CBSE Class X · Artificial Intelligence, subject code 417 · Curriculum for session 2026-27

The CBSE Class 10 AI syllabus, decoded unit by unit, with every mark accounted for.

CBSE's Department of Skill Education publishes the Class X Artificial Intelligence curriculum as a thirteen-page document, and most families never open it. They should, because it answers the questions that decide a grade: which units carry theory marks and which are practical only, why Statistical Data has 28 hours and no theory marks, what the practical file must contain, which free tools the board itself prescribes, and what the project has to relate to. This page reads that document for you, unit by unit, and shows how a live twice-weekly batch covers all of it in a school year.

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Source: CBSE curriculum for session 2026-27, Artificial Intelligence (sub. code 417), Class X · total marks 100, theory 50 and practical 50

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The courses that teach this syllabus

One course for the paper itself, and two for students who want to go past it in the directions the syllabus opens.

CBSE Computational Thinking and AI for Teens course thumbnail

The paper / 417 Class 10 batch

CBSE AI for Class 9 to 12

Every unit on this page, taught live on Monday and Wednesday evenings in a dedicated Class 10 batch, with the practical file and project built across the year.

Open the syllabus →
Visual Machine Learning with Orange for Teens course thumbnail

The tool CBSE names / Orange

Visual Machine Learning with Orange

The no-code tool the 2026-27 curriculum prescribes for Statistical Data, Computer Vision and NLP practicals, taught as a real machine learning course.

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AI and Machine Learning for Teens course thumbnail

Beyond the paper / models

AI and ML for Teens

For the student who reads Unit 2 and Unit 3 and wants to train the models properly, in code, rather than stop at the board's depth.

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Ans. The short version

The CBSE Class 10 Artificial Intelligence syllabus for 2026-27 (code 417) is worth 100 marks: a 50-mark theory paper and a 50-mark practical. Theory is Part A, five employability skills units at two marks each, plus Part B, seven AI units of which five carry theory marks: Revisiting the AI Project Cycle and Ethical Frameworks (7), Advanced Concepts of Modeling (11), Evaluating Models (10), Computer Vision (4) and Natural Language Processing (8). Statistical Data and Advance Python are practical-only. Part C is a practical file of at least 15 programs (15), a practical examination on Units 4 to 7 (15), a viva (5), a project related to the Sustainable Development Goals (10) and a project viva (5). The board names Orange Data Mining, Teachable Machine, Lobe and Jupyter Notebook as tools. Modern Age Coders teaches all of it live, Monday and Wednesday at 9 PM IST.

Q1. Where do the hours and marks go?

The unit ledger, exactly as CBSE tabulates it

Two numbers per unit tell you how to study it: the hours CBSE allots, which say how much school will teach, and the marks, which say how much the paper cares.

UnitTheory hrsPractical hrsTheory marksWeight
Part A: five employability units (Communication, Self-Management, ICT, Entrepreneurial, Green Skills)50010
Unit 1: Revisiting AI Project Cycle and Ethical Frameworks for AI1147
Unit 2: Advanced Concepts of Modeling in AI18711
Unit 3: Evaluating Models21410
Unit 4: Statistical Data (assessed through practicals)0280
Unit 5: Computer Vision10204
Unit 6: Natural Language Processing2078
Unit 7: Advance Python (assessed through practicals)0100
Theory paper: Part A plus Part B1308050

The weight column is each unit's share of the 50 theory marks, and it tells a story most students never hear. Modeling and Evaluating Models together are 21 of the 50, more than two fifths of the paper, from two units that are almost entirely conceptual. Computer Vision gets 20 practical hours but only four theory marks, so it is a unit to do rather than to revise. And the two zero-mark units are not optional: Statistical Data and Advance Python are where the 15-mark practical examination and the 15-mark file are earned.

The grand total in the curriculum is 210 hours for 100 marks. School periods for a skill subject rarely reach that, which is the honest reason a twice-weekly batch exists: our Monday and Wednesday 9 PM classes put the theory-bearing units on Monday and the practical units on Wednesday, so nothing on this ledger is left to the last term.

Q2. What is actually inside each unit?

Seven units, read from the curriculum's own session list

CBSE writes each unit as sub-units, learning outcomes and named sessions or activities. This is what those sessions add up to, in plain language.

Unit 1 · 7 marks

Revisiting AI Project Cycle and Ethical Frameworks for AI

The project cycle from Class 9 returns, now as the spine for everything else: problem scoping, data acquisition, data exploration, modelling, evaluation, and the idea that the cycle loops. The three domains of AI, data, computer vision and natural language, are re-introduced with real applications in each. The new material is ethics: what an ethical framework is and why AI needs one, the types of frameworks, and bioethics as a worked example with a healthcare case study. This unit feeds the case-based question, where a scenario is described and the student must scope it and name its ethical risk.

