CBSE Class 09 Artificial Intelligence 2025 Syllabus

Artificial Intelligence (AI) is an overarching discipline that covers a broad range of domains and applications, and is expected to impact every field in the coming future. This curriculum focuses on building AI readiness in young minds.

Part B: Subject Specific Skills

Unit Name Marks
1 AI Reflection, Project Cycle and Ethics 10
2 Data Literacy 10
3 Math for AI (Statistics & Probability) 7
4 Introduction to Generative AI 5
5 Introduction to Python 8
  Total 40

Unit 1: AI Reflection, Project Cycle and Ethics

AI Reflection

  • To identify and appreciate Artificial Intelligence and describe its applications in daily life.
  • To recognize, engage and relate with the three realms of AI: Computer Vision, Data Statistics and Natural Language Processing.

AI Project Cycle

  • 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.
  • Identify data requirements and find reliable sources to obtain relevant data.
  • To understand the purpose of Data Visualisation.
  • Use various types of graphs to visualise acquired data.
  • Understand modeling (Rule-based & Learning-based)
  • Understand various evaluation techniques.
  • 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.
  • 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: Data Literacy

Basics of data literacy

  • Define data literacy and recognize its importance Understand how data literacy enables informed decisionmaking 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

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.

Project Interactive Data Dashboard & Presentation

  • Recognize the importance of data visualization
  • Discover different methods of data visualization

Unit 3: Math for AI

Importance of Math for AI

  • Analyzing the data in the form of numbers/images and find the relation/pattern between the them.
  • Use of Math in AI.
  • Number Patterns, Picture Analogy

Statistics

  • Understand the concept of Statistics in real life.
  • Application in various real life scenarios.

Probability

  • Understand the concept of Probability in real life and explore various types of events.
  • Application in various real life scenarios.

Unit 4: Introduction to Generative AI

  • Define Generative AI & classify different kinds.
  • 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.

Unit 5: Introduction to Python

  • Learn basic programming skills through gamified platforms.
  • Acquire introductory Python programming skills in a very user-friendly format.