The use of Artificial Intelligence has nowadays become pretty common in our lives. As such it is important that the students get themselves familiarized with the basic concepts of AI. CBSE Class 9 syllabus for AI comprise of important topics and sub-topics that can provide the students fundamental knowledge about this technology. Along with this, the students will also get to learn basics of Python coding language. In this article, the candidates can find the complete details of the CBSE Class 9 Artificial Intelligence syllabus 2023-24.
CBSE Artificial Intelligence Syllabus for Class 9 2023-24
The syllabus of AI provides the students adaptation with the important technical and life skills for AI. The main aim is to help learners understand the concepts of Artificial Intelligence and its application in different scenarios. Check below the complete details of the CBSE Class 9 Artificial Intelligence syllabus 2023-24.
|Unit No.||Unit Name||Sub-unit||Duration/ Periods|
|Unit I||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 II||AI Project Cycle||Problem Scoping||14 Hours/ 21 Periods|
|Data Acquisition||2 Hours/ 3 Periods|
|Data Exploration||4 Hours/ 6 Periods|
|Modelling||6 Hours/ 9 Periods|
|Unit III||Neural Network||—–||4 Hours/ 6 Periods|
|Unit IV||Introduction To Python||—–||70 Hours/ 105 Periods|
|—–||Total||—–||112 Hours/ 168 Periods|
Unit I: Introduction to AI
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 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.
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.
Session: Introduction to sustainable development goals
Recommended Activity: Go Goals Board Game
Learners to answer questions on Sustainable Development Goals
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 visualize 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
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
Unit II: AI Project Cycle
Session: Introduction to AI Project Cycle
- Problem Scoping
- Data Acquisition
- Data Exploration
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
Activity: Introduction to data and its types
Students work around the scenarios given to them and think of ways to acquire data.
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
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 analyze a pattern amongst same alphabets and to differentiate the different ones
Unit III: 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 IV: 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
CBSE Class 9 Artificial Intelligence Syllabus 2023-24: Download PDF
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