CBSE Class 10 · Artificial Intelligence, code 417 · Notes in Hinglish 2026-27

Class 10 AI notes in Hindi: every examined 417 unit in simple Hinglish, with the English terms intact.

These class 10 AI notes in Hindi explain the CBSE 417 units for 2026-27 in Hinglish, the way many students actually think about a topic, while every technical term stays in English, in bold, exactly as it appears in the paper. Read the meaning in Hindi, then learn the English word you will write. In our Monday and Wednesday batch the same units are taught, tested and revised against the marking scheme.

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Courses that go with these notes

The 417 board course where these units are taught live, the Python course for the practical-only Advance Python unit, and the Orange course for the no-code tool used in Statistical Data and the case studies.

CBSE Computational Thinking and AI for Teens course thumbnail

The batch / 417 Class 10

CBSE AI for Class 9 to 12

Every 417 unit taught in order, with the exam terms drilled until they come out right in a written answer, and the practical file built alongside.

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Python for Teens course thumbnail

Unit 7 / Python

Python for Teens

Lists, NumPy, Matplotlib and CSV files, the programs behind the practical exam, explained step by step for a student meeting code for the first time.

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Visual Machine Learning with Orange for Teens course thumbnail

Unit 4 / Orange

Visual ML with Orange

Hands-on with the no-code tool named for the Statistical Data unit and the coral bleaching and sentiment analysis case studies.

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Ans. The short version

Class 10 AI notes in Hindi ke liye 2026-27 ka CBSE 417 syllabus follow karein: Part A (Employability Skills, 10 marks), phir Part B ke theory units: Unit 1 AI Project Cycle and Ethical Frameworks (7), Unit 2 Advanced Concepts of Modeling (11), Unit 3 Evaluating Models (10), Unit 5 Computer Vision (4) aur Unit 6 Natural Language Processing (8). Unit 4 Statistical Data aur Unit 7 Advance Python sirf practical mein aate hain. Samjho Hinglish mein, par paper mein English terms hi likho. Modern Age Coders 417 live padhata hai, Monday aur Wednesday 9:00 PM IST, ya personalised one to one.

Q1. Ye notes kaise use karein?

Class 10 AI notes in Hindi: pehle samjho, phir English term yaad karo

Concept Hindi mein samajhna aasaan hai, par exam mein marks English term se milte hain. CBSE ka 2025-26 ka 417 sample paper sirf English mein hai, isliye har bold word ko waise hi yaad karo jaise yahan likha hai.

Unit (English naam, jaisa paper mein)Theory marksKaise check hota hai
Part A: Employability Skills (5 units)10Theory, har unit ke 2 marks
Unit 1: Revisiting AI Project Cycle and Ethical Frameworks for AI7Theory
Unit 2: Advanced Concepts of Modeling in AI11Theory
Unit 3: Evaluating Models10Theory, numericals ke saath
Unit 4: Statistical Data0Sirf practical
Unit 5: Computer Vision4Theory, aur kuch hissa practical mein
Unit 6: Natural Language Processing8Theory, aur case study practical mein
Unit 7: Advance Python0Sirf practical

Hinglish mein padho

Har point ka matlab apni bhasha mein pakdo. Jab idea clear ho jaata hai, toh ratna kam padta hai.

English mein likho

Answer mein Problem Scoping, Recall, Tokenisation jaise words exact likho. Examiner inhi keywords ko dhoondhta hai.

Language school se confirm karo

Board paper Hindi mein bhi chhapta hai ya nahi, aur Hindi mein answer chalega ya nahi, ye humne confirm nahi kiya hai. Apne school se poochh lo.

Yahi units English mein, ek revision sheet per unit ke format mein, CBSE Class 10 AI notes page par hain. Dono ko saath padhoge toh term aur matlab dono pakke ho jayenge.

Q2. Part A, Unit 1 aur Unit 2

Artificial intelligence kaksha 10: Part A, project cycle aur modeling ke notes

Part A ke 10 marks sabse aasaan marks hain, aur Unit 1 plus Unit 2 milkar 18 marks dete hain. Ye teen hisse theory paper ka sabse bada chunk hain.

