CBSE Class 9 Artificial Intelligence Latest Syllabus, Unit Wise Chapters And Marking Scheme: The new curriculum for CBSE class 9 AI has been released by CBSE on it's official website. In this article, we will be providing the detailed syllabus, unit-wise chapters and the marking scheme for the Class 9 AI syllabus. You can download the syllabus from the direct link for free.
OBJECTIVES OF THE COURSE:
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:
- To become AI-ready, Help learners understand the world of Artificial Intelligence and its applications through games, activities and multi-sensorial learning.
- Introducing the learners to three domains of AI in an age-appropriate manner.
- Allowing the learners to construct the meaning of AI through interactive participation and engaging hands-on activities.
- Revisiting AI domains, project cycle and Ethics
- Introducing the learners to the importance of Math for AI, data literacy and generative AI
- Introducing the learners to programming skills - Basic Python coding language.
CBSE Class 9 Artificial Intelligence Syllabus 2024-25
UNITS | NO. OF HOURS for Theory and Practical | MAX. MARKS for Theory and Practical | ||
PART A | Employability Skills | |||
Unit 1: Communication Skills-I | 10 | 2 | ||
Unit 2: Self-Management Skills-I | 10 | 2 | ||
Unit 3: ICT Skills-I | 10 | 2 | ||
Unit 4: Entrepreneurial Skills-I | 15 | 2 | ||
Unit 5: Green Skills-I | 5 | 2 | ||
Total | 50 | 10 | ||
PART B | Subject Specific Skills | |||
Theory | Practical | |||
Unit 1: AI Reflection, Project Cycle and Ethics | 30 | 25 | 10 | |
Unit 2: Data Literacy | 22 | 28 | 10 | |
Unit 3: Math for AI (Statistics & Probability) | 12 | 13 | 7 | |
Unit 4: Introduction to Generative AI | 8 | 12 | 5 | |
Unit 5: Introduction to Python | 1 | 9 | 8 | |
Total | 160 | 40 | ||
PART C | Practical Work | |||
Unit 5: Introduction to Python Practical File (minimum 15 programs) | 15 | |||
Practical Examination ● Simple programs using input and output function ● Variables, Arithmetic Operators, Expressions, Data Types ● Flow of control and conditions ● Lists * Any 3 programs based on the above topics | 15 | |||
Viva Voce | 5 | |||
Total | 35 | |||
PART D | Project Work / Field Visit / Student Portfolio * relate it to Sustainable Development Goals | 15 | ||
Total | 15 | |||
GRAND TOTAL | 210 | 100 |
PART-A: EMPLOYABILITY SKILLS
S. No. | Units | Duration in Hours |
1 | Unit 1: Communication Skills-I | 10 |
2 | Unit 2: Self-management Skills-I | 10 |
3 | Unit 3: Information and Communication Technology Skills-I | 10 |
4 | Unit 4: Entrepreneurial Skills-I | 15 |
5 | Unit 5: Green Skills-I | 5 |
TOTAL | 50 |
NOTE: Detailed curriculum/ topics covered under Part A: Employability Skills can be downloaded from the CBSE website.
