Hours per year
100
40 hrs CT + 20 hrs AI + 40 hrs project work
CBSE AI Curriculum 2026–27
Class 7 AI — what your 12-year-old will learn.
Class 7 turns students into AI architects. They learn to see AI as part of larger systems, write their first Python in Colab, understand how Large Language Models actually work, and ship a complete AI project — from problem discovery and field interviews through user testing and a final showcase.
Pedagogy
Systems thinking, Python, and shipping a real AI project end-to-end.
Assessment
Project-driven. The capstone — discovery, prototype, build, test, iterate, document, present — is the primary assessment.
The four strands of Class 7 AI
CBSE organises each grade's AI curriculum into four strands. Here are Class 7's.
Strand A
Systems Thinking
Strand B
Python for AI
Strand C
NLP, Vision, and LLMs Deep-Dive
Strand D
The Architect's Capstone
What your child will learn
- ✓ Systems thinking and second-order effects
- ✓ Python basics, pandas, matplotlib, scikit-learn
- ✓ How Large Language Models work — and why they hallucinate
- ✓ Computer vision, embeddings, RAG, and multimodal AI
- ✓ Running their own end-to-end AI project — discovery to showcase
Key concepts — explained for Class 7
Each of these is a real Dhee Learning session — written for parents, mapped to the CBSE strand.
What are Large Language Models (LLMs) for kids
ChatGPT, Claude, Gemini — what's actually happening inside, explained for Class 7.
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AI is never alone — how AI lives inside a system
Every AI model sits inside a sociotechnical system of people, data and rules. Why you can't judge AI in isolation. For Class 7.
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How to map a system — actors, data and feedback loops
A system map shows every actor, data flow and feedback loop as a diagram. A core systems-thinking tool. For Class 7.
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Stakeholders in AI — who's affected, who decides?
Stakeholders are everyone an AI system touches, not just its builders. How to find them all. For Class 7.
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Unintended consequences of AI — the Cobra Effect
Why a well-meant system can cause the exact problem it was meant to fix. The Cobra Effect, for Class 7.
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First vs second-order effects — thinking ahead in AI
The direct result of a decision is only the start; second-order effects ripple further. How to anticipate them. For Class 7.
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The YouTube rabbit hole — how recommendation AI narrows what you see
How reinforcing feedback loops in recommendation systems progressively narrow content. A systems teardown for Class 7.
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Designing AI for the long term — time horizons
Short-term wins often hurt long-term system health. Why time horizon is a design choice. For Class 7.
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Goodhart's Law — when AI optimises the wrong thing
'When a measure becomes a target, it stops being a good measure.' Why AI chases the wrong goal. For Class 7.
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Algorithmic cascades — when AI errors amplify each other
When one AI's output feeds another, small errors can cascade — like the 2010 Flash Crash. For Class 7.
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Human-in-the-loop AI — keeping people in charge
Why critical AI systems keep a human as the final decision-maker, with AI only advising. For Class 7.
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How content moderation AI works — false positives and negatives
Moderation systems must balance blocking good content against allowing harm. The hard trade-off. For Class 7.
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AI loan approvals — how bias creeps into credit scoring
How AI credit systems can encode historical discrimination, and what disparate impact means. For Class 7.
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How much AI affects you every day — mapping your exposure
An urban Indian household meets 50–100 algorithmic decisions a day, mostly invisibly. Map your own. For Class 7.
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What is a function? Explained without code — for Class 7
A function is a named recipe that takes inputs and returns one output. The idea before the Python syntax. For Class 7.
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What is a loop? Explained without code — for Class 7
A loop is one action repeated many times. The plain-English idea behind every for-loop. For Class 7.
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Why learn Python for AI? A beginner's guide for Class 7
Why Python is the language of AI — and how code gives a machine precise, repeatable instructions. For Class 7.
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Python variables and types explained for Class 7
A variable is a named container for a value. How Python figures out the type for you. A beginner guide for Class 7.
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Python lists and dictionaries for beginners — Class 7
Lists store items by position; dictionaries store them by name. The two workhorses of Python. For Class 7.
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Python loops and conditionals explained for Class 7
How for-loops repeat work and if-statements make choices in Python — including why indentation matters. For Class 7.
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Python functions for beginners — def explained for Class 7
A function is reusable code that takes inputs and returns an output. How to write one with def. For Class 7.
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Reading a CSV with pandas — your first data file in Python
CSV is the most common data format, and pandas reads it in one line. The start of data science. For Class 7.
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Data visualisation with matplotlib for beginners — Class 7
A chart turns numbers into a pattern your eyes read instantly. Plotting your first graph in Python. For Class 7.
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Cleaning a messy dataset — the real work of data science
Data scientists spend 60–80% of their time cleaning data. Why messy data is normal and how to fix it. For Class 7.
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Your first machine learning model with scikit-learn — Class 7
Create → fit → predict: how scikit-learn trains your first ML model in a few lines. For Class 7.
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How to evaluate a machine learning model — accuracy isn't enough
Why accuracy can lie, and what a confusion matrix really tells you about your model. For Class 7.
