CBSE DEPARTMENT OF SKILL EDUCATION CURRICULUM
CBSE DEPARTMENT OF SKILL EDUCATIONCURRICULUM FOR SESSION 2020-2021ARTIFICIAL INTELLIGENCE (SUB. CODE 417)CLASS – IX & XOBJECTIVES OF THE COURSE:The objective of this module/curriculum - which combines both Inspire and Acquire modules is todevelop a readiness for understanding and appreciating Artificial Intelligence and its application inour lives. This module/curriculum focuses on:1.Helping learners understand the world of Artificial Intelligence and its applications throughgames, activities and multi-sensorial learning to become AI-Ready.2.Introducing the learners to three domains of AI in an age appropriate manner.3.Allowing the learners to construct meaning of AI through interactive participation andengaging hands-on activities.4.Introducing the learners to AI Project Cycle.5.Introducing the learners to programming skills - Basic python coding language.LEARNING OUTCOMES:Learners will be able to1.Identify and appreciate Artificial Intelligence and describe its applications in daily life.2.Relate, apply and reflect on the Human-Machine Interactions to identify and interact with thethree domains of AI: Data, Computer Vision and Natural Language Processing and Undergoassessment for analysing their progress towards acquired AI-Readiness skills.3.Imagine, examine and reflect on the skills required for futuristic job opportunities.4.Unleash their imagination towards smart homes and build an interactive story around it.5.Understand the impact of Artificial Intelligence on Sustainable Development Goals to developresponsible citizenship.6.Research and develop awareness of skills required for jobs of the future.7.Gain awareness about AI bias and AI access and describe the potential ethicalconsiderations of AI.8.Develop effective communication and collaborative work skills.9.Get familiar and motivated towards Artificial Intelligence and Identify the AI Project Cycleframework.Page 1 of 15
10. Learn problem scoping and ways to set goals for an AI project and understand the iterativenature of problem scoping in the AI project cycle.11. Brainstorm on the ethical issues involved around the problem selected.12. Foresee the kind of data required and the kind of analysis to be done, identify datarequirements and find reliable sources to obtain relevant data.13. Use various types of graphs to visualise acquired data.14. Understand, create and implement the concept of Decision Trees.15. Understand and visualise computer’s ability to identify alphabets and handwritings.16. Understand and appreciate the concept of Neural Network through gamification and learnbasic programming skills through gamified platforms.17. Acquire introductory Python programming skills in a very user-friendly format.SKILLS TO BE DEVELOPED:417 – Artificial Intelligence Class IX & X - 2020-2021Page 2 of 15
SCHEME OF UNITS (SESSION 2020-2021)Total Marks: 100 (Theory-50 Practical-50)This course is a planned sequence of instructions consisting of units meant for developingemployability and vocational competencies of students of Class IX opting for skill subject along withother education subjects. The unit-wise distribution of hours and marks for class IX is as follows:ARTIFICIAL INTELLIGENCE (417)Class IX (Session 2020-21)UNITSNO. OF HOURSMAX. MARKSfor Theory andPractical200for Theory andPractical100PART AEmployability SkillsUnit 1 : Communication Skills-I10Unit 2 : Self-Management Skills-I10Unit 3 : ICT Skills-I10Unit 4 : Entrepreneurial Skills-I15Unit 5 : Green Skills-I05Total50Subject Specific Skills1010MarksPART BUnit 1: Introduction to Artificial Intelligence (AI)Unit 2: AI Project Cycle40Unit 3: Neural NetworkUnit 4: Introduction to Python*(* To be assessed in Practicals only)PART DPART CTotal40Practical Work – PYTHONUnit 4: Introduction to PythonPractical Examination35Viva VoceTotal35Project Work/Field VisitPractical File/ Student Portfolio15Viva VoceTotalGRAND TOTAL417 – Artificial Intelligence Class IX & X - 2020-202115200100Page 3 of 15