Unit 2 · 11 marks

Advanced Concepts of Modeling in AI

The heaviest theory unit. It separates AI, machine learning and deep learning, then separates rule-based from learning-based models. Learning-based models split into supervised, unsupervised and reinforcement learning; supervised into classification and regression; unsupervised into clustering and association; deep learning into artificial and convolutional neural networks. The curriculum points students at Teachable Machine and Google's drum-machine experiment to feel the difference, and at the TensorFlow playground to watch a neural network learn. The examinable core is the vocabulary tree and the ability to place a described problem on it.

Unit 3 · 10 marks

Evaluating Models

Why evaluate at all, then how: the train-test split, accuracy and error, and for classification the confusion matrix with precision, recall and F1 score. CBSE lists three activities that are, in effect, the exam: build a confusion matrix from scratch, calculate a classifier's accuracy, and decide which metric fits a given problem. The closing sub-unit on bias, transparency and accuracy connects evaluation back to ethics. Students who understand why recall matters more than accuracy for a medical test score full marks here; students who memorised four formulas do not.

Unit 4 · practical only, 28 hours

Statistical Data

Deliberately no-code. The unit introduces data science and the idea of no-code and low-code AI, then works entirely in Orange Data Mining and a spreadsheet: important concepts in statistics, the AI project cycle rebuilt inside Orange, and the Palmer penguins case study for exploration, modelling and evaluation. There are no theory marks; the unit is assessed in the practical file and the practical examination, and it is the first place students discover that a model can be built by connecting blocks and still be reasoned about like any other.

Unit 5 · 4 marks plus practical, 30 hours

Computer Vision

Theory covers what computer vision is and where it is used, then the basics of images: pixels, resolution, pixel values, grayscale versus RGB, and the tasks of feature extraction, detection and segmentation. The practical side is the richest in the syllabus: Lobe and Teachable Machine for no-code image classifiers, a Smart Sorter activity, a real-world coral bleaching classification model built in Orange, the convolution operator applied to images, and the architecture of a CNN with its kernels and layers. Four theory marks undersell a unit that produces the projects students are proudest of.

Unit 6 · 8 marks plus practical

Natural Language Processing

Why human language is hard for machines, the applications students already use, voice assistants, captions, translation, sentiment analysis, keyword extraction, and the stages of NLP: lexicon, syntax, semantics, logical analysis. Chatbots are explored by playing with several, then classified as script bots or smart bots. The examinable technique is text processing: normalisation, bag of words and TF-IDF, with a hands-on. The practical is a sentiment-analysis case walkthrough in Orange on a real dataset.

Unit 7 · practical only, 10 hours

Advance Python

Short in hours and long in consequence. The recap covers working in Jupyter Notebook, creating virtual environments and installing packages; then Python fundamentals, variables, data types, operators and control structures, and the use of built-in functions and libraries. This is the unit that makes the practical file possible, because CBSE's suggested programs are all Python, and it is the unit the practical examination leans on most. Our Python for CBSE Class 10 AI page takes it program by program.

Q3. What does a full-marks answer look like?

One worked example from Unit 6: bag of words, the way the paper asks it

Text processing questions are reliable marks once a student has done the procedure by hand a few times. Here is the procedure, from two documents to a table.

Step 1 and 2normalise, then build the vocabulary
Document 1: "Aman likes to play cricket."
Document 2: "Riya likes to play football."

# Text normalisation
# lowercase, remove punctuation, tokenise
D1: aman likes to play cricket
D2: riya likes to play football

# Remove stop words (to)
D1: aman likes play cricket
D2: riya likes play football

Vocabulary (unique words, in order met):
aman  likes  play  cricket  riya  football

Marks are lost in the first two lines, not the last: a student who forgets to lowercase or to drop the stop word gets a different vocabulary and a different table.

Step 3the bag-of-words table
          aman likes play cricket riya football
Document 1   1     1    1     1      0     0
Document 2   0     1    1     0      1     1

# Each cell counts how often the word
# appears in that document.

Reading it: "likes" and "play" appear in
both documents, so they say little about
which document is which. "cricket" and
"football" appear in one each, so they
carry the meaning. That observation is
exactly what TF-IDF formalises next.

The paper can ask for the table, for the vocabulary, or for which words carry meaning. All three are the same procedure, and Monday sessions run it on fresh sentences until it is automatic.

Q4. What does the practical half consist of?