PART-B – SUBJECT SPECIFIC SKILLS
- Unit 1: AI Reflection, Project Cycle and Ethics
- Unit 2: Data Literacy
- Unit 3: Math for AI (Statistics & Probability)
- Unit 4: Introduction to Generative AI
- Unit 5: Introduction to Python
UNIT 1: AI REFLECTION, PROJECT CYCLE AND ETHICS
SUB-UNIT | LEARNING OUTCOMES | SESSION / ACTIVITY / PRACTICAL |
AI Reflection | To identify and appreciate Artificial Intelligence and describe its applications in daily life. | Session: Introduction to AI and setting up the context of the curriculum |
To recognise, engage and relate with the three realms of AI: Computer Vision, Data Statistics and Natural Language Processing. | 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) https://next.rockpaperscissors.ai/ − Game 2: Semantics (based on Natural Language Processing - NLP) https://research.google.com/semantris/ − Game 3: Quick Draw (based on Computer Vision - CV) https://quickdraw.withgoogle.com/ | |
AI PROJECT CYCLE | Identify the AI Project Cycle framework. | Session: Introduction to AI Project Cycle ● Problem Scoping ● Data Acquisition ● Data Exploration ● Modeling ● Evaluation ● Deployment |
Learn problem scoping and ways to set goals for an AI project. | Session: Problem Scoping Activity: Brainstorm around the theme provided and set a goal for the AI project. ● Discuss various topics within the given theme and select one. ● Fill in the 4Ws problem canvas and a problem statement to learn more about the problem identified in the community/ society ● List down/ Draw a mind map of problems related to the selected topic and choose one problem to be the goal for the project. | |
Identify stakeholders involved in the problem scope. Brainstorm on the ethical issues involved around the problem selected. | ● Activity: To set actions around the goal. ● List down the stakeholders involved in the problem. ● Search for the current actions taken to solve this problem. ● Think about the ethics involved in the goal of your project. | |
Understand the iterative nature of problem scoping in the AI project cycle. Foresee the kind of data required and the kind of analysis to be done. | Activity: Data and Analysis ● What are the data features needed? ● How will the features collected affect the problem? ● Where can you get the data? ● How frequently 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? | |
Share what the students have discussed so far. | Presentation: Presenting the goal, actions and data. Teamwork Activity: ● Brainstorming solutions for the problem statement. | |
Identify data requirements and find reliable sources to obtain relevant data. | Session: Data Acquisition Activity: Introduction to data and its types. ● Students work around the scenarios given to them and think of ways to acquire data. Activity: Data Features ● Identifying the possible data features affecting the problem. Activity: System Maps ● Creating system maps considering data features identified. | |
To understand the purpose of Data Visualisation | Session: Data Exploration/ Data Visualisation ● Need of visualising data ● Ways to visualise data using various types of graphical tools. Quiz Time | |
Use various types of graphs to visualise acquired data. | Recommended Activities: Let’s use Graphical Tools ● Selecting an appropriate graphical format and presenting the graph sketched. ● Understanding graphs using https://datavizcatalogue.com/ ● Listing of newly learnt data visualization techniques. ● Top 10 Song Prediction: Identify the data features, collect the data and convert it into a graphical representation. ● Collect and store data in a spreadsheet and create some graphical representations to understand the data effectively. | |
Understand modelling (Rule-based & Learning-based) | Session: Modeling ● Introduction to modelling and types of models (Rule-based & Learning-based) | |
Understand various evaluation techniques. | Session: Evaluation Learners will understand about new terms ● True Positive ● False Positive ● True Negative ● False Negative | |
Challenge students to think about how they can apply their knowledge of deployment in future AI projects and encourage them to continue exploring different deployment methods. | Session: Deployment Recommended Case Study: Preventable Blindness. Activity: Implementation of AI project cycle to develop an AI Model for Personalized Education. | |
To understand and reflect on the ethical issues around AI. | Video Session: Discussing about AI Ethics Recommended Activity: Ethics Awareness ● Students to explore Moral Machine (https://www.moralmachine.net/ ) to understand more about the impact of ethical concerns | |
