Artificial Intelligence in CBSE (Class 9-12): What Students Actually Learn

What is Artificial Intelligence in CBSE?

Artificial Intelligence is one of CBSE's skill subjects. It is offered at two levels with two different subject codes, and the two are designed to flow into each other:

• Code 417 - Class 9 and Class 10 (secondary level), an introductory skill subject.
• Code 843 - Class 11 and Class 12 (senior secondary level), a deeper, project-heavy elective.

A common point of confusion for parents: AI (417/843) is not the same as Computer Science (083) or Informatics Practices (065). AI is a skill subject focused on building and evaluating AI projects, while Computer Science is the academic computing subject with heavy Python and database work. Many students take Computer Science as a main elective and AI as their additional skill subject. If you are weighing the two, our Computer Science course page and Informatics Practices page explain the differences in detail.

CBSE AI Class 9 and 10 (Code 417)

At the secondary level, the goal is awareness plus a first taste of building. Students learn to recognise where AI is and is not being used, understand the three core domains, and write basic Python.

What Class 9 covers

Part B (Subject-Specific Skills) for Class 9 is roughly 40 hours, split into four units:

• Introduction to AI - what AI is, AI vs not-AI, and where it appears in everyday apps.
• AI Project Cycle - problem scoping, data acquisition, data exploration, modelling and evaluation.
• Neural Networks - the idea of how a neural network learns, taught through games and visual tools.
• Introduction to Python - input/output, variables, operators, data types, conditions and lists.

The three domains introduced are Data Sciences, Computer Vision, and Natural Language Processing (NLP). The course is assessed across theory, practical work, and a project linked to the Sustainable Development Goals.

What Class 10 covers

Class 10 builds directly on Class 9 with seven subject units. The indicative theory marks tell you where to focus:

• Revisiting the AI Project Cycle and ethical frameworks for AI (~7 marks)
• Advanced concepts of modelling in AI (~11 marks)
• Evaluating models
• Statistical data for AI
• Computer Vision (~20 marks) - the heaviest single unit
• Natural Language Processing (~8 marks)
• Advance Python

The practical side carries real weight: a practical file of at least 15 programs (15 marks), a practical exam covering statistical data, computer vision and advance Python (15 marks), viva voce (5 marks), and project work (10 marks). In short, you cannot pass Class 10 AI on theory alone - you have to actually write and run code.

CBSE AI Class 11 and 12 (Code 843)

At senior secondary level, AI becomes a serious elective with an even 50:50 split between theory and practical.

Class 11 (843)

Class 11 lays the foundation for the capstone. Subject-specific units include an introduction to AI for everyone, careers in AI, Python programming, an introduction to the Capstone Project, Data Literacy (from data collection to analysis), Machine Learning algorithms, leveraging linguistics with computer science, and AI Ethics and Values. The total is 100 marks, split 50 theory and 50 practical.

Class 12 (843)

Class 12 is the deep end. Theory (50 marks) spans:

• Python Programming
• Data Science Methodology
• Making Machines See (computer vision)
• AI with the Orange Data Mining tool
• Introduction to Big Data and Data Analytics
• Understanding Neural Networks
• Generative AI
• Data Storytelling

The practical half (50 marks) centres on a Capstone Project - students work in teams over roughly 30 hours to define a real problem (using tools like Design Thinking and the 5W1H framework), build and evaluate a model, and document everything in a log book. Concepts like training/testing data split and cross-validation are assessed here, not just memorised.

AI vs Computer Science: which should you pick?

Both are excellent, but they serve different goals:

• Choose AI (417/843) if you want hands-on exposure to data, machine learning and real projects, and you enjoy building things end to end.
• Choose Computer Science (083) if you want deeper programming, SQL/databases, and a stronger base for engineering or a BCA/B.Tech path.

Many of our students do both. If your child is in Class 11 and leaning toward AI, our CBSE AI Class 11 course pairs well with CBSE Computer Science Class 12 the following year. You can browse the full list on the CBSE courses page.

How Kwickprep helps you with CBSE AI

AI rewards consistent, guided practice far more than last-minute cramming, because so many marks live in the practical file, project and viva. With Kajal Ma'am mentoring Computer Science students since 2006, our teaching is built around writing code, debugging it, and explaining it confidently in the viva.

Strong Python is the single biggest predictor of doing well in AI, since every domain - data, vision, NLP - runs on it. If your fundamentals are shaky, start with our focused Python course before tackling the AI domains. Students across India and abroad study with us; international families can see the international page, and you can check our verified outcomes on the results page. For class fit, schedule or any doubts, reach out via contact.

Key takeaways

• CBSE AI uses two codes: 417 for Class 9-10 and 843 for Class 11-12.
• The three core domains are Data Sciences, Computer Vision, and NLP.
• Class 10 leans heavily on Computer Vision; Class 12 is built around a team Capstone Project.
• Practical work, projects and viva carry major marks - coding practice is non-negotiable.
• AI is different from Computer Science (083); many students take both.
• Solid Python is the foundation that makes everything else easier.

Always confirm the exact unit names and marks for your batch against the official CBSE Academic curriculum PDF for the current session, as weightings are revised from time to time.