PadhoSikhoBanaao

Bharat ko aage badhaao

PadhoSikhoBanaao

Bharat ko aage badhaao

Knowledge → Real-World Skills

Here, learners build advanced robotics systems, IoT prototypes, AI applications, automation modules, and competition-ready projects. Futurists are trained like young engineers and tech leaders.

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Course Highlights (Aligned with NEP)

Artificial Intelligence (Core Concepts)

  1. Foundations of AI
  2. Types of AI: Narrow, Strong, Supervised, Unsupervised
  3. Real applications in healthcare, defense, telecom, industries
  4. AI pipelines: Data → Model → Prediction
  5. Responsible AI principles: fairness, transparency, safety

Data Science Essentials

  1. What is data? Types of data
  2. Data collection, cleaning, visualization
  3. Graphs: line, bar, scatter plots
  4. Intro to NumPy & Pandas (simple use cases)
  5. Mini-projects: Weather data analysis, School attendance analysis


Computer Vision (CV)

  1. How computers understand images
  2. Beginner OpenCV concepts (age-appropriate)
  3. Object detection, face recognition basics
  4. Projects: Gesture-controlled interface, Face detection & filters


Internet of Things (IoT)

  1. What is IoT and how devices talk to each other
  2. Cloud connectivity basics
  3. Automation and smart control
  4. IoT Projects: Smart home system, Weather station, Plant monitoring system



Design Thinking & Innovation

  1. 5-step design cycle
  2. Real problem identification
  3. Prototype development
  4. Innovation project presentation
  5. Suitable for ATL/Science fair submissions

Python Programming (Beginner to Intermediate)

  1. Python basics: variables, data types, operators
  2. Loops, functions, conditional statements
  3. Lists, tuples, dictionaries
  4. File handling & modules
  5. Build projects: Password generator, Student data management system, Chat-based menu programs


Machine Learning (Hands-On)

  1. What is ML? How machines learn?
  2. Data features, labels, training, testing
  3. Types: Classification & Regression
  4. Tools: Teachable Machine, Python-based ML (intro)
  5. Build ML projects: Image classifier, Sentiment analyzer, Simple prediction model



Robotics Engineering

  1. Microcontroller programming (Arduino/Pi/Pico)
  2. Sensors: IR, ultrasonic, gas, flame, DHT, soil moisture
  3. Circuits, motors, relays, servo control
  4. Robotics projects: Line follower robot, Fire safety robot, Obstacle avoider, Smart irrigation system




Natural Language Processing (NLP)

  1. How computers understand human language
  2. Tokenization, keywords, intent detection (simple level)
  3. Build projects: Rule-based chatbot, Text classifier, Voice command system


Ethics, Safety & Responsible AI

  1. Digital footprint
  2. Cybersecurity basics
  3. Data privacy awareness
  4. Ethical challenges in AI models

PROJECTS THROUGHOUT THE YEAR

  1. Python mini-apps
  2. AI image classifier
  3. Robotics prototypes
  4. Gesture-controlled system
  5. IoT monitoring device
  6. Simple ML prediction model
  7. Chatbot with NLP
  8. Science exhibition & ATL-ready projects

Learning Outcomes

Students will be able to:

✔ Code confidently in Python
✔ Build robotics and IoT systems
✔ Train and test simple AI/ML models
✔ Understand CV & NLP fundamentals
✔ Analyse datasets using Python
✔ Apply design thinking to real problems
✔ Prepare for careers in AI, robotics, engineering, IT

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