Python Classes Syllabus, Units & Marks

Studying this subject? See the Python Classes course, or read the units below first.

What is the Python Classes syllabus?

Python Classes is organised into 12 units. The full unit list, the topics inside each one and the exam pattern are below, taken from the syllabus we teach to.

Python Classes unit list

What each unit covers

Unit 1: Getting Started with Python

• Installing Python and using the interpreter / IDE (IDLE, VS Code)
• Interactive mode vs script mode
• print() and basic output
• Comments and code readability
• Your first program

Unit 2: Variables, Data Types and Operators

• Variables and assignment
• Numbers (int, float, complex) and Booleans
• Type casting and type checking
• Arithmetic, comparison, logical, assignment operators
• Identity and membership operators
• Taking user input with input()

Unit 3: Strings

• Creating and indexing strings
• Slicing and immutability
• String concatenation and repetition
• Common string methods
• String formatting (f-strings, format())
• Escape sequences

Unit 4: Control Flow

• if / elif / else statements
• Nested and shorthand conditionals
• match-case statements
• while loops
• for loops and the range() function
• break, continue and pass

Unit 5: Data Structures

• Lists: indexing, slicing, methods, sorting
• List comprehensions
• Tuples and unpacking
• Sets and set operations
• Dictionaries and nested dictionaries
• Looping techniques over collections

Unit 6: Functions

• Defining and calling functions
• Parameters, arguments and return values
• Default, keyword, *args and **kwargs
• Scope: local vs global
• Lambda (anonymous) functions
• Recursion and an idea of efficiency
• Modular thinking and reusability

Unit 7: Modules and Standard Library

• Importing modules and packages
• math, random, statistics modules
• datetime and time
• Creating your own modules
• pip and installing third-party packages
• Brief tour of the standard library

Unit 8: Input/Output and File Handling

• Reading and writing text files
• File modes (r, w, a, r+)
• with statement and context managers
• Working with CSV files
• Introduction to JSON

Unit 9: Errors and Exception Handling

• Syntax errors vs runtime errors
• try / except / else / finally
• Catching specific exceptions
• Raising exceptions
• Debugging strategies