To gain awareness around AI bias and AI access. | Session: AI Bias and AI Access ● Discussing the possible bias in data collection ● Discussing the implications of AI technology | |
To let the students analyse the advantages and disadvantages of Artificial Intelligence. | Recommended Activity: Balloon Debate ● Students divide into teams of 3 and 2 teams are given the 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 society. |
UNIT 2: DATA LITERACY
SUB-UNIT | LEARNING OUTCOMES | SESSION / ACTIVITY / PRACTICAL |
Basics of data literacy | ● Define data literacy and recognise its importance Understand how data literacy enables informed decision-making and critical thinking ● Apply the Data Literacy Process Framework to analyze and interpret data effectively ● Differentiate between Data Privacy and Security ● Identify potential risks associated with data breaches and unauthorized access. ● Learn measures to protect data privacy and enhance data security | Session: Basics of data literacy ● Introduction to Data Literacy ● Impact of data Literacy ● How to become Data Literate? ● What are data security and privacy? How are they related to AI? ● Best Practices for Cyber Security |
Recommended Activity: Impact of News Articles Reference Videos: ● https://www.youtube.com/watch?v =yhO_t-c3yJY ● https://www.youtube.com/watch?v =aO858HyFbKI ● https://www.cbse.gov.in/cbsenew/ documents/Cyber%20Safety.pdf | ||
Acquiring Data, Processing, and Interpreting Data | ● Determine the best methods to acquire data. ● Classify different types of data and enlist different methodologies to acquire it. ● Define and describe data interpretation. ● Enlist and explain the different methods of data interpretation. ● Recognize the types of data interpretation. ● Realize the importance of data interpretation | Session: Acquiring Data, Processing, and Interpreting Data ● Types of data ● Data Acquisition/Acquiring Data ● Best Practices for Acquiring Data ● Features of data and Data Preprocessing ● Data Processing and Data Interpretation ● Types of Data Interpretation ● Importance of Data Interpretation |
Recommended Activities: ● Trend analysis ● Visualize and Interpret Data | ||
Project Interactive Data Dashboard & Presentation | ● Recognize the importance of data visualization ● Discover different methods of data visualization | Session: Project Interactive Data Dashboard & Presentation ● Data visualization Using Tableau Reference Links ● https://public.tableau.com/en- us/s/download ● https://www.datawrapper.de/ Video Links: ● https://www.youtube.com/watch?v=NL CzpPRCc7U ● https://www.youtube.com/watch?v=_M 8BnosAD78 |
UNIT 3: MATH FOR AI (Statistics & Probability)
SUB-UNIT | LEARNING OUTCOMES | SESSION / ACTIVITY / PRACTICAL |
Importance of Math for AI | Analyzing the data in the form of numbers/images and finding the relation/pattern between them. Use of Math in AI. | Session: Importance of Math for AI ● Finding Patterns in Numbers and images. ● Uses of Math - ○ Statistics ○ Linear Algebra ○ Probability ○ Calculus |
Number Patterns Picture Analogy | Activity: ● observe the number pattern and find the missing number. ● To find connections between sets of images and use them to solve problems, | |
Statistics | Understand the concept of Statistics in real life. | Session : ● Definition of Statistics ● Applications ○ Disaster Management ○ Sports ○ Diseases Prediction ○ Weather Forecast |
Application in various real-life scenarios | Activity: Uses of Statistics in daily life ● Students will explore the applications of statistics in real life. They collect data and can apply various statistical measures to analyze the data. Activity: Car Spotting and Tabulating Purpose: To implement the concept of data collection, analysis and interpretation. Activity Introduction: ● In this activity, Students will be engaged in data collection and tabulation. ● Data collection plays a key role in Artificial Intelligence as it forms the basis of statistics and interpretation by AI. ● This activity will also require students to answer a set of questions based on the recorded data. | |
Probability | Understand the concept of Probability in real life and explore various types of events. | Session: Introduction to Probability ● How to calculate the probability of an event ● Types of events ● understand the concept of Probability using a relatable example. Exercise: Identify the type of event. |
Application in various real-life scenarios | Session: Applications of Probability ● Sports ● Weather Forecast ● Traffic Estimation Exercise: Revision time |