Part C, line by line: file, practical exam, two vivas and a project

Part C componentMarksShare
Practical file with a minimum of 15 programs15
Practical examination on Units 4, 5, 6 and 715
Viva voce5
Project work, field visit or student portfolio (any one)10
Viva voce related to the project5
Practical total50

CBSE's suggested programs for the file

  • Add the elements of two lists
  • Calculate mean, median and mode using NumPy
  • Display a line chart from (2,5) to (9,10)
  • Display a scatter chart for the points (2,5), (9,10), (8,3), (5,7), (6,18)
  • Read a CSV file saved on your system and display 10 rows
  • Read a CSV file and display its information
  • Read an image and display it using Python
  • Read an image and identify its shape using Python

Eight suggestions, fifteen required: the rest come from the practical sides of Units 4 to 6, and a well-built file goes past fifteen so the student has a choice of programs to explain in the viva. The project must relate to the Sustainable Development Goals; CBSE's sample is predicting Palmer penguin species from statistical data, and the strongest student projects share its shape, one dataset, one question, one model.

How the file, the project and both vivas are built across a year rather than a fortnight is on the project and practical file page; how to turn the theory ledger above into a revision plan is on board exam preparation.

Q5. What has changed around this syllabus?

Three 2026 facts every Class 10 AI family should know

Class 10 continues on 417

CBSE published the Class X AI curriculum for 2026-27 on the earlier scheme. The units, hours and 50 plus 50 marking on this page are the current ones, and a Class 10 student this session sits exactly this paper.

Class 9 has moved on

Code 417 was discontinued for Class 9 from 2026-27. Class 9 students join the new Computational Thinking and AI subject, which becomes compulsory with an annual examination from 2027-28. The concepts overlap; the paper does not.

Two board exam phases from 2026

CBSE now runs Class 10 boards as a compulsory February to March exam and an optional May improvement exam for a limited number of subjects, with the better score counting. The improvement exam is framed around the main subjects, so ask your school whether a skill subject can be re-attempted.

For the younger classes and the road to the 2027-28 change, the CBSE AI curriculum guide covers Classes 3 to 8 and what the Class 8 to Class 9 jump now means. This page stays with the Class 10 paper.

Q6. In what order should it be studied?

A school-year sequence that respects the ledger

The order below is the one our Monday and Wednesday batch follows, and it is built from the hours column: the heavy theory early, the practical file continuous, the project never last.

  1. April to June: Units 1 and 2, and the practical file begins

    The project cycle and ethics first, because they frame everything; then the modelling vocabulary tree while there is time to let it settle. Wednesdays start Advance Python immediately, so the first file programs exist before the first school test.

  2. July to September: Unit 3, Unit 4 and the project chosen

    Evaluation is the unit that rewards slow understanding, so it gets the long stretch. Orange arrives with Statistical Data and the penguins, and the project is scoped now, related to an SDG, while there are still months to build it calmly.

  3. October to November: Units 5 and 6 with their practicals

    Computer Vision and NLP back to back, theory on Mondays and Teachable Machine, Lobe, Orange and the sentiment case study on Wednesdays. The file passes fifteen programs here. Part A runs in ten-minute blocks throughout.

  4. December to January: file complete, project finished, first full mocks

    A full theory paper under time, a timed practical on an unseen question, and the project demoed with its viva questions. What breaks in December is fixable; what breaks in February is not.

  5. February: revision by marks, not by page count

    Modeling and Evaluating Models get the most revision hours because they carry 21 marks; Computer Vision theory gets a day because it carries four. Part A gets its ten questions. Then the board practical, and then the paper.

Q7. What does the batch cost?

Monthly fees, the same for every course we teach

Billed monthly, no admission fee, stop at any month end. The free demo class comes first.

Group batch · Mon and Wed 9 PM

₹1,499

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  • Ten to fifteen students, one teacher all year
  • Every unit on this page, theory and practical
  • File, project and viva rehearsal included
  • Certificate on completion
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Mini batch

₹2,999

per month

  • Four to five students
  • Other timings than the Monday and Wednesday batch
  • More attention per student on the practical units
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One to one

₹4,999

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  • Private teaching on your own schedule
  • The whole syllabus at the student's pace
  • The usual choice for a start after October
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The rest of the Class 10 series

Nine more pages for Class 10 board students

Four more on CBSE AI 417, and five on the ICSE Computer Applications paper for families on the other board.

The Mon and Wed 9 PM batch/cbse-class-10-ai-classes-online Python for Class 10 AI/python-for-cbse-class-10-ai Board exam preparation/cbse-class-10-ai-board-exam-preparation Project and practical file/cbse-class-10-ai-project-and-practical-file ICSE Class 10 Java classes/icse-class-10-java-classes-online ICSE Computer Applications syllabus/icse-class-10-computer-applications-syllabus-explained ICSE Java programs practice/icse-class-10-java-programs-practice ICSE BlueJ Java coaching/icse-class-10-bluej-java-coaching ICSE board exam preparation/icse-class-10-computer-applications-board-exam-preparation

Questions about the syllabus

What parents and students ask after reading the curriculum

Is CBSE Class 10 AI (417) the same subject as the new Computational Thinking and AI?

