CBSE Class 9 Artificial Intelligence Syllabus 2025-26
Welcome to the Cbse Class 9 Artificial Intelligence syllabus page for the academic year 2025-26. Whether you’re a student eager to explore the exciting world of AI or a parent looking to support your child’s educational journey, you’re in the right place. Here, you’ll find the syllabus neatly organized into four comprehensive tables, each designed to guide you through different aspects of the curriculum. These tables will provide clear insights into the topics covered, learning objectives, assessment criteria, and key competencies expected throughout the course. Our aim is to make the information accessible and straightforward, ensuring you have everything you need to embark on this fascinating subject with confidence. We hope this page serves as a helpful resource for your academic planning and success.
CBSE Class 9 Artificial Intelligence Syllabus Structure
CBSE Class 9 Artificial Intelligence Units and Topics
Focus on developing foundational skills in communication, self-management, ICT, entrepreneurship, and environmental awareness, which are crucial for understanding Artificial Intelligence. Prioritize self-management and ICT skills as they contribute to your overall assessment. Key Topics: – Effective communication techniques – Goal setting and time management strategies – Basic ICT tools and their applications – Entrepreneurship fundamentals – Importance and impact of green skills
| Unit | Unit Name | No. of Hours for Theory | Max. Marks for Theory |
|---|---|---|---|
| 1 | Communication Skills-I | 10 | – |
| 2 | Self-Management Skills-I | 10 | 3 |
| 3 | ICT Skills-I | 10 | 3 |
| 4 | Entrepreneurial Skills-I | 15 | 4 |
| 5 | Green Skills-I | 05 | – |
| Total | 50 | 10 |
Class 9 Artificial Intelligence Marks Distribution
The CBSE Class 9 Artificial Intelligence syllabus focuses on foundational AI concepts, including ethical considerations, the AI project cycle, neural networks, and Python programming. These units are designed to provide students with a practical understanding of AI’s potential and its real-world applications. Key Topics: – Introduction To AI: Understand AI’s purpose and possibilities, including ethical implications. – AI Project Cycle: Learn the stages of problem scoping, data acquisition, exploration, and modeling. – Neural Network: Grasp neural network concepts through interactive activities. – Introduction To Python: Gain basic programming skills to support AI project development.
| Unit | Unit Name | Max. Marks for Theory | Unit-wise Sections |
|---|---|---|---|
| 1 | Introduction to Artificial Intelligence (AI) | 10 | ExciteRelatePurposePossibilitiesAI Ethics |
| 2 | AI Project Cycle | 15 | Problem ScopingData AcquisitionData ExplorationModelling |
| 3 | Neural Network | 5 | Understand and appreciate theconcept of Neural Networkthrough gamification. |
| 4 | Introduction to Python | 10 | Introduction to Python |
| Total | 40 |
Artificial Intelligence Syllabus Details
The CBSE Class 9 Artificial Intelligence syllabus prioritizes hands-on programming skills, focusing on Python with an emphasis on practical application. Students must complete a practical file with at least 15 Python programs, participate in a practical examination, and prepare for a viva voce. Key Topics: – Simple programs using input and output functions – Variables, Arithmetic Operators, and Expressions – Data Types – Flow of control and conditions – Lists
| Unit | Unit Name | Max. Marks for Practical |
|---|---|---|
| 4 | Introduction to PythonPractical File with minimum 15 programs | 15 |
| Practical ExaminationSimple programs using input and outputfunctionVariables, Arithmetic Operators,Expressions, Data TypesFlow of control and conditionsLists* Any 3 programs based on the above topics | 15 | |
| Viva Voice | 5 | |
| Total | 35 |
Artificial Intelligence Syllabus Details
Focus on integrating Artificial Intelligence projects with sustainable development goals, as this component carries a practical weight of 15 marks. Engage in activities that demonstrate real-world applications of AI, enhancing both technical skills and global awareness. Key Topics: – Project Work focused on AI applications – Field Visits to understand AI in different sectors – Development of a Student Portfolio showcasing AI projects and learning – Connection of AI projects to sustainable development goals
| Unit Name | Max. Marks for Practical |
|---|---|
| Project Work / Field Visit / Student Portfolio* relate it to sustainable development goals | 15 |
| Total | 15 |
❓ Frequently Asked Questions
Q1. What Is The marks distribution for the CBSE Class 9 Artificial Intelligence syllabus?
The CBSE Class 9 Artificial Intelligence syllabus is divided into practical and theory components. Typically, theory exams hold 70 marks, while practicals constitute 30 marks. It’s important to check the latest syllabus as CBSE occasionally updates the distribution.
Q2. Which chapters are most important in the Class 9 AI syllabus?
Key chapters include Introduction to AI, AI Project Cycle, and Neural Networks. These chapters provide foundational knowledge and are frequently emphasized in exams. Understanding these concepts is crucial for both theoretical exams and practical applications.
Q3. What Is the exam pattern for the Class 9 AI subject?
The exam pattern includes multiple-choice questions, short answer questions, and long answer questions. Practical exams assess your ability to apply AI concepts through projects or lab activities. Understanding the pattern helps in strategic preparation and time management during exams.
Q4. How can students effectively prepare for the AI exams in Class 9?
To prepare effectively, focus on understanding core concepts and practicing practical applications. Regularly revise chapters, take mock tests, and work on AI projects. Collaborative study sessions can also aid in grasping complex topics. Ensure to stay updated with any syllabus changes.
Q5. Are there any recommended resources for studying AI in Class 9?
Utilize the CBSE-provided textbooks and resources for foundational learning. Online platforms like Khan Academy or Coursera offer supplementary AI courses. Joining AI-focused school clubs or online forums can provide additional support and practical exposure.