Class 10 - Robotics and Artificial Intelligence
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Take your knowledge to the next level with the ICSE Class 10 Robotics and Artificial Intelligence course. This comprehensive program dives deep into New Age Robotic Systems (NARS), collaborative robots (Cobots), and advanced topics in machine intelligence, cybersecurity, and robotics integration. Students enhance coding expertise through advanced Python programming and gain hands-on experience with libraries like NumPy, Pandas, and Matplotlib, essential for data analysis and AI projects. Ideal for those preparing for the ICSE robotics and AI syllabus, this course offers practical lab work, PictoBlox machine learning projects, and complete robotics system development with Quarky kits.
What you will learn:
- Master advanced robotics topics including Cobots and smart robotics systems
- Build complete robotics assemblies and learn robotics integration
- Gain skills in advanced Python programming and data analysis tools
- Explore machine learning applications and real-world AI projects
- Understand cybersecurity, ethics, and responsible AI deployment
- Work on complex robotics and AI projects using Quarky and PictoBlox
Skills You’ll Gain:
- Python Programming
- Artificial Intelligence Concepts
- Machine Learning
- Deep Learning Basics
- Computer Vision
- Object Detection using OpenCV & Python
- Python Libraries: NumPy, Pandas, Matplotlib, Scikit-learn
- Data Analysis & Visualization
- Sensors (IR, Ultrasonic, PIR, etc.)
- Arduino Programming
- Hands-on with AI Tools
- Logic Building & Debugging Skills
1. NARS Foundation
2. Industrial NARS
3. Service & Smart Systems
4. Specialized Applications
1. Machine vs Robot
2. Robot Characteristics
3 Cobot Introduction
4. Cobot Integration
1. Gear Systems
2. Sensor Technology
3. Actuator Systems
4. Control Integration
1. Quarky Kit Introduction
2. Programming Setup
3. Component Identification
4. Design Tools
1. Basic Robot Assembly
2. Navigation Robots
3. Safety & Detection
4. Advanced Manipulation
1. System Types
2. Decision Comparison
3. ML Fundamentals
4. ML Applications
1. Intelligence Comparison
2. AI Benchmarks
3. Human-Machine Collaboration
4. Security & Ethics
1. Project Methodology
2. Problem Definition
3. Data Management
4. Modeling & Evaluation
1. Advanced Python Setup
2. Python Libraries
3. Data Structures
4. String Processing
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What you need/Requirement

Laptop/PC
A personal computer is essential for hands-on practice and project work.
Learning Path




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