No. Artificial Intelligence, code 417, is the existing Class 10 skill subject and CBSE has published its 2026-27 curriculum on the earlier scheme. Computational Thinking and AI is the new curriculum for Classes 3 to 8 from 2026-27, becoming a compulsory Class 9 subject with an annual examination from 2027-28. Code 417 was discontinued for Class 9 from 2026-27 as part of that transition, but a Class 10 student this year sits 417 exactly as described on this page.

Which units carry theory marks and which are practical only?

Theory marks come from Part A, ten marks across five employability units, and from five Part B units: Revisiting AI Project Cycle and Ethical Frameworks (7), Advanced Concepts of Modeling (11), Evaluating Models (10), Computer Vision (4) and Natural Language Processing (8). Statistical Data and Advance Python are marked as to be assessed through practicals and carry no theory marks; they show up in the practical file and the practical examination instead.

Do you need Python for the theory paper?

No line of Python is examined in the theory paper. Python lives in Part C: the practical file needs at least 15 programs, the practical examination is set on Units 4 to 7, and the curriculum's own suggested programs are all Python, from NumPy statistics to reading a CSV and displaying an image. The theory paper tests concepts, so a student who understands what a model, a metric or a convolution is will score there even if their coding is still growing.

What is Orange Data Mining and does my child have to install it?

Orange is a free, open-source, no-code data science tool that CBSE names in the 2026-27 curriculum for the Statistical Data unit and for the practical sides of Computer Vision and NLP, alongside Teachable Machine and Lobe. Students build models by connecting blocks rather than by writing code. It installs free on Windows and Mac, and in our batch it is set up in the first practical session, so no family has to fight it alone.

How many programs does the practical file need, and which ones?

A minimum of 15, worth 15 marks. CBSE's suggested list includes adding the elements of two lists, mean, median and mode using NumPy, a line chart and a scatter chart from given points, reading a CSV file and displaying ten rows and its information, and reading an image to display it and identify its shape. A good file goes past the minimum so that the student has choices in the viva.

What does the project have to be about?

CBSE asks that the project, field visit or portfolio relate to the Sustainable Development Goals, and its sample projects include predicting Palmer penguin species from statistical data. In practice the strongest projects are small, real and explainable: one dataset, one question, one model built in Orange or Python, and a student who can say why the result is what it is when the viva examiner asks.

Are there any changes to the Class 10 board exam itself in 2026?

From 2026, CBSE runs Class 10 board exams in two phases: a compulsory first exam in February to March and an optional second exam in May for students wanting to improve marks in a limited number of subjects, with the better score counting. CBSE has framed the improvement exam around the main subjects, so whether a skill subject like AI can be re-attempted is a question for your school. The 417 syllabus and its 50 plus 50 marking are unchanged either way.

My child is in Class 9. Should they prepare from this syllabus?

A Class 9 student in 2026-27 is no longer on code 417, which CBSE discontinued for Class 9 this session; they move to the new Computational Thinking and AI subject, compulsory with an exam from 2027-28. The concepts overlap heavily, project cycle, data, models, evaluation, ethics, so nothing learned from this page is wasted, but the units and marks here describe the Class 10 paper specifically.

How do the Monday and Wednesday classes divide this syllabus?

Mondays carry the theory-bearing units and Part A, taught for understanding and then practised in the question shapes the paper uses. Wednesdays are the practical lab: Orange for Statistical Data and the practical halves of Computer Vision and NLP, and Jupyter for Advance Python, producing one practical-file program a week. Across the year that covers all 210 curriculum hours' worth of content at a pace a school timetable rarely manages.

What is the next step from this page?

Send the form and a mentor books a free demo class for the Monday and Wednesday batch. The demo is a real session, and it doubles as a check of where your child currently stands on the syllabus above, so you leave knowing which units need most work. No card, no enrolment fee, and a straight recommendation either way.

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The free demo doubles as a syllabus check

Bring the student, their textbook and their honest sense of which units feel shaky. The demo is a real session from the batch, and the teacher uses it to place your child against the ledger on this page: which units are already understood, which are memorised, which have not been met. You leave with a running practical program and a specific list, which is more than most families have by February.

Reading on instead? The batch page explains the Monday and Wednesday rhythm, and Python for Class 10 AI takes Unit 7 program by program.

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