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Using a pre-trained image model — transfer learning for Class 7
How a model trained on millions of images can be reused for your own task. Transfer learning, explained. For Class 7.
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How to use a language model via API — for Class 7
Send text, get a response: how to use an LLM through an API, and why tokens cost money. For Class 7.
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What is an API? The mental model every coder needs — Class 7
An API is a contract for how two programs talk. REST, GET and POST explained simply. For Class 7.
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Error messages are friends — reading Python tracebacks
An error message tells you exactly what went wrong and where. How to read a Python traceback. For Class 7.
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How to read other people's code — a real coding skill for Class 7
Developers read far more code than they write. Why reading code is its own skill, and how to get good at it. For Class 7.
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What is GitHub? A gentle tour for beginners — Class 7
GitHub is where code lives and how developers collaborate. A first tour for young coders. For Class 7.
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What are tokens? How AI reads text — for Class 7
Before a model reads text, it splits it into tokens. Why modern LLMs use sub-word pieces. For Class 7.
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What are embeddings? Words as points in space — for Class 7
Embeddings turn words into lists of numbers that capture meaning. How AI understands language. For Class 7.
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How AI understands context — why 'bank' means two things
The same word can mean different things depending on its neighbours. How AI handles ambiguity. For Class 7.
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What is sentiment analysis? Building one — for Class 7
How AI decides if text is positive, negative or neutral — one of the most-used NLP tasks. For Class 7.
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What is text classification? Building a topic classifier — Class 7
How AI sorts text into categories — one of the oldest and most useful NLP tasks. For Class 7.
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How machine translation works — and where it fails
How neural translation maps meaning across languages, and why it still stumbles. For Class 7.
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Indian language NLP — the real challenges for AI
22 scheduled languages, many scripts, little data: why Indian-language AI is genuinely hard. For Class 7.
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Next-token prediction — the truth about how LLMs work
An LLM is trained to do one thing: predict the next token. Why that simple goal, at scale, is so powerful. For Class 7.
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Why do LLMs hallucinate? The deep explanation for Class 7
Hallucination is a structural consequence of how LLMs generate text — not a simple bug. The deep version. For Class 7.
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What is RAG? Retrieval-augmented generation for Class 7
RAG combines searching real documents with generating answers, so the AI cites facts instead of guessing. For Class 7.
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Prompt engineering as software engineering — for Class 7
Good prompting is a craft with patterns, like few-shot examples. Why it's real engineering. For Class 7.
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How to evaluate LLM outputs — accuracy, safety and more
LLM answers must be judged on accuracy, relevance, coherence and safety — not just one score. For Class 7.
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How computer vision works — convolution explained intuitively
CNNs spot patterns by sliding small filters across an image. The intuition behind computer vision. For Class 7.
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Object detection vs classification — what's the difference?
Classification asks 'what is this?'; detection adds 'where is it?' with boxes. How tools like YOLO work. For Class 7.
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How AI image generation works — diffusion models for Class 7
Diffusion models build images by reversing noise, starting from static. How tools like Stable Diffusion create art. For Class 7.
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AI, training data and copyright — the big debate for Class 7
AI learns from human-made work — but is that fair use? The lawsuits and ethics, for Class 7.
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What is multimodal AI? Models that see, read and hear
Multimodal AI handles text, images, audio and video together — like GPT-4 reading a photo. For Class 7.
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How to run an AI ethics review — fairness, privacy and harm
Who benefits, who could be harmed, what data is used: the four lenses of an AI ethics review. For Class 7.
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AI data requirements — what data does your project need?
Every AI needs training data and runtime data. How to specify type, quantity and quality before you build. For Class 7.
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Choosing the right AI approach — classification, regression and more
Different problems need different AI methods. The five problem types every young builder should know. For Class 7.
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Iterating on an AI project — fixing what user testing finds
Iteration means fixing the top problems from testing and checking nothing else broke. Regression testing, for Class 7.
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How to document an AI project — telling the whole story
Good project docs cover problem, research, design, build, test and reflection — not just the result. For Class 7.
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Dhee teaches Class 7 AI the way it should be taught.
Dhee Learning doesn't hand out answers. For each Class 7 concept, Dhee asks questions, listens to your child, and probes their reasoning — exactly the spirit of the CBSE syllabus, but in 15-minute spoken sessions at home.
Common questions about Class 7 AI
What does the CBSE AI curriculum cover in Class 7? +
Class 7 turns students into AI architects. They learn to see AI as part of larger systems, write their first Python in Colab, understand how Large Language Models actually work, and ship a complete AI project — from problem discovery and field interviews through user testing and a final showcase.
How is AI taught in Class 7? +
Colab notebooks, capstone projects with real users, ethics reviews, design sprints, and rehearsals for a final showcase.
Is there an exam for AI in Class 7? +
Project-driven. The capstone — discovery, prototype, build, test, iterate, document, present — is the primary assessment.
How can my child practise CBSE AI Class 7 at home? +
Dhee Learning is an AI study buddy whose syllabus mirrors the CBSE Class 7 AI strands. Your child can work through each concept in 15-minute sessions — Dhee asks questions and listens, instead of handing out answers.