Class 11 Computer Science Resources
📚 Computer Science Book
Class 11 Computer Science Curriculum
CS — Chapter 1: Computer System
Introduction to computer systems, evolution, memory, CPU data transfer, microprocessors, data & information, software, and operating systems.
CS — Chapter 2: Encoding Schemes and Number System
Number systems, conversions between binary, octal, decimal, hexadecimal, and encoding schemes.
CS — Chapter 3: Emerging Trends
Artificial Intelligence, Big Data, IoT, Cloud Computing, Grid Computing, and Blockchain technologies.
CS — Chapter 4: Introduction to Problem Solving
Steps for problem solving, algorithms, flowcharts, pseudocode, flow of control, verification, and comparison of algorithms.
CS — Chapter 5: Getting Started with Python
Python introduction, keywords, identifiers, variables, comments, data types, operators, expressions, I/O, and type conversion.
CS — Chapter 6: Flow of Control
Selection statements (if-else), indentation, repetition (loops), break and continue statements, nested loops.
CS — Chapter 7: Functions
Functions, user-defined functions, scope of variables, and Python standard library.
CS — Chapter 8: Strings
String operations, traversing strings, string methods, built-in functions, and string handling techniques.
CS — Chapter 9: Lists
List operations, traversing lists, list methods, nested lists, copying, and list manipulation techniques.
CS — Chapter 10: Tuples and Dictionaries
Tuples, tuple operations, dictionaries, dictionary methods, manipulation, and nested structures.
CS — Chapter 11: Societal Impact
Digital footprints, digital society, cyber ethics, data protection, cybercrime, IT Act, and impact on health and privacy.
📚 Informatics Practices Book
Class 11 Informatics Practices Curriculum
IP — Chapter 1: Computer System
Introduction to computer systems, evolution, memory, and software fundamentals.
IP — Chapter 2: Emerging Trends
Artificial Intelligence, Big Data, IoT, Cloud Computing, Grid Computing, and Blockchain fundamentals.
IP — Chapter 3: Brief Overview of Python
Python basics, keywords, identifiers, variables, data types, operators, expressions, loops, and functions.
IP — Chapter 4: Working with Lists and Dictionaries
List operations, traversing, list methods, dictionaries, traversing dictionaries, and manipulation.
IP — Chapter 5: Understanding Data
Data collection, data storage, data processing, and statistical techniques for data analysis.
IP — Chapter 6: Introduction to NumPy
NumPy arrays, indexing, slicing, operations on arrays, concatenation, reshaping, and statistical operations.
IP — Chapter 7: Database Concepts
File systems, database management systems, relational data model, and keys in databases.