ARTIFICIAL INTELLIGENCE (417)Class X (Session 2020-21)UNITSNO. OF HOURSMAX. MARKSfor Theory andPractical200for Theory andPractical100PART AEmployability SkillsUnit 1 : Communication Skills-II10Unit 2 : Self-Management Skills-II10Unit 3 : ICT Skills-II10Unit 4 : Entrepreneurial Skills-II15Unit 5 : Green Skills-II05Total50Subject Specific Skills1010MarksUnit 1: Introduction to Artificial Intelligence (AI)PART BUnit 2: AI Project CycleUnit 3: Advance Python*(*To be assessed in Practicals only)Unit 4: Data Science*(*To be assessed in Practicals only)40Unit 5: Computer Vision*(*To be assessed in Practicals only)Unit 6: Natural Language ProcessingUnit 7: EvaluationPART CTotal40Practical Work: Unit 3: Advance Python, Unit 4: Data Science Unit 5: Computer VisionPractical Examination35Viva VocePART DTotal35Project Work/Field VisitPractical File/ Student Portfolio15Viva VoceTotalGRAND TOTAL417 – Artificial Intelligence Class IX & X - 2020-202115200100Page 4 of 15
DETAILED CURRICULUM/TOPICS FOR CLASS IX:Part-A: EMPLOYABILITY SKILLSS. No.UnitsDuration in Hours1.Unit 1: Communication Skills-I102.Unit 2: Self-management Skills-I103.Unit 3: Basic Information and Communication Technology Skills-I104.Unit 4: Entrepreneurial Skills-I155.Unit 5: Green Skills-I05TOTALNOTE:50For Detailed Curriculum/ Topics to be covered under Part A: EmployabilitySkills can be downloaded from CBSE website.Part-B – SUBJECT SPECIFIC SKILLS Unit 1: Introduction to Artificial Intelligence (AI) Unit 2: AI Project Cycle Unit 3: Neural Network Unit 4: Introduction To Python (to be assessed through Practicals)UNIT 1: INTRODUCTION TO AISUB-UNITLEARNING OUTCOMESSESSION / ACTIVITY / PRACTICALExciteTo identify and appreciateArtificial Intelligence and describeits applications in daily life.Session: Introduction to AI and setting up thecontext of the curriculumIce Breaker Activity: Dream Smart Home idea Learners to design a rough layout of floor planof their dream smart home.To relate, apply and reflect on theHuman-Machine Interactions.To identify and interact with thethree domains of AI: Data,Computer Vision and NaturalLanguage Processing.Recommended Activity: The AI Game Learners to participate in three games basedon different AI domains. Game 1: Rock, Paper and Scissors (basedon data) Game 2: Mystery Animal (based on NaturalLanguage Processing - NLP) Game 3: Emoji Scavenger Hunt (based onComputer Vision - CV)Recommended Activity: AI Quiz (Paper Pen/Online Quiz)To undergo an assessment foranalysing progress towardsacquired AI-Readiness skills.417 – Artificial Intelligence Class IX & X - 2020-2021Page 5 of 15
SUB-UNITRelatePurposeLEARNING OUTCOMESSESSION / ACTIVITY / PRACTICALTo imagine, examine and reflecton the skills required for futuristicjob opportunities.Recommended Activity: To write a letterWriting a Letter to one’s future self Learners to write a letter to self-keeping thefuture in context. They will describe what theyhave learnt so far or what they would like tolearn somedayVideo Session: To watch a video Introducing the concept of Smart Cities, SmartSchools and Smart HomesRecommended Activity: Write an Interactive Story Learners to draw a floor plan of aHome/School/City and write an interactivestory around it using Story Speaker extensionin Google docs.Learners to relate to applicationof Artificial Intelligence in theirdaily lives.To unleash their imaginationtowards smart homes and buildan interactive story around it.To relate, apply and reflect on theHuman-Machine Interactions.To understand the impact ofArtificial Intelligence onSustainable Development Goalsto develop responsiblecitizenship.Possibilities To research and developawareness of skills required forjobs of the future.To imagine, examine and reflecton the skills required for thefuturistic opportunities.To develop effectivecommunication and collaborativework skills.AI EthicsTo understand and reflect on theethical issues around AI.To gain awareness around AIbias and AI access.417 – Artificial Intelligence Class IX & X - 2020-2021Session: Introduction to UN Sustainable DevelopmentGoalsRecommended Activity: Go Goals Board Game Learners to answer questions on SustainableDevelopment GoalsSession: Theme-based research and CaseStudies Learners will listen to various case-studies ofinspiring start-ups, companies or communitieswhere AI has been involved in real-life. Learners will be allotted a theme aroundwhich they need to search for present AItrends and have to visualise the future of AI inand around their respective theme.Recommended Activity: Job Ad Creating activity Learners to create a job advertisement for afirm describing the nature of job available andthe skill-set required for it 10 years down theline. They need to figure out how AI is goingto transform the nature of jobs and create theAd accordingly.Video Session: Discussing about AI EthicsRecommended Activity: Ethics Awareness Students play the role of major stakeholdersand they have to decide what is ethical andwhat is not for a given scenario.Session: AI Bias and AI Access Discussing about the possible bias in datacollection Discussing about the implications of AItechnologyPage 6 of 15
