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CBSE Artificial Intelligence for Class 9 and 10 (subject code 417): what it is and what changed in 2026-27

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In short: Artificial Intelligence, subject code 417, is one of CBSE's skill subjects for Classes 9 and 10. It is a 100-mark subject, half theory and half practical, built around the AI project cycle, data, Python and, in Class 10, computer vision and language processing. For Class 10 in 2026-27 it carries on in the same place as before: an optional skill subject with a Class 10 Board exam. For Class 9 in 2026-27 the picture has changed, because CBSE is moving Class 9 to a new scheme with compulsory Computational Thinking and AI modules. Below is what CBSE's own documents say, with links, so you can check each point.

If your child is younger, our explainer of CBSE's CT and AI curriculum for the younger classes covers the stage before this one.

What changed for 2026-27

Three CBSE documents matter here.

Two things do not line up. CBSE's skill education website still lists a 2026-27 Class 9 curriculum for subject 417. That file is dated 2 April 2026, before the circular (9 April) and the curriculum document (May 2026). And the curriculum document is not consistent with itself: its scheme table lists CT and AI modules for Class 9 in 2026-27, while its note vii says the CT and AI modules for Classes 9 to 12 come in the 2027-28 session. So if your child is entering Class 9, ask the school directly whether it is offering 417 this year or only the new CT and AI modules.

Is there an NCERT book for it? Not for subject 417 itself: its content is set by CBSE's skill curriculum above. For the new CT and AI modules, NCERT has published an introductory CT and AI module for Grades 9 to 12 (first edition, October 2026): 108 pages, five units planned for about 20 class hours, with students keeping a running "Curious Notebook" that teachers can use for assessment. It is free on NCERT's website (link under Sources).

The curriculum also says Classes 9 and 10 form one composite course, so a student should take in Class 9 only the subjects they mean to continue in Class 10.

How subject 417 is marked

Both the Class 9 and Class 10 curricula for 2026-27 give the same overall split: 100 marks, 50 theory and 50 practical, over 210 hours (50 hours of employability skills and 160 hours of AI).

PartWhat it isMarks
A. Employability SkillsCommunication, self-management, ICT, entrepreneurial and green skills (five units, 50 hours)10
B. Subject Specific SkillsThe AI units (160 hours of theory and practical)40
C and D. Practical work and projectPractical file, practical exam, viva, and a project, field visit or portfolio50

In Class 10 the 50 practical marks break down as a practical file of at least 15 programs (15), a practical exam (15), a viva (5), a project, field visit or student portfolio (10) and a viva on the project (5). In Class 9 the practical file, exam and viva add up to 35, and the project (linked to the Sustainable Development Goals) is worth 15.

The AI units, class by class

Class 9 (2026-27 curriculum):

UnitMarksTheory hoursPractical hours
1. AI Reflection, Project Cycle and Ethics103025
2. Data Literacy102228
3. Math for AI (Statistics and Probability)71213
4. Introduction to Generative AI5812
5. Introduction to Python819

Class 10 (2026-27 curriculum):

UnitMarksTheory hoursPractical hours
1. Revisiting AI Project Cycle and Ethical Frameworks for AI7114
2. Advanced Concepts of Modeling in AI11187
3. Evaluating Models10214
4. Statistical Data––28
5. Computer Vision41020
6. Natural Language Processing8207
7. Advance Python––10

Units with no theory marks are tested in the practical exam. The Class 10 practical exam covers statistical data, computer vision, natural language processing and Python; the Class 9 practical exam covers Python (input and output, variables and operators, conditions, lists).

What the course actually asks students to do

The curricula describe a hands-on course. A few examples from the Class 9 document: playing three browser games that each show one area of AI (data, language, vision), walking through the six stages of the AI project cycle, from defining the problem and collecting and exploring data to building, testing and finally deploying a model, choosing a problem and discussing its ethics, drawing graphs from data, and writing simple Python programs. The Class 10 document adds decision trees, judging how good a model is, and recognising handwriting and letters with computer vision. Both list AI bias and the Sustainable Development Goals among the learning outcomes.

The curricula also include a suggested equipment list for the school's lab, based on a batch of 20 students with two students to a computer. In practice, that means this is a subject a school has to resource, not one a student can take alone.

Should your child take it?

That depends on your child and on what the school offers, so these are questions to ask rather than a rule:

To get a feel for the ideas before choosing, a short no-device introduction such as our ten-minute explanation of AI works at any age.

Honest status

Sources