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    Part D: Project / Field Visit / Student Portfolio (15 Marks Total)

    Part D: AI Project, Field Visit & PortfolioClass 9 Artificial Intelligence (Subject Code 417)

    Apply theoretical AI skills to solve real human challenges. Build an AI Capstone model aligned with the UN Sustainable Development Goals, organize a physical or virtual industry field visit, or assemble an exemplary 5-activity student portfolio.

    SDG Aligned Problem Solving
    Teachable Machine & ML for Kids
    Total Weightage: 15 Marks

    Choose Any 1 of the 3 Options (CBSE Scheme)

    Option 1: AI Project

    Build an AI classifier with Teachable Machine, create a 4Ws canvas, system map, and spreadsheet visualization.

    Option 2: Field Visit

    Visit an industry, startup, or lab applying AI (physical or virtual mode) and present a structured case study report.

    Option 3: Student Portfolio

    Compile a documented record of at least 5 completed AI activities (Future Letter, Smart Home Floor Plan, etc.).

    Pathway Option 1

    AI Capstone Project Aligned with UN SDGs

    The CBSE curriculum mandates that student AI projects must address pressing local or global challenges defined under the 17 United Nations Sustainable Development Goals (SDGs).

    1

    4Ws Problem Canvas

    Define Who, What, Where, and Why clearly for your community problem.

    2

    System Map

    Map relationships and feedback loops between identified data features.

    3

    Data Visualization

    Store collected metrics in spreadsheets and generate comparative charts.

    4

    AI Model Prototype

    Train an image, audio, or pose model using Teachable Machine or ML for Kids.

    Curriculum Recommended SDG Project Ideas:

    SDG 3: Good Health & Well-BeingTeachable Machine (Pose Model)

    Postural Correction & Ergonomics Coach

    Train a computer vision model on webcam pose feeds to detect slouching and improper ergonomic posture during online study sessions, alerting students to sit upright.

    SDG 11: Sustainable Cities & CommunitiesTeachable Machine (Image Model)

    Automated Waste Sorting Assistant

    Train an image recognition classifier to identify recyclable plastics, paper, and biodegradable organic waste, simulating automated smart recycling bins.

    SDG 12: Responsible Consumption & ProductionMachine Learning for Kids

    Crop Disease Spotter for Cotton Farming

    Inspired by the CottonAce case study, build an AI prototype that recognizes pink bollworm leaf damage patterns to guide farmers on pesticide optimization.

    SDG 13: Climate ActionSpreadsheets + Tableau Public

    Carbon Footprint & Commute Analyzer

    Collect neighborhood transportation data, construct system maps of vehicular emissions, and forecast emission reduction via school bus pooling.

    Pathway Option 2

    AI Industry Field Visit & Virtual Tour Report

    Students can fulfill Part D by visiting an IT enterprise, robotics center, data lab, or automated logistics hub in either physical or virtual mode, compiling an analytical report covering:

    1. Problem & Domain

    What business problem does the organization solve? Which AI domain (Computer Vision, NLP, Data) is employed?

    2. Data Pipeline

    How does the company collect, clean, and protect user data? What security and cyber hygiene protocols are enforced?

    3. Societal Impact

    What positive impact does the AI produce? How are potential ethical dilemmas, worker safety, and bias managed?

    Pathway Option 3

    Student AI Portfolio (Minimum 5 Activities)

    If selecting the portfolio pathway, students maintain a neatly bound or digital compilation of at least 5 hands-on class activities:

    1. Letter to My Future Self

    Reflective essay on human-machine co-existence, future career aspirations, and personal ethical philosophies in an AI-driven society.

    2. Smart Home Floor Plan

    Architectural diagram identifying smart sensors, IoT devices, smart thermostats, and automated lighting (inspired by the LUIS demo).

    3. Future Job Advertisement

    Drafting a job recruitment flyer for a 2035 career (e.g., AI Ethicist, Autonomous Vehicle Fleet Coordinator, Prompt Engineer).

    4. The 4Ws Problem Canvas

    Structured canvas mapping Who are the stakeholders, What is the problem, Where does it occur, and Why is a solution valuable.

    5. Ecological System Map

    Causal loop diagram illustrating relationships between high energy consumption, data center operations, and renewable energy adoption.

    Quick Revision Terms Cheat Sheet (Part D)

    UN SDGs17 Global goals established by the United Nations to end poverty and ensure prosperity by 2030.
    Teachable MachineWeb-based tool by Google for training quick machine learning models without writing code.
    System MapDiagram illustrating interconnected elements and positive/negative causal feedback loops.
    4Ws CanvasScoping tool: Who are stakeholders, What is the issue, Where is context, Why does it matter.
    Student PortfolioCurated evidence of a student's learning journey, creative projects, and reflections across the term.
    Field Visit ReportAnalytical documentation summarizing industrial applications, technology stack, and ethics observed.

    Frequently Asked Questions: Part D Project Work

    Return to the Main AI Syllabus Hub

    Review the comprehensive Class 9 Artificial Intelligence 417 curriculum structure, marks distribution, and chapter guides.

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    Curriculum reference: CBSE Class 9 Artificial Intelligence (Subject Code 417), Session 2026–27.

    Disclaimer: TeacherColab is an independent educational platform and is not affiliated with or endorsed by CBSE.

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