTION TO AI
SUB-UNIT : Excite

SESSION / ACTIVITY / PRACTICAL

Session: Introduction to AI 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 AI Game Learners to participate in three games based on different AI 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:AI Quiz (Paper Pen/Online Quiz)
Recommended Activity: To write a letter
Writing a Letter to one’s future self

  • Learners 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

LEARNING OUTCOMES

  • To identify and appreciate Artificial Intelligence and describe 
    its applications in daily life.
  • To relate, apply and reflect on the Human-Machine Interactions.
  • To identify and interact with the three domains of AI: Data, 
    Computer Vision and Natural Language Processing.
  • To undergo an assessment for analysing progress towards 
    acquired AI- Readiness skills.
  • To imagine, examine and reflect on the skills required 
    for futuristic job opportunities.
SUB-UNIT : Relate

SESSION / ACTIVITY / PRACTICAL

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.

LEARNING OUTCOMES

  • Learners to relate to application of Artificial 
    Intelligence in their daily lives.
  • To unleash their imagination towards smart homes 
    and build an interactive story around it.
  • To relate, apply and reflect on the Human-Machine Interactions.
SUB-UNIT Purpose
SESSION / ACTIVITY / PRACTICAL
Session: Introduction to sustainable development goals

Recommended Activity: Go Goals Board Game

Learners to answer questions on Sustainable Development Goals

LEARNING OUTCOMES

To understand the impact of Artificial Intelligence on 
Sustainable Development Goals to develop responsible 
citizenship.
SUB-UNIT Possibilities

SESSION / ACTIVITY / PRACTICAL

Session: Theme-based research and Case Studies

  • Learners will listen to various case-studies of inspiring start-ups, companies or communities where AI has been involved in real-life.
  • Learners will be allotted a theme around which they need to search for present AI trends and have to visualise the future of AI 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 AI is going to transform the nature of jobs and create the Ad accordingly.

LEARNING OUTCOMES

  • To research and develop awareness of skills required for 
    jobs of the future.
  • To imagine, examine and reflect on the skills
    required for the futuristic opportunities.
  • To develop effective communication and collaborative work 
    skills.

SUB-UNIT AI Ethics
SESSION / ACTIVITY / PRACTICAL

Video Session: Discussing about AI 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: AI Bias and AI Access

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

Recommended Activity: Balloon Debate

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

LEARNING OUTCOMES

  • To understand and reflect on the ethical issues around AI.
  • To gain awareness around AI bias and AI access.
  • To let the students analyse the advantages and disadvantages 
    of Artificial Intelligence.

UNIT  2 : AI PROJECT CYCLE

SUB-UNIT  Problem Scoping

SESSION / ACTIVITY / PRACTICAL

Session: Introduction to AI Project Cycle

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

Activity: Brainstorm around the theme provided and set a goal for the AI project.

  • Discuss various topics within the given theme and select one.
  • List down/ Draw a mindmap 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.

LEARNING OUTCOMES

  • Identify the AI Project Cycle framework.
  • Learn problem scoping and ways to set goals for an AI project.
  • Identify stakeholders involved in the problem scoped.
  • Brainstorm on the ethical issues involved around the 
    problem selected.
  • Understand the iterative nature of problem scoping for 
    in the AI project cycle.
  • Foresee the kind of data required and the kind of analysis
    to be done.
  • Share what the students have discussed so far.
SUB-UNIT  Data Acquisition

SESSION / ACTIVITY / PRACTICAL

Activity: Introduction to data and its types.

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

LEARNING OUTCOMES

  • Identify data requirements and find reliable sources to obtain relevant data.
SUB-UNIT : Data Exploration

SESSION / ACTIVITY / PRACTICAL

Session: Data Visualisation

  • Need of visualising data
  • Ways to visualise 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.

LEARNING OUTCOMES

  • To understand the purpose of Data Visualisation
  • Use various types of graphs to visualise acquired data.
SUB-UNIT Modelling

SESSION / ACTIVITY / PRACTICAL

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 “AI 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 analyse a pattern amongst same alphabets and to differentiate the different ones.

LEARNING OUTCOMES

Understand and visualise computer’s ability 
to identify alphabets and handwritings.

UNIT  3 :  NEURAL NETWORK

SESSION / ACTIVITY / PRACTICAL

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.

LEARNING OUTCOMES

Understand and appreciate the concept of Neural Network 
through gamification.

UNIT  5 : INTRODUCTION TO PYTHON

SESSION / ACTIVITY / PRACTICAL

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.

LEARNING OUTCOMES

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

Source :- CBSE Website 9 (cbse.nic.in)

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