India · CBSE Learning Outcomes
Class 11 Computer Science
A comprehensive introduction to computer science fundamentals focusing on problem solving through Python. Students explore hardware architecture, algorithmic logic, and the ethical implications of digital technology in the modern world.
Computer Systems and Organization
Exploration of hardware components, memory hierarchy, and how software interacts with physical circuitry.
Tracing the history of computers from the abacus to modern integrated circuits and cloud computing.
Understanding binary, octal, and hexadecimal systems alongside logic gates and circuits.
Analyzing the role of the OS in resource management and the different categories of software.
Computational Thinking and Foundations
Developing a mindset for breaking down complex problems into manageable algorithmic steps.
Learning to identify repeating structures and breaking problems into sub-problems.
Visualizing logic and writing language-independent instructions for problem solving.
Introduction to the concept of time and space complexity in basic searches and sorts.
Python Programming Fundamentals
Mastering the syntax and basic constructs of the Python language for general purpose programming.
Working with numbers, strings, and the dynamic typing system in Python.
Implementing decision-making logic using if-else structures and logical operators.
Automating repetitive tasks through for and while loops.
Data Structures and Collections
Using Python lists, tuples, and dictionaries to organize and manipulate data sets.
Understanding ordered sequences and the difference between mutable and immutable data.
Manipulating text data through slicing, concatenation, and built-in methods.
Mapping data using unique keys for fast lookup and complex data modeling.
Society, Law, and Ethics
Examining the impact of technology on privacy, security, and social equity.
Analyzing how personal data is collected, stored, and used by digital platforms.
Identifying common threats like phishing, malware, and hacking, and defensive strategies.
Understanding copyrights, licenses, and the environmental impact of technology.
Data Handling and Analysis
Introduction to statistics, data visualization, and drawing insights from information.
Gathering data from various sources and preparing it for meaningful analysis.
Using charts and graphs to represent trends and patterns in data.
Exploring the characteristics of large-scale datasets and their applications in AI.