UNIT 4: INTRODUCTION TO GENERATIVE AI:
LEARNING OUTCOMES | SESSION / ACTIVITY / PRACTICAL |
Students will be able to define Generative AI & classify different kinds. | Recommended Activity: ● Activity: Guess the Real Image vs. the AI-generated image |
● Students will be able to explain how Generative AI works and recognize how it learns. ● Applying Generative AI tools to create content. ● Understanding the ethical considerations of using Generative AI. | Session: ● Introduction to Generative AI ● Generative AI vs Conventional AI |
Session: ● Types of Generative AI ● Examples of Generative AI | |
Session: ● Benefits of using Generative AI ● Limitations of using Generative AI | |
Recommended Activities: ● Hands-on Activity: GAN Paint ● Generative AI tools | |
Session: ● Ethical considerations of using Generative AI |
PART-C: PRACTICAL WORK
UNIT 5: INTRODUCTION TO PYTHON: Suggested Program List
UNIT 5: INTRODUCTION TO PYTHON: Suggested Program List | |
| ● To print personal information like Name, Father’s Name, Class, and School Name. ● To print the following patterns using multiple print commands- ● To find the square of the number 7 ● To find the sum of two numbers 15 and 20. ● To convert the length given in kilometres into meters. ● To print the table of 5 up to five terms. ● To calculate Simple Interest if the principle_amount = 2000 rate_of_interest = 4.5 time = 10 |
INPUT | ● To calculate the Area and Perimeter of a rectangle ● To calculate the Area of a triangle with Base and Height ● To calculate average marks of 3 subjects ● To calculate discounted amount with discount % ● To calculate the Surface Area and Volume of a Cuboid |
LIST | ● Create a list in Python of children selected for science quiz with the following names- Arjun, Sonakshi, Vikram, Sandhya, Sonal, Isha, Kartik Perform the following tasks on the list in sequence- ○ Print the whole list ○ Delete the name “Vikram” from the list ○ Add the name “Jay” at the end ○ Remove the item which is in the second position. ● Create a list num=[23,12,5,9,65,44] ○ print the length of the list ○ print the elements from second to fourth position using positive indexing ○ print the elements from position third to fifth using negative indexing ● Create a list of the first 10 even numbers, add 1 to each list item and print the final list. ● Create a list List_1=[10,20,30,40]. Add the elements [14,15,12] using the extend function. Now sort the final list in ascending order and print it. |
IF, FOR, WHILE | ● Program to check if a person can vote ● To check the grade of a student ● Input a number and check if the number is positive, negative or zero and display an appropriate message ● To print the first 10 natural numbers ● To print the first 10 even numbers ● To print odd numbers from 1 to n ● To print the sum of the first 10 natural numbers ● Program to find the sum of all numbers stored in a list |
Important Links | ●https://cbseacademic.nic.in/web_material/Curriculum21/publication/secondary/Pytho n_Content_Manual.pdf ●https://drive.google.com/drive/folders/1qRAckDculA5i164OUFDlilxb8mT65MMb |
PART-D: Project Work / Field Visit / Student Portfolio
Suggested Projects | 1. Create an AI Model using tools like- ○ Teachable Machine (https://teachablemachine.withgoogle.com/) ○ Machine Learning For Kids (https://machinelearningforkids.co.uk/) 2. Choose an issue that pertains to the objectives of sustainable development and carry out the actions listed below. ○ To understand more about the problem identified, create a 4Ws problem canvas. ○ Identify the data features and create a system map to understand the relationship between them ○ Visualize the data collected graphically (Spreadsheet software to be used to store and visualize the data) ○ Suggest an AI-enabled solution to it (Prototype/Research Work) |
Suggested Field Visit | Visit an industry or IT company or any other place that is creating or using AI applications and present the report for the same. The visit can be in physical or virtual mode. |
Suggested Student Portfolio | Maintaining a record of all AI activities and projects (For Example Letter to Futureself, Smart Home Floor Plan, Future Job Advertisement, Research Work on AI for SDGs and AI in Different Sectors, 4Ws canvas, System Map). (Minimum 5 Activities) |
Students can download the direct link for the syllabus from the link provided below. Happy Learning! For more such content, keep following Jagran Josh.
CBSE Class 9 Artificial Intelligence Latest Syllabus FREE PDF Download
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