Complete CBSC School Curriculum: Coding, Robotics & AI/ML

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Coding

- Understand sequence and order

- Follow step-by-step instructions

- Recognize patterns in daily activities

- Basic cause and effect   

- Sequencing

- Instructions

Patterns

- Problem-solving

- Story sequencing cards

- Dance move sequences

- Simple drawing instructions

- Role-play activities

- Observation checklists

- Oral demonstrations

- Activity participation

Pattern completion tasks

  Robotics

- Control screen-free robots

- Understand directional commands

- Navigate simple paths

- Introduction to input-output

Forward/backward/turn

-Directional movement

-Path planning

-Commands

-Floor robot maze navigation

-Treasure hunt challenges

-Shape drawing with robots

-Story-based missions

-Task completion

-Peer collaboration

-Problem-solving approach

-Verbal explanation

AI/ML Concepts

-Identify patterns in objects

- Sort by attributes (color, shape, size)

- Make simple predictions

- Understand that machines follow rules

-Pattern recognition

- Classification

- Sorting

- Prediction

-Sort animals by features

- Pattern completion games

- Guess the next item

- Smart toy interactions       

-Sorting accuracy

- Pattern identification

- Prediction reasoning

- Group discussions

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Coding

- Create sequences with loops

- Understand events and triggers

- Debug simple programs

- Build interactive stories

- Loops (repeat)

- Events

- Debugging

Sequences             

- Animated greeting cards

- Interactive digital stories

- Simple pattern games

- Character movement programs             

- Project completion

- Code review

- Peer feedback

- Creative expression

Robotics

- Program robot movements

- Use color sensors

- Complete structured challenges

- Understand input-output relationship             

- Sensor basics

- Color detection

- Cause-effect

- Programming logic     

- Color-following robot

- Obstacle navigation

- Light-activated responses

- Musical robots  

- Challenge success rate

- Design documentation

- Teamwork assessment

- Presentation skills

AI/ML Concepts             

- Recognize automation in daily life

- Understand if-then relationships

- Create simple decision trees

- Identify smart devices at home

- Automation

- Conditionals (if-then)

- Decision making

- Smart technology

- Smart home simulation

- Robot pet behavior programming

- Voice command games

- Traffic light logic     

- Concept application

- Real-world connections

- Logical reasoning

- Oral presentations

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Coding

- Master loops and nested loops

- Use conditionals effectively

- Introduction to variables

- Debug complex sequences

- Nested loops

- If-else statements

- Variables

- Debugging strategies             

- Maze solving games

- Quiz applications

- Interactive animations

- Simple catch games  

- Code efficiency

- Problem-solving approach

- Error identification

- Project presentation

Robotics             

- Line-following robots

- Multiple sensor programming

- Design-test-improve cycle

- Basic engineering concepts             

- Line sensors

- Distance sensors

- Sequential programming

- Design thinking             

- Line-following car

- Obstacle avoidance robot

- Drawing robot

- =Simple gripper mechanism             

- Technical documentation

- esting logs

- Design improvements

- Team collaboration

AI/ML Concepts             

- Computational thinking fundamentals

- Pattern-based decision making

- Introduction to data collection

- Algorithms in everyday life             

- Algorithms

- Data patterns

- Computational thinking

- Training concept

- Shape recognition program

- Sort data by multiple rules

- Weather prediction game

- Pattern finder application

- Algorithmic thinking

- Data analysis

- Logical reasoning

- Concept maps

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Coding

- Use variables for storage

- Create custom functions

- Build interactive games

- Understand user input/output             

- Variables & data

- Functions

- User interaction

-Game logic

- Score-keeping games

- Quiz with questions bank

- Simple platformer

-Interactive calculator

- Code functionality

- User experience

- Documentation quality

- Peer code review

Robotics

-Multi-sensor integration

- Motor speed and direction control

- Collaborative robot builds

- Introduction to feedback systems

- Touch sensors

- Light sensors

- Motor programming

- Feedback loops

- Sensor-triggered alarm

- Light-seeking robot

- Remote-controlled vehicle

- Automated gate system

- System functionality

- Design process

- Team contribution

-Technical report

AI/ML Concepts             

- Distinguish smart vs programmed systems

- Understand training vs coding

- Recognize data patterns

- Introduction to machine learning

- Training data

- Learning systems

- Pattern recognition

- Prediction

- Animal classifier

- Sound recognition

- Gesture control game

- Recommendation system (books)

- Model accuracy

- Data collection quality

- Testing documentation

- Concept explanation

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Coding

-Transition to text-based coding

- Python syntax basics

- Lists and basic data structures

- Create functional programs             

- Python basics

- Lists & strings

- Functions

- Input/output

-Text adventure game

- Simple calculator

- Mad Libs generator

- Number guessing game   

- Code syntax accuracy

- Logic implementation

- Program functionality

- Written reflection

Robotics

-Logic-based robot programming

- Complex sensor combinations

- Design-build-test methodology

- Introduction to automation             

- Logical operators (AND/OR)