SUB-UNITLEARNING OUTCOMESSESSION / ACTIVITY / PRACTICALTo let the students analyse theRecommended Activity: Balloon Debateadvantages and disadvantages of Students divide in teams of 3 and 2 teams areArtificial Intelligence.given same theme. One team goes inaffirmation to AI for their section while theother one goes against it. They have to come up with their points as towhy AI is beneficial/ harmful for the society.UNIT 2: AI PROJECT CYCLE:SUB-UNITProblemScopingLEARNING OUTCOMESIdentify the AI Project Cycleframework.Learn problem scoping and waysto set goals for an AI project.Identify stakeholders involved inthe problem scoped.Brainstorm on the ethical issuesinvolved around the problemselected.Understand the iterative nature ofproblem scoping for in the AIproject cycle.Foresee the kind of data requiredand the kind of analysis to bedone.Share what the students havediscussed so far.417 – Artificial Intelligence Class IX & X - 2020-2021SESSION / ACTIVITY / PRACTICALSession: Introduction to AI Project Cycle Problem Scoping Data Acquisition Data Exploration Modelling EvaluationActivity: Brainstorm around the theme providedand set a goal for the AI project. Discuss various topics within the giventheme and select one. List down/ Draw a mind map of problemsrelated to the selected topic and choose oneproblem to be the goal for the project.Activity: To set actions around the goal. List down the stakeholders involved in theproblem. Search on the current actions taken to solvethis problem. Think around the ethics involved in the goalof your project.Activity: Data and Analysis What are the data features needed? Where can you get the data? How frequent do you have to collect thedata? What happens if you don’t have enoughdata? What kind of analysis needs to be done? How will it be validated? How does the analysis inform the action?Presentation: Presenting the goal, actions anddata.Page 7 of 15
SUB-UNITLEARNING OUTCOMESSESSION / ACTIVITY / PRACTICALDataAcquisitionIdentify data requirements andfind reliable sources to obtainrelevant data.Activity: Introduction to data and its types. Students work around the scenarios given tothem and think of ways to acquire data.DataExplorationTo understand the purpose ofData VisualisationSession: Data Visualisation Need of visualising data Ways to visualise data using various types ofgraphical tools.Recommended Activity: Let’s use GraphicalTools To decide what kind of data is required for agiven scenario and acquire the same. To select an appropriate graphical format torepresent the data acquired. Presenting the graph sketched.Session: Decision Tree To introduce basic structure of DecisionTrees to students.Recommended Activity: Decision Tree To design a Decision Tree based on thedata given.Recommended Activity: Pixel It To create an “AI Model” to classifyhandwritten letters. Students develop a model to classifyhandwritten letters by diving the alphabetsinto pixels. Pixels are then joined together to analyse apattern amongst same alphabets and todifferentiate the different ones.Use various types of graphs tovisualise acquired data.ModellingUnderstand, create and implementthe concept of Decision Trees.Understand and visualisecomputer’s ability to identifyalphabets and handwritings.UNIT 3: NEURAL NETWORK:LEARNING OUTCOMESSESSION / ACTIVITY / PRACTICALUnderstand and appreciate theconcept of Neural Networkthrough gamification.Session: Introduction to neural network Relation between the neural network and nervous system inhuman body Describing the function of neural network.Recommended Activity: Creating a Human Neural Network Students split in four teams each representing input layer (Xstudents), hidden layer 1 (Y students), hidden layer 2 (Zstudents) and output layer (1 student) respectively. Input layer gets data which is passed on to hidden layers aftersome processing. The output layer finally gets all informationand gives meaningful information as output.417 – Artificial Intelligence Class IX & X - 2020-2021Page 8 of 15
