What the Class 9 and Class 10 Computer Science courses cover, unit by unit, and how the free notes on this site line up with them. No textbook files are hosted or distributed here.
Class 9 and Class 10 Computer Science are one continuous course split across two years. Class 9 builds the foundations — how a computer is organised, how data is represented, how networks move it, and how to plan a solution before writing code. Class 10 takes those foundations and makes them practical: writing real Python, querying real data with SQL, and evaluating whether an AI model actually works. If a Class 10 topic feels like it assumes something, the assumption is usually in the matching Class 9 chapter, and each page links across to it.
Class 9
Class 9 Computer Science
The Class 9 Computer Science course introduces computing as a subject rather than as a set of software skills. It starts from systems thinking and the internal architecture of a computer, moves through networks and problem-solving, and finishes with the social and commercial context in which computing is used.
Units covered
Introduction to computing systems, number systems and text encoding
Digital signals, Boolean logic and systematic troubleshooting
Computer networks, protocols, topologies and the OSI model
Computational thinking, algorithms, flowcharts and pseudocode
Web development with HTML, CSS and JavaScript
Data science fundamentals and gathering data
Emerging technologies: AI, machine learning and the Internet of Things
The Class 10 Computer Science course builds directly on Class 9. It goes deeper into how an operating system works, introduces Python programming properly, and develops the data science and artificial intelligence material from an overview into something you can calculate with and evaluate.
Units covered
Operating systems: structure, services, processes and scheduling
System recovery, diagnostic tools and advanced maintenance
Introduction to Python programming: data types, operators and I/O
Control structures in Python: selection, loops, lists and debugging
Data science: the data science life cycle, visualisation and SQL
Introduction to AI and machine learning, including model evaluation
Applications of AI: NLP, robotics, speech technology and ethics
Digital entrepreneurship: problem-solving, ethics and customer tools
These pages describe what each course covers. IK Learning does not host, upload, mirror or link to textbook PDFs or scanned pages — those remain the copyright of their publishers, and your school or the official publisher is the right source for a copy. The notes we publish are our own explanatory material, written to be studied alongside your course book.