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Advanced
Class 9 - Robotics and Artificial Intelligence
Learn Robotics and Artificial Intelligence from scratch with ICSE Class 9 Robotics and AI course. Master robot fundamentals, Python programming, and AI tools like Quarky and PictoBlox for engaging, practical learning.
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Course Description
Step into the world of Robotics and Artificial Intelligence with the ICSE Class 9 AI & Robotics course. This engaging curriculum covers robot fundamentals, motion mechanics, robot systems, and AI basics while introducing students to real-world applications across industries like healthcare, agriculture, and entertainment. Alongside practical projects, learners build coding confidence through Python programming for beginners and explore popular AI tools such as PictoBlox and Machine Learning for Kids. Perfect for students aiming to excel in the ICSE robotics syllabus and start early in AI and robotics innovation.
What you will learn:
- Understand robot basics, components, and real-world applications
- Explore bio-inspired robots and practical uses in everyday life
- Learn essential Python programming concepts for students
- Discover how data shapes Artificial Intelligence systems
- Develop projects using Quarky robotics kits and PictoBlox AI tools
- Learn ethical considerations in AI and responsible technology use
Learning Path
7 Modules • Click a step to explore
0%
Module 1
Module 2
Module 3
Module 4
Module 5
Module 6
Module 7
1
Module 1: Introduction to Robotics
1.1
1. Robot Fundamentals - Understanding Robots, Why Robots?, Defining a Robot, Characteristics & Benefits
1.2
2. Robot Evolution & Laws - Evolution of Robots, Three Laws of Robotics
1.3
3. Robot Classification - Classification Based on Terrain & Controls, Manual vs Automatic Robots
1.4
4. Bio-Inspired & Real-World Robots - Bio-inspired Robots, Real World Applications
2
Module 2: Robot as a System
2.1
1. Core Building Blocks - Power Supply, Actuators, Sensors, Control Systems
2.2
2. System Components - End Effector, Communication System, User Interface, Structural Frame
2.3
3. Locomotion & Software - Mobility System, Software and Firmware of Robots
2.4
4. Design Integration - Mechanical, Electronics & Computation in Robots, Design Aspects of Different Robot Types
3
Module 3: Concepts in Robotics
3.1
1. Motion Mechanics - Types of Motion (Linear, Angular, Circular), Motion in One/Two Dimensions
3.2
2. Joints & Links - Types of Joints (Prismatic, Spherical), Types of Links (Rigid, Soft)
3.3
3. Joint-Link Integration - Using Links and Joints in Robotic Systems
3.4
4. Degrees of Freedom - DOF Definition, Identification, Practical Examples
4
Module 4: Introduction to Artificial Intelligence
4.1
1. AI Fundamentals - Understanding Intelligence, Animal Intelligence, Understanding AI
4.2
2. AI Timeline - History of Artificial Intelligence
4.3
3. AI Applications - E-commerce, Automobiles, Social Media, Agriculture, Robotics, Banking, Search Engines
4.4
4. AI Benefits & Ethics - Benefits of Using AI, Ethical Considerations (Bias, Fairness, Accountability, Transparency)
5
Module 5: Role of Data and Information, Evolution of Computing
5.1
1. Data Fundamentals - Data and Information (Qualitative vs Quantitative, Discrete vs Continuous, Primary vs Secondary)
5.2
2. Data Acquisition - Data Sources, Data Acquisition Methods
5.3
3. Data Types - Audio Data, Visual Data, Numeric Data, Text Data
5.4
4. Computing Evolution - Deterministic vs Probabilistic Computing, The Advent of AI, AI Discretion & Human Element
6
Module 6: Introduction to Data and Programming with Python
6.1
1. Python Basics - Getting Started, Statements, Comments, Keywords, Identifiers, Variables & Data Types
6.2
2. Python Operators - Arithmetic, Comparison, Logical, Assignment Operators, Input/Output
6.3
3. Data Structures & Control - Lists, Flow Control, Conditions (if/else/elif), Loops (for/while)
6.4
4. Functions & AI Tools - User Defined Functions, Introduction to PictoBlox AI, Machine Learning for Kids
7
Module 7: AI Concepts and AI Project Framework
7.1
1. AI Concepts - Broad AI vs Narrow AI, Expert Systems, ELIZA Example
7.2
2. AI Domains - Data Sciences, Computer Vision (CV), Natural Language Processing (NLP)
7.3
3. Project Methodology - AI Project Cycle, Problem Scoping (4Ws Problem Canvas)
7.4
4. Data Pipeline & Modeling - Data Acquisition, Data Exploration, Modelling, Evaluation, Neural Networks
Instructor
Verified
Nitil Singh
Edtech Mentor and Web Developer !
900+
Reviews
1000+
Students
20+
Courses
Biography
“
I am an enthusiastic educator with 3+ year of experience teaching Robotics, STEM and Automation. I specialize in simplifying complex technical concepts, making them engaging and accessible for learners of all backgrounds. My classes blend theory with hands-on projects, helping students understand how robotics shape the world around us.
Passionate about fostering curiosity and innovation, I am committed to inspiring the next generation of creators and problem-solvers through practical learning and interactive teaching methods.
Educational Qualification - B.Tech - Computer Science Engineering (CSE)
Experience - 3+ Year in Education-Technology (EdTech) and Web Development.
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What’s Included
Everything you need to know about this course
Lectures
30 ClassesDuration
12 - 14 WeeksLevel
BeginnerLanguage
English / HindiWhat you need / Requirement
Laptop/PC
A personal computer is essential for hands-on practice and project work.
Learning Path
Your Journey. Your Growth.
A structured path designed to take you from basics to mastery with clarity, confidence, and real-world impact.
01
Beginner
Start with fundamental concepts and build a strong foundation.
02
Intermediate
Expand your knowledge and start building practical projects.
03
Advanced
Dive deeper into specialized areas and master complex techniques.
04
Master
Achieve expert-level proficiency and innovate with your skills.
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