UNIT 4: INTRODUCTION TO PYTHON:NOTE: Python should be assessed through Practicals only and should not beassessed with the Theory Exam.LEARNING OUTCOMESSESSION / ACTIVITY / PRACTICALLearn basic programming skillsthrough gamified platforms.Recommended Activity: Introduction to programming using Online Gaming portals likeCode Combat.Session: Introduction to Python language Introducing python programming and its applicationsPractical: Python Basics Students go through lessons on Python Basics(Variables, Arithmetic Operators, Expressions, Data Types integer, float, strings, using print() and input() functions) Students will try some simple problem solving exercises onPython Compiler.Acquire introductory Pythonprogramming skills in a veryuser-friendly format.Practical: Python Lists Students go through lessons on Python Lists (Simpleoperations using list) Students will try some basic problem solving exercises usinglists on Python Compiler.417 – Artificial Intelligence Class IX & X - 2020-2021Page 9 of 15
DETAILED CURRICULUM/TOPICS FOR CLASS X:Part-A: EMPLOYABILITY SKILLSS. No.UnitsDuration in Hours1.Unit 1: Communication Skills-II102.Unit 2: Self-management Skills-II103.Unit 3: Basic Information and Communication Technology Skills-II104.Unit 4: Entrepreneurial Skills-II155.Unit 5: Green Skills-II05TOTALNOTE:50For Detailed Curriculum/ Topics to be covered under Part A: EmployabilitySkills can be downloaded from CBSE website.Part-B – SUBJECT SPECIFIC SKILLS Unit 1: Introduction to Artificial Intelligence (AI)Unit 2: AI Project CycleUnit 3: Advance Python (To be assessed through Practicals)Unit 4: Data Science (To be assessed through Practicals)Unit 5: Computer Vision (To be assessed through Practicals)Unit 6: Natural Language ProcessingUnit 7: EvaluationUNIT1. INTRODUCTIONTO AISUB-UNITFoundationalconcepts of AIBasics of AI: Let’sGet Started2. AI PROJECTCYCLEIntroductionSESSION/ ACTIVITY/ PRACTICALSession: What is Intelligence?Session: Decision Making. How do you make decisions? Make your choices!Session: what is Artificial Intelligence and what is not?Session: Introduction to AI and related terminologies. Introducing AI, ML & DL. Introduction to AI Domains (Data, CV & NLP)Session: Applications of AI – A look at Real-life AIimplementationsSession: AI EthicsSession: Introduction to AI Project CycleData AcquisitionSession: Understanding Problem Scoping &Sustainable Development GoalsSession: Simplifying Data AcquisitionData ExplorationSession: Visualising DataProblem Scoping417 – Artificial Intelligence Class IX & X - 2020-2021Page 10 of 15
UNITSUB-UNITModellingEvaluation3. ADVANCEPYTHONRecap(To be assessedthrough Practicals)Session: Jupyter NotebookSession: Python BasicsIntroductionSession: Introduction to Data ScienceSession: Applications of Data Science(To be assessedthrough Practicals)5. COMPUTERVISIONSession: Introduction to modelling Introduction to Rule Based & Learning BasedAI Approaches Introduction to Supervised Unsupervised &Reinforcement Learning Models Neural NetworksSession: Evaluating the idea!Session: Introduction to Python(To be assessedthrough Practicals)4. DATASCIENCESSESSION/ ACTIVITY/ PRACTICALSession: Revisiting AI Project CycleConcepts of DataSciencesSession: Python for Data SciencesK-nearestneighbour modelActivity: Personality PredictionIntroductionSession: Statistical Learning & Data VisualisationSession: Understanding K-nearest neighbour modelSession: Introduction to Computer VisionSession: Applications of CVConcepts ofComputer VisionOpenCVSession & Activity: Understanding CV Concepts Pixels How do computers see images? Image FeaturesSession: Introduction to OpenCVHands-on: Image ProcessingConvolutionOperatorConvolutionNeural Network6. NATURALLANGUAGEPROCESSINGIntroductionSession: Understanding Convolution operatorActivity: Convolution OperatorSession: Introduction to CNNSession: Understanding CNN Kernel Layers of CNNActivity: Testing CNNSession: Introduction to Natural Language ProcessingSession: NLP ApplicationsSession: Revisiting AI Project CycleChatbotsActivity: Introduction to Chatbots417 – Artificial Intelligence Class IX & X - 2020-2021Page 11 of 15