- Sensor fusion

- Design process

- Automation basics

- Automated plant waterer

- Parking sensor system

- Smart dustbin

- Home automation model

- Design documentation

- Testing and refinement

- Presentation quality

- Innovation assessment

AI/ML Concepts             

-Real-world AI applications

- Supervised learning introduction

- Data bias awareness

- Ethical considerations             

- Supervised learning

- Training datasets

- Bias in data

- AI ethics

- Spam filter simulation

-Face detection basics

- Movie recommender

- AI in daily life project             

- Research quality

- Practical application

-Ethics discussion

- Portfolio presentation

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Coding 

- Python Programming Fundamentals
- Operators and expressions
- Control structures (if/else, loops)
- Function creation

- Data types
- Operators
- Control flow
- Functions and parameters

- Grade calculator
- Simple chatbot
- Text-based games
- Pattern generator

-Coding tests
- Project rubrics
- Code efficiency
- Problem-solving approach

Robotics

-Microcontroller basics
- Digital and analog inputs
- Basic circuit design
- Robot movement programming

- Digital I/O
- Analog sensors
- Circuit basics
- Serial communication

- Temperature monitor
- Motion detector
- LED traffic light
- Distance measuring device

- Technical documentation
- Circuit diagrams
- Functionality testing
- Safety compliance

AI/ML Concepts

- How machines learn
- Classification fundamentals
- Real-world AI examples
- Data and features

- Classification
- Features and labels
- Training process
- AI applications

- Plant species identifier
- Music genre detector
- Handwriting recognition introduction
- AI research presentation

-Concept understanding
- Research skills
- Presentation delivery
- Critical thinking

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Coding 

- Python data structures (lists, tuples, dictionaries)
- File handling
- Modules and libraries
- String manipulation

- Data structures
- File I/O
- Modules
- String methods

- Contact manager
- Quiz with file storage
- Text analyzer
- Simple database

- Written exams
- Project assessment
- Code documentation
- Peer review

Robotics

- Electronics fundamentals
- Voltage, current, resistance
- Sensor networks
- Circuit design and testing

- Ohm’s Law
- Series and parallel circuits
- Breadboard prototyping
- PWM control

- Smart plant monitor
- Distance warning system
- RGB mood lighting
- Solar tracker

-Circuit testing
- Design documentation
- Safety protocols
- Troubleshooting skills

AI/ML Concepts

- Training machine learning models
- Image and audio recognition
- Model accuracy and testing
- Data preprocessing

- Training and testing
- Accuracy metrics
- Overfitting basics
- Data quality

- Speech command recognizer
- Hand gesture controller
- Rock-paper-scissors AI
- Sound classifier

-Model performance
- Training logs
- Testing documentation
- Analysis report

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Coding

- Object-oriented programming
- Classes and objects
- Web development basics (HTML/CSS)
- Algorithms and sorting

- OOP concepts
- Inheritance
- Web technologies
- Algorithm efficiency

- Library management system
- Personal portfolio website
- Tic-tac-toe with AI
- Sorting visualizer

- Theory exams
- Practical tests
- Project evaluation
- Code quality metrics

Robotics

- Multi-component systems
- Automation projects
- Wireless communication basics
- Project management

- System integration
- State machines
- Bluetooth/WiFi basics
- Documentation

- Warehouse automation model
- Smart traffic system
- Home security prototype
- Automated greenhouse

- Project proposal
- System design
- Implementation quality
- Final presentation

AI/ML Concepts             

- Computer vision introduction
- Object detection basics
- Neural networks overview
- Dataset creation

- Image processing
- Object detection
- Neural networks
- Data labeling

- Face detection app
- Object counter
- Color-based tracker
- Custom dataset project

- Model accuracy
- Dataset quality
- Technical report
- Demonstration

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Coding

- Advanced Python programming
- Data structures (stacks, queues)
- Algorithm design
- API integration

-Advanced data structures
- Recursion
- API calls
- JSON handling

- Weather dashboard
- Data visualization tool
- REST API consumer
- Web scraper

- Written examination (40%)
- Practical exam (30%)
- Project work (20%)
- Internal assessment (10%)

Robotics

- Internet of Things (IoT) fundamentals
- Cloud connectivity
- Sensor networks
- Data logging and visualization

- IoT protocols
- MQTT/HTTP
- Cloud platforms
- Data analytics

- Smart home system
- Environmental monitoring station
- IoT-based attendance
- Remote plant monitor

- Design documentation
- System functionality
- Data analysis
- Innovation report

