Part C: Practical Exam & Capstone Blueprint15 Practical Activities, Capstone Workflow, Lab Rubrics & Viva Voce Bank
The definitive practical examination guide for CBSE Class 11 Artificial Intelligence. Complete documentation for all 15 prescribed practical file activities, IBM SkillsBuild certification requirements, Capstone project workflow, and Viva Voce model answers.
Part C: 50 Marks Score Distribution
5 M
IBM SkillsBuild
12 M
Team Prototype
7 M
Bootcamps / Intern
10 M
15 Activities
10 M
Hands-on Coding
6 M
Viva Voce
15 Prescribed Practical Activities (CBSE Handbook Page 7)
Students must complete, run, and neatly document each activity in their official laboratory record book:
AI Domains Categorization
AI FoundationsCategorize 15 real-world applications into Data Science, NLP, and Computer Vision.
Industry Hiring Analysis
AI CareersIdentify 10 major global enterprises actively recruiting for specialized AI positions.
Technical vs. Soft Skills Comparison
AI CareersCompare technical toolkits and soft skills listed by two corporations (e.g. IBM & Cognizant).
Level 1 Python Control Flow Programs
Python Level 1Write at least 5 Python programs demonstrating operators, data types, if-elif-else, and for loops.
Level 2 Python Libraries (NumPy, Pandas, Sklearn)
Python Level 2Execute 5 programs utilizing NumPy array operations, Pandas DataFrames (.loc/.iloc), and Scikit-Learn KNN.
4-Quadrant Empathy Map Creation
Design ThinkingConstruct a comprehensive Empathy Map (Says, Thinks, Does, Feels) for a target persona scenario.
Project Abstract Creation (5W1H Framework)
Design ThinkingAuthor a formal Capstone Project Abstract incorporating the 5W1H method aligned with UN SDGs.
Python Statistics Module Computations
Data LiteracyImplement Python programs calculating Mean, Median, Mode, Variance, and Standard Deviation.
Matplotlib Data Visualizations
Data LiteracyGenerate Line Graphs, Bar Charts, Histograms with bins, Scatter Plots, and Pie Charts using Matplotlib.
Pearson Correlation Coefficient in MS Excel
Machine LearningCompute Pearson's r for paired continuous variables in Excel using formula and scatter trendline.
Linear Regression Modeling in MS Excel
Machine LearningCalculate Slope and Intercept for a regression dataset using =SLOPE() and =INTERCEPT().
Ice-Cream Ordering Chatbot Development
NLPBuild a functioning conversational ordering bot using Google Dialogflow, Botsify, or Python.
'Humans Need Not Apply' Reflection Paper
AI EthicsAuthor an analytical summary paper reflecting on automation and societal implications from the documentary.
Comparative Policy Study across Global Tech
AI EthicsCompare ethical guidelines established by the IBM AI Ethics Board, Microsoft, Google, and the EU.
Ethical Dilemmas on Moral Machine & Survival of the Best Fit
AI EthicsExplore autonomous vehicle collision trade-offs on MIT Moral Machine and hiring bias in Survival of the Best Fit.
Capstone Execution Timeline (30 Instructional Hours)
Follow the official 11-step execution workflow from the CBSE-IBM Projects Cookbook (Handbook Page 8):
Viva Voce Question Bank with Model Answers
Frequently Asked Questions (FAQ)
Score 50/50 in Practical & Capstone with 1:1 Live Lab Mentoring
Get 1-on-1 personalized assistance with your 15 Practical File activities, Excel regressions, Scikit-Learn pipelines, Capstone project documentation, and mock Viva Voce sessions.