What is required for the Class XI AI Project component?

Students must complete a working Python project demonstrating data handling, simple machine learning modeling, and documentation in their practical notebook for the external examiner.

Home ASSEB AI HubUnit 11: Case Studies & Project

Class XIASSEB-527Unit 11: Case Studies and Project

Unit 11: Case Studies & Project

Master official ASSEB Class XI AI Unit 11: Case studies in Computer Vision, Natural Language Processing, AlphaGo, IBM Watson, AlphaFold, Tesla, and hands-on Python AI Project.

Theory: 4 Marks

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Practical: 10 Marks

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12 min read

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Class XI Units Navigator(14 Official Units)

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U1Employability Skills - Unit 1: ICT SkillsFree U2Employability Skills - Unit 2: Entrepreneurial Skills4m U3Employability Skills - Unit 3: Green Skills2m U1Introduction to Artificial IntelligenceFree U2AI Paradigms5m U3Mathematics for AI5m U4Programming for AI5m U5Machine Learning Paradigms4m U6Data Collection and Exploration6m U7Supervised Algorithms5m U8Unsupervised Algorithms4m U9Storytelling with Data5m U10AI Ethics and Values4m U11Case Studies & Project4m

Learning Outcomes

Analyze milestone real-world AI case studies across diverse industries (AlphaGo, IBM Watson Health, AlphaFold, Tesla Autopilot).
Understand applied Computer Vision and Natural Language Processing architectures.
Critically evaluate the technological successes and operational limitations of deployed AI systems.
Execute an end-to-end Basic AI Project in Python synthesizing the theory and practical concepts covered across Class XI.

Board Exam Scoring Tips

In 5-mark case study questions, structure your answer into: 1) Problem Context, 2) AI Architecture Used, 3) Real-World Impact, 4) Limitations / Ethical Challenges.
Know the difference between Computer Vision (processing pixel matrices) and NLP (processing tokenized text).

Key Takeaways

Case studies reveal how theoretical algorithms translate into real engineering successes and failures.
AlphaGo demonstrated the power of combining deep neural networks with Monte Carlo Tree Search.
AlphaFold solved a 50-year-old grand challenge in biology by predicting 3D protein structures from amino acid sequences.
The Class XI basic project requires an end-to-end Python script documented in a practical lab notebook for board evaluation.

Practice Unit MCQ Quiz

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