Part A: Employability Skills, ek line mein har unit

  • Communication Skills-II: baat pahunchane ke tareeke, jaise verbal, non-verbal aur visual, aur kaun si cheez message ko rokti hai (barriers).
  • Self-Management Skills-II: stress ko sambhalna, khud ko motivate rakhna, aur SMART goals banana: Specific, Measurable, Achievable, Realistic, Time-bound.
  • ICT Skills-II: computer ka sahi istemaal aur dekhbhaal, files sambhalna, aur virus se bachav.
  • Entrepreneurial Skills-II: entrepreneur kaun hota hai, uske gun, aur business ka idea kaise shuru hota hai.
  • Green Skills-II: sustainable development, yaani aaj ki zaroorat aise poori karna ki aane wali peedhi ka hissa na chhine.

Har Part A unit ke short answers Part A employability skills page par hain.

Unit 1: AI Project Cycle aur Ethical Frameworks

  1. AI Project Cycle ke stages, isi order mein: Problem Scoping (problem ko saaf samajhna), Data Acquisition (data ikattha karna), Data Exploration (graphs se data ko samajhna), Modelling (model chunna aur banana), Evaluation (naye data par test karna), aur CBSE handbook ke hisaab se aakhri stage Deployment (model ko asli duniya mein lagana).
  2. 4Ws Problem Canvas: Who (kise problem hai, yaani stakeholders), What (problem kya hai), Where (kahan aur kab hoti hai), Why (solve karne se kya fayda hoga).
  3. AI ke teen domains: Statistical Data, Computer Vision aur Natural Language Processing.
  4. Ethical Framework ek set of rules hai jo batata hai ki AI banate waqt sahi aur galat kya hai. Do type: sector-based (ek field ke liye, jaise healthcare ke liye bioethics) aur value-based (rights-based, utility-based, virtue-based).
  5. Bioethics ke chaar principles: Respect for Autonomy (patient khud faisla le sake), Do not harm, Ensure maximum benefit for all, aur Give justice (sabke saath barabar vyavhaar).

Unit 2: Advanced Concepts of Modeling in AI

English termHinglish mein matlabEk example
AI, ML, DLAI sabse bada circle hai; ML uske andar, jahan machine data se seekhti hai; DL, ML ke andar, jo neural networks use karta haiChess khelne wala program (AI), spam filter (ML), face unlock (DL)
Rule Based ApproachInsaan rules likhta hai, machine bas follow karti hai; naya case aaye toh rule dobara likhna padta hai"Agar temperature 40 se upar, toh alert bhejo" wala program
Learning Based ApproachMachine khud data se pattern seekhti haiPhotos dekh kar billi aur kutte mein farq seekhna
Supervised LearningData par label laga hota hai, yaani sahi jawab pehle se pata hota haiClassification (category batana) aur Regression (number batana)
Unsupervised LearningLabel nahi hota, machine khud groups ya rishte dhoondhti haiClustering (milte-julte groups) aur Association (saath mein khareedi jaane wali cheezein)
Reinforcement LearningSahi kaam par reward, galat par penalty; machine trial and error se seekhti haiGame khelna seekhta hua agent
ANN aur CNNANN: insaani dimaag jaise neurons ka network. CNN: images ke liye khaas network jo chhote filters chalata haiHandwriting pehchanna (CNN)

Neural Network ki teen layers hoti hain: Input Layer (data andar aata hai), Hidden Layers (calculation hoti hai) aur Output Layer (result bahar aata hai). Ek neuron har input ko uske weight se guna karta hai, sab jodta hai, aur bias add karta hai. Jaise inputs 1 aur 1, weights 0.5 aur 0.3, bias -0.6: weighted sum = 0.5 + 0.3 - 0.6 = 0.2. Is unit ke aur sawaal advanced modeling questions page par hain.

Q3. Unit 3: Evaluating Models

AI class 10 Hindi medium students ke liye: Evaluating Models ke formulas aur ek solved numerical

Evaluation ka matlab hai model ko aise data par test karna jo usne pehle kabhi nahi dekha, taaki pata chale woh kitna sahi hai. Is unit ke 10 marks mein numericals zaroor aate hain, isliye formulas pakke karo.

Zaroori terms

  • Train-test split: data ke do hisse. Ek se model seekhta hai (training data), doosre se test hota hai (testing data). Same data par test karoge toh score jhootha achha aayega, kyunki model ne ratt liya hoga (overfitting).
  • Confusion Matrix: 2 x 2 table jo prediction ko reality se milati hai.
  • True Positive (TP): model ne Yes kaha, sach mein Yes. True Negative (TN): model ne No kaha, sach mein No.
  • False Positive (FP): model ne Yes kaha, par sach mein No. False Negative (FN): model ne No kaha, par sach mein Yes.
  • Ethical concerns: Bias (data ek group ki taraf jhuka ho), Transparency (model ka faisla samjhaya ja sake), Accuracy (galat score par bharosa na karein).