AI/ML Concepts             

- AI ethics and responsibility
- Data privacy and security
- Algorithmic bias
- Social implications of AI

- Ethical AI
- Privacy concerns
- Bias detection
- Fairness in algorithms

Bias in datasets analysis
Privacy impact assessment
Ethical AI case studies
Fair lending model

Research paper
Ethics debate
Case study analysis
Group presentation

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Coding

Advanced Python concepts
Database management (SQL)
Web frameworks basics
Software development lifecycle

Database design
SQL queries
Backend basics
SDLC phases

School management system
E-commerce prototype
Blog platform
Inventory tracker

Theory exam (40 marks)
Practical exam (30 marks)
Project (20 marks)
Viva (10 marks)

Robotics

Advanced IoT systems
Edge computing concepts
Real-time data processing
System architecture design

Edge vs cloud
Real-time systems
Distributed systems
Performance optimization

Smart agriculture system
Industrial automation model
Intelligent traffic management
Energy monitoring system

Project report (detailed)
System demonstration
Technical viva
Innovation assessment

AI/ML Concepts             

Machine learning algorithms
Supervised vs unsupervised learning
Model evaluation metrics
scikit-learn basics

Classification algorithms
Clustering
Regression
Cross-validation

Student performance predictor
Customer segmentation
Spam email classifier
House price prediction

Model accuracy report
Algorithm comparison
Jupyter notebook
Presentation

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Computer Science

Advanced Python (OOP, inheritance)
File handling & exceptions
Data structures implementation
Database management with SQL
Boolean logic and circuits

Classes & inheritance
Polymorphism
Exception handling
Stacks, queues
Relational databases

Student record system
Bank management application
Custom data structure library
Database-driven website

Unit tests (20 marks each)
Practical (30 marks)
Project (20 marks)
Annual exam (70 marks)

Robotics

Autonomous robot systems
SLAM (Simultaneous Localization and Mapping)
Advanced sensors (LIDAR, IMU, GPS)
Robot operating systems basics
Competition robotics

Autonomous navigation
Localization
Mapping algorithms
Sensor fusion
Control systems

Autonomous delivery robot
Maze-solving robot
Line-following with mapping
Robotic arm with vision
Competition robot

Design portfolio
Technical documentation
Performance testing
Competition participation
Viva voce

AI/ML  

- Deep learning fundamentals
- Convolutional - Neural Networks
- Recurrent Neural Networks
- Model training pipelines
TensorFlow/Keras basics
- Computer vision applications

- Neural network architecture
- CNNs for images
- RNNs for sequences
Training/validation/testing
- Transfer learning
- Hyperparameter tuning

- MNIST digit classifier
- CIFAR-10 image recognition
- Sentiment analysis (movie reviews)
- Time series forecasting
- Custom image classifier

- Theory exam (40%)
- Model performance (25%)
- Project report (25%)
- Presentation (10%)

Domain

Learning Objectives

Key Concepts

Sample Projects

Assessment Methods

Computer Science

Advanced data structures (graphs, trees)
Algorithm complexity analysis
Computer networks fundamentals
Cybersecurity basics
Full-stack development

Graph algorithms
Big O notation
TCP/IP, HTTP
Encryption & security
Client-server architecture

Social network analyzer
Path-finding visualizer
Secure chat application
Network monitoring tool
Full-stack e-commerce site

Board Exam (70 marks)
  - Theory: 35 marks
  - Case studies: 15 marks
  - SQL/Python: 20 marks
Practical (30 marks)
  - Lab test: 15 marks
  - Project: 10 marks
  - Viva: 5 marks

Robotics

End-to-end robotics systems
Multi-robot coordination
Real-world deployment
PCB design basics
Advanced control systems
Capstone robotics project

System integration
Swarm robotics
PID controllers
State estimation
Fault tolerance
Professional documentation

Capstone Project:
  - Autonomous warehouse robot
  - Search & rescue bot
  - Agricultural automation
  - Medical assistance robot
  - Competition-level robot

Project proposal (10%)
Design documentation (20%)
Implementation (30%)
Testing & refinement (20%)
Final presentation (15%)
Viva & demo (5%)

AI/ML

Advanced neural networks
Natural Language Processing
Computer vision applications
Model deployment
MLOps basics
Capstone AI project
Research & ethics

NLP fundamentals
Object detection (YOLO, R-CNN)
Model serving
Cloud deployment
A/B testing
Responsible AI
Research methodology

Capstone AI Project:
  - Healthcare diagnostic tool
  - Real-time object detection system
  - Chatbot with NLP
  - Predictive analytics dashboard
  - AI research paper

AI Board Exam (70 marks)
Practical (30 marks)
  - Project: 15 marks
  - Lab practical: 10 marks
  - Viva: 5 marks
Continuous assessment
Research paper/report