CBSE Artificial Intelligence 417 for Class 9 and 10: 2026–27 Guide
CBSE Artificial Intelligence 417 is a skill subject offered in Classes 9 and 10. For the 2026–27 session, both classes carry 100 marks: 50 for theory and 50 for practical and project work. Class 9 builds the foundation; Class 10 moves into AI models, evaluation, computer vision, natural language processing and more advanced Python.
This guide follows the current CBSE curriculum—not an old coaching-site summary.
What is CBSE Artificial Intelligence subject code 417?
Artificial Intelligence 417 is CBSE's secondary-school AI subject. It is designed to help students understand how AI works, where it is used, how data shapes its decisions and how to build simple projects responsibly.
The course is not only about definitions. CBSE explicitly includes games, activities, data work, ethical discussion, Python practice and a student project or portfolio. That means the best preparation combines three things:
- clear concepts;
- hands-on practice; and
- the ability to explain what you built and why.
Class 9 vs Class 10 AI 417 syllabus
| Class 9 foundation | Class 10 progression |
|---|---|
| AI reflection, project cycle and ethics | Revisiting the project cycle and ethical frameworks |
| Data literacy | Advanced AI modelling |
| Mathematics for AI: statistics and probability | Model evaluation: accuracy, precision, recall and F1 score |
| Introduction to generative AI | Statistical data and no-code AI workflows |
| Introductory Python | Computer vision |
| Practical file and an AI-for-SDG project | Natural language processing and advanced Python |
What students learn in Class 9
Class 9 begins with the AI project cycle: problem scoping, data acquisition, data exploration, modelling, evaluation and deployment. Students also examine bias, access and the ethical questions around an AI solution.
The data-literacy unit develops the habit of asking useful questions about data: What features matter? Where did the data come from? Is it reliable? What kind of graph communicates it honestly?
Mathematics for AI introduces the role of statistics and probability. Generative AI is covered at an introductory level, including what it creates and why its output must be evaluated. Python starts with fundamentals such as input and output, variables, operators, conditions, loops and lists.
For 2026–27, CBSE lists a minimum of 15 Python programs in the practical file. Project work is intended to connect AI with a Sustainable Development Goal or a real social problem.
What students learn in Class 10
Class 10 goes deeper. Students compare rule-based and learning-based systems, then study supervised, unsupervised and reinforcement learning. They encounter classification, regression, clustering, neural networks and convolutional neural networks.
Model evaluation matters just as much as model building. Students learn why a high accuracy number is not always enough and work with the confusion matrix, precision, recall and F1 score.
The curriculum then applies those ideas to three domains:
- statistical data, including no-code tools and data exploration;
- computer vision, including pixels, image features, object detection, segmentation and convolution; and
- natural language processing, including text normalisation, bag of words, TF-IDF, chatbots and sentiment analysis.
Advanced Python is assessed through practical work. The Class 10 curriculum again requires a practical file with at least 15 programs, together with practical examination, viva and project, field-visit or portfolio work.
A practical study plan for AI 417
1. Start from the official unit list
Print or save the current CBSE curriculum. Turn every unit and sub-unit into a checklist. This prevents an old video playlist or guidebook from quietly deciding what you study.
2. Learn every concept in three forms
For each idea, aim to:
- define it in plain language;
- recognise it in a real example; and
- use it in a small activity, calculation or program.
For example, do not stop at defining classification. Identify the labels and features in a familiar problem, build or inspect a tiny classifier, then explain a case where its prediction could be wrong.
3. Maintain the practical file throughout the year
Do not leave Python programs and screenshots until the final week. After every practical, record the aim, logic, program or workflow, result and one thing you learned. A clean file also makes viva preparation much easier.
4. Treat the project as evidence of thinking
A strong AI project begins with a specific problem—not a flashy tool. Identify the people affected, the data needed, possible bias, how success will be measured and what the AI should not be allowed to decide.
5. Practise explaining results
Students often memorise terms but struggle when asked, “Why did the model make that mistake?” Practise reading graphs, comparing metrics and describing limitations. Those explanations show real understanding.
6. Revise with retrieval, not rereading
Close the notes and answer questions from memory. Draw the AI project cycle. Rebuild a confusion matrix. Predict a program's output before running it. Short, frequent retrieval sessions are more useful than repeatedly highlighting the same page.
Common mistakes to avoid
- Studying the Class 9 and Class 10 syllabi as if they are identical.
- Using material from an older academic session without checking changes.
- Memorising Python programs without understanding variables and control flow.
- Treating practical-only units as unimportant.
- Building a project without documenting the problem, data, ethics and evaluation.
- Confusing subject code 417 for Classes 9–10 with AI 843 for senior secondary classes.
Frequently asked questions
Is coding compulsory in CBSE AI 417?
Python practical work is part of the curriculum. Class 9 introduces the basics, while Class 10 uses Python and AI tools in more advanced practical tasks.
Is AI 417 a theory or practical subject?
It is both. In 2026–27 the total is 100 marks, divided into 50 theory and 50 practical and project work for each class.
Which AI domains are taught?
The curriculum repeatedly uses data, computer vision and natural language processing. Class 10 studies computer vision and NLP in greater detail.
Where should I check the latest syllabus?
Use CBSE Academic's current curriculum pages. The two primary documents for this guide are the Class 9 AI 417 curriculum and the Class 10 AI 417 curriculum.
Learn AI by doing it
Learnijoy School turns AI ideas into short explanations, interactive simulations, quizzes and guided practice. Students can experiment with models instead of only memorising their definitions. Explore Learnijoy School.
Learnijoy is an independent learning platform and is not affiliated with or endorsed by CBSE.