Formulas, ek jagah

Accuracy(TP + TN) / total
Error1 - Accuracy
PrecisionTP / (TP + FP)
RecallTP / (TP + FN)
F1 Score2 x P x R / (P + R)
Solved numericalUnit 3
Ek model 100 emails check karta hai.
Spam = Positive.

              Reality: Yes  Reality: No
Predicted Yes   TP = 36      FP = 4
Predicted No    FN = 12      TN = 48

Accuracy  = (36 + 48) / 100 = 0.84
Error     = 1 - 0.84        = 0.16
Precision = 36 / (36 + 4)   = 0.90
Recall    = 36 / (36 + 12)  = 0.75
F1 = 2 x 0.90 x 0.75 / (0.90 + 0.75)
   = 1.35 / 1.65 = 0.82 (2 d.p.)
Galat predictions = FP + FN = 16

Dhyan do: F1 ko (0.90 + 0.75) / 2 = 0.825 se mat nikaalna. Average galat tareeka hai. Saari values python3 se dobara check ki gayi hain.

Kaun sa metric kab?

  • Recall tab zaroori jab FN mehnga ho: bimaari ka test, jahan beemar ko "healthy" bolna khatarnak hai.
  • Precision tab zaroori jab FP mehnga ho: spam filter, jahan zaroori email spam mein chali jaaye toh nuksaan.
  • Dono zaroori hon toh F1 Score dekho.

Aise aur numericals, ek mark se chaar mark tak, confusion matrix numericals page par hain, aur saare formulas ek page par Class 10 AI formula sheet mein.

Q4. Unit 5 aur Unit 6

AI class 10 Hinglish notes: Computer Vision aur Natural Language Processing

Computer Vision machine ko images aur videos "dekhna" sikhata hai; Natural Language Processing use insaani bhasha samajhna sikhata hai. Dono milkar 12 theory marks hain.

Unit 5: Computer Vision (4 marks)

  • CV Tasks: Image Classification (poori image ki ek category), Classification + Localisation (category aur uski jagah par box), Object Detection (kai objects, sabke box), Instance Segmentation (har object ki exact outline, pixel tak).
  • Pixel: image ka sabse chhota hissa, ek chhota rang ka dabba.
  • Resolution: width x height pixels. 100 x 50 image mein 5,000 pixels.
  • Pixel value: 0 se 255 tak. 0 matlab kaala, 255 matlab safed. 256 values kyunki ek byte mein 8 bits hain aur 2 ki power 8 = 256.
  • Grayscale vs RGB: grayscale mein har pixel ki ek value; RGB mein teen (Red, Green, Blue). Isliye 100 x 50 ki RGB image 15,000 values rakhti hai.
  • Applications: face unlock, self-driving cars, medical imaging, retail mein shelf check.

Convolution, kernel aur CNN ki layers curriculum mein practical wale table mein rakhe gaye hain, Teachable Machine aur Orange ke saath. Unit 2 mein CNN ka naam theory mein bhi aata hai.

Unit 6: Natural Language Processing (8 marks)

  • Applications: voice assistants, auto generated captions, language translation, sentiment analysis (review positive hai ya negative), text classification, keyword extraction.
  • Stages of NLP: Lexical Analysis (words pehchanna), Syntactic Analysis ya Parsing (grammar check), Semantic Analysis (matlab banta hai ya nahi), Discourse Integration (pichhle sentence se jodna), Pragmatic Analysis (asli duniya mein kya matlab hai).
  • Script-bot vs Smart-bot: script-bot fixed script par chalta hai, jaise customer care ka menu; smart-bot data se seekhta hai aur khule sawaal samajh leta hai.
  • Text Normalisation: sentence segmentation, tokenisation (sentence ko words aur punctuation mein todna), stop words hatana (the, is, and), sab ko lowercase karna, phir stemming (ending kaatna, non-word bhi ban sakta hai) ya lemmatisation (sahi dictionary word milta hai).
  • Bag of Words: har document mein har word kitni baar aaya, uski ginti. TFIDF batata hai ki koi word ek document ke liye kitna khaas hai.
Bag of Words, solvedUnit 6
Doc 1: AI helps farmers
Doc 2: AI helps doctors and farmers

Vocabulary: [ai, helps, farmers, doctors, and]
Doc 1 vector: [1, 1, 1, 0, 0]
Doc 2 vector: [1, 1, 1, 1, 1]

Pehle lowercase karo, phir vocabulary ke order mein ginti likho.