UNITSUB-UNITLanguageDifferencesConcepts ofNatural LanguageProcessing7. EVALUATIONIntroductionSESSION/ ACTIVITY/ PRACTICALSession: Human Language VS Computer LanguageHands-on: Text processing Data Processing Bag of Words TFIDF NLTKSession: Introduction to Model EvaluationConfusion MatrixSession & Activity: Confusion MatrixEvaluation ScoreCalculationSession: Understanding Accuracy, Precision, Recall &F1 ScoreActivity: Practice Evaluation* NOTE: Unit 3, 4 & 5 should be assessed through Practicals only and should not beassessed with the Theory Exam.LIST OF ITEMS/ EQUIPMENTS (MINIMUM REQUIREMENTS):This equipment/materials listed below are required to conduct effective hands-on learning sessionswhile delivering the AI curriculum to class 10 students. The list below consists of minimalconfiguration required to execute the AI curriculum for class 10 and create social impact real timesolutions/ projects. The quantities mentioned here are recommended for a batch of 20 studentskeeping the human-machine ratio as 2:1. An exhaustive list may be compiled by the teacher(s)teaching the subject.S. NO.AITEM NAME, DESCRIPTION & SPECIFICATION2SYSTEM SPECIFICATIONSProcessor: Intel Core i5-7300U Processor or equivalent with minimum SYSmark 2018 Rating of 750 or higherGraphic Card: Integrated graphics3Form Factor: - USFF (Ultra Small Form factor) System chassis volume less than One Litre4RAM: 8GB DDR4 – 2400MHz or above5Storage: 500 GB HDD – 7200 rpm6Display: 18.5” LED Monitor with HDMI, in-built-speaker,7Keyboard: Keyboard with numerical keypad (recommended)8Mouse: Optical Mouse9Webcam: Full HD Camera10Headphones with Mic11Dual Band Wireless Connectivity Min 800 Mbps12Bluetooth V4.2 or HigherPorts: 4 USB 3.0 ports, dual high-definition display ports (HDMI 2.0/DP/thunderbolt 3.0ports), High definition 8-channel audio through HDMI interface or through audio jack.VPU: - Integrated or support for VPU - vision processing unit to accelerate AI machinevision applications.11314417 – Artificial Intelligence Class IX & X - 2020-2021Page 12 of 15
S. NO.ITEM NAME, DESCRIPTION & SPECIFICATIONBSOFTWARE SPECIFICATIONS1Operating System: Any2Anti-Virus Activated3Internet Browser: Google Chrome4Productivity Suite: Any (Google Suite recommended)5Anaconda Navigator Distribution (https://bit.ly/AI-installation-guide)6Conceptual installations (https://bit.ly/AI-installation-guide)7Intel OpenVINO tools8PythonNOTE: In keeping with the spirit of Recycle, Upcycle and Reuse, it is recommended to make use ofany equipment/ devices/ accessories from the existing invento
Identify and appreciate Artificial Intelligence and describe its applications in daily life. 2. Relate, apply and reflect on the Human-Machine Interactions to identify and interact with the three domains of AI: Data, Computer Vision and Natural Language Processing and Undergo .
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All Head(s)/ In-Charge(s), Centre of Excellence, CBSE 18. In charge IT Unit with the request to put this Circular on the CBSE Academic Website 19. In-Charge, Library 20. The Head (Media & Public Relations), CBSE 21. DS to Chairman, CBSE 22. SPS to Secretary, CBSE 23. SPS to Director (Academics), CBSE 24. SPS to Director (Information Technology .
The Commissioner, Kendriya Vidyalaya Sangathan, 18-Institutional Area, Shaheed Jeet . Centre of Excellence, CBSE 16. In charge IT Unit with the request to put this circular on the CBSE Academic website 17. In-Charge, Library 18. The Head (Media & Public Relations), CBSE 19. DS to Chairman, CBSE 20. SPS to Secretary, CBSE 21. SPS to Director .
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1. The Commissioner, Kendriya Vidyalaya Sangathan, 18 Institutional Area, Shaheed Jeet Singh Marg, New Delhi-16 . Centre of Excellence, CBSE 17. Incharge IT Unit with the request to put this circular on the CBSE Academic Website 18. In-Charge, Library 19. The Head (Media & Public Relations), CBSE 20. DS to Chairman, CBSE 21. SPS to Secretary .
1. The Commissioner, Kendriya Vidyalaya Sangathan, 18-Institutional Area, Shaheed Jeet Singh Marg, New Delhi-16 . Centre of Excellence, CBSE 16. In charge IT Unit with the request to put this circular on the CBSE Academic website 17. In-Charge, Library 18. The Head (Media & Public Relations), CBSE 19. DS to Chairman, CBSE 20. SPS to Secretary .