IDF, solvedN = 2 documents
IDF = log(N / documents jismein word hai)

"doctors": log10(2 / 1) = 0.301
"ai":      log10(2 / 2) = log 1 = 0

Jo word har document mein hai, uska IDF zero: woh documents mein farq nahi batata.

NLP ke aur solved examples Bag of Words and TFIDF page par hain.

Q5. Unit 4, Unit 7 aur practical

Statistical Data aur Advance Python: sirf practical wale units ke short notes

Unit 4 aur Unit 7 se theory paper mein koi sawaal nahi aata, lekin practical ke 50 marks mein inka bada hissa hai: practical file, practical exam aur viva.

Unit 4: Statistical Data

  • No-Code AI: bina code likhe AI model banana, drag and drop se. Low-Code mein thoda code lagta hai.
  • Orange Data Mining: CBSE ka chuna hua no-code tool. Palmer Penguins case study mein species predict karna.
  • Mean, median, mode: average, beech wali value (sort karke), aur sabse zyada baar aane wali value.

Unit 7: Advance Python

  • Jupyter Notebook mein code cell by cell chalta hai.
  • NumPy (numbers aur mean, median), Matplotlib (line chart, scatter chart), CSV file padhna.
  • CBSE ke 8 suggested programs mein lists jodna, charts banana, CSV padhna aur image padhna shaamil hain. Practical file mein kam se kam 15 programs chahiye.
Practical (Part C)Marks
Practical File, kam se kam 15 programs15
Practical Examination (Units 4, 5, 6, 7)15
Viva Voce5
Project Work, Field Visit ya Student Portfolio10
Project ka Viva5
Total50

Programs ka code aur unka output Python for CBSE Class 10 AI page par likha hai.

Q6. Notes ke baad kya?

Notes padhne ke baad: live class mein ye units kaise pakke hote hain

Notes se concept samajh aata hai; marks tab aate hain jab wahi concept time ke andar, sahi English terms ke saath, likha jaaye. Hamari Monday aur Wednesday 9:00 PM IST batch mein yahi practice hoti hai.

Term se answer tak

Har unit ke baad chhota timed test hota hai. Answer screen par marking scheme ke saath check hota hai, aur jo keyword chhoot gaya woh wahin dikh jaata hai.

Numericals baar baar

Confusion matrix, pixel count aur Bag of Words ke sawaal naye numbers ke saath tab tak dohraye jaate hain jab tak galti band na ho.

Viva aur mock papers

Viva ke sawaal teacher bolkar poochhte hain. December se poore mock papers, aur har class mein doubt time, jahan koi bhi concept dobara samjhaya jaata hai.

Har unit ke likhne layak sawaal CBSE Class 10 AI important questions page par hain.

Batch or personalised: you choose

Learn these units live in the batch, or one to one

The same 417 syllabus and teachers in both formats. The batch suits a student who wants a fixed weekly routine; one to one suits a student who needs more time on certain units or on writing answers in the exam's English terms. Monthly billing, no admission fee.

Option 1 · Fixed batch timings

Group batch, Monday and Wednesday 9 PM

₹1,499

per month, two live classes a week

  • Monday and Wednesday, 9:00 PM IST, live on video
  • A Class 10 AI group of fifteen to twenty
  • Every theory unit taught, then tested on time
  • Answers checked against the marking scheme
  • Mock papers and viva practice from December
Book a free demo in this batch

Option 2 · Choose your own timing

Personalised one to one

₹4,999

per month, one private class a week, at a time set with you

  • Class days and times chosen by the family
  • Slow, careful work on the units your child finds hardest
  • Practice turning an understood idea into a written answer
  • Numericals repeated with fresh figures
  • Same CBSE 417 syllabus and teachers
Ask for a personalised plan

A student who understands the ideas but loses marks in writing often gains most from a few one to one sessions on answer-writing. A student starting the units fresh usually does better in the batch, where the whole syllabus runs in order. Fees are shown in your own currency.

Studying outside India?

Class 10 AI notes and classes for CBSE students abroad

Many Hindi-speaking families study at CBSE schools in the Gulf and Nepal, where the same 417 paper is set. Here is the local time of the 9:00 PM IST batch.

Where you liveMon and Wed 9:00 PM ISTBest format
India (IST)
every Indian city		9:00 PMBatch fits
UAE and Oman
Dubai, Abu Dhabi, Sharjah, Muscat		7:30 PMBatch fits
Saudi Arabia, Qatar, Kuwait, Bahrain
Riyadh, Jeddah, Dammam, Doha, Kuwait City, Manama		6:30 PMBatch fits
Nepal
Kathmandu		9:15 PMBatch fits
Ethiopia and East Africa
Addis Ababa and East Africa Time		6:30 PMBatch fits
Singapore and Malaysia
Singapore, Kuala Lumpur		11:30 PMChoose 1-on-1

If the batch hour does not suit your evening, one to one can run earlier. Families outside India can read more on Class 10 AI online classes for the Gulf and abroad.

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The rest of the Class 10 series

More pages for Class 10 board students

Every page in the CBSE Class 10 AI (417) series, grouped by what you need: classes, each unit, question practice, notes and revision, and the exam itself.

Classes, tuition and batches

Unit by unit

Questions and practice

Notes and revision

Exam, marks and practicals

Choosing the subject

ICSE Class 10 Computer Applications (Java): The Tue and Wed ICSE Java batch ICSE Computer Applications syllabus ICSE Java programs practice ICSE CA important questions

Questions about Class 10 AI notes in Hindi

What students ask about class 10 AI notes in Hindi

Where can I find class 10 AI notes in Hindi?

This page gives unit-wise notes for CBSE Class 10 AI (417), 2026-27, in Hinglish: Hindi written in Roman script, with every technical term kept in English. It covers Part A, the five theory units with their marks, the two practical-only units and solved numericals for confusion matrix, Bag of Words and IDF.

Is there a Hindi medium book for AI class 10?

When we checked the CBSE skill education site on 6 November 2026, we found the Class 10 AI facilitator handbook in English only, and the 2025-26 sample paper for 417 is also English only. Some publishers and teachers offer Hindi explanations, but always learn the English terms, because those are what the paper uses.

Can I write the AI 417 board exam in Hindi?

We have not been able to confirm this from a CBSE document, so ask your school. Even where Hindi answers are allowed, technical terms such as precision, recall, tokenisation and pixel should be written exactly as they are in English, since they have no standard Hindi equivalents in the curriculum.

Which units of artificial intelligence kaksha 10 come in the theory paper?

Part A Employability Skills (10 marks), Unit 1 AI Project Cycle and Ethical Frameworks (7), Unit 2 Advanced Concepts of Modeling (11), Unit 3 Evaluating Models (10), Unit 5 Computer Vision (4) and Unit 6 Natural Language Processing (8). Unit 4 Statistical Data and Unit 7 Advance Python are assessed only in the practical.

What are the stages of the AI project cycle in Class 10?

The CBSE Class 10 handbook lists six stages in order: Problem Scoping, Data Acquisition, Data Exploration, Modelling, Evaluation and Deployment. Problem Scoping uses the 4Ws canvas: Who, What, Where and Why. Learn the stage names in English, in order, because one-mark questions often ask which stage comes next.

How do I remember precision and recall?

Both have TP on top. Precision divides by everything the model called Yes (TP + FP), so it asks how many Yes answers were right. Recall divides by everything that really was Yes (TP + FN), so it asks how many real cases were caught. For F1, use 2PR / (P + R), never the plain average.

Are AI class 10 Hinglish notes enough for the board exam?

They are enough to understand the units, but not on their own to score. You also need practice writing answers in English with the right keywords, solving numericals under time, and preparing the practical file, project and viva, which together carry 50 of the 100 marks.

Is there a PDF of these Hindi notes?

There is no separate PDF. You can print this page or save it as a PDF from your browser's print option. The numericals were rechecked with Python before publishing, so the printed copy can be used for revision as it stands.

Do your AI classes help Hindi medium students?

Our live 417 classes teach every unit, then test it with timed questions marked against the scheme, so students practise turning an idea they understand into a written answer with the correct English terms. Doubt time in every class lets a student ask for any concept to be explained again. One to one is also available.

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In the free first class your child works through one unit with a teacher: the idea first, then the English terms the paper expects, then a short question written and checked on screen. Afterwards the mentor tells you which units need the most work and whether the batch or one to one would suit your child.

Want the English version of these notes too? Read CBSE Class 10 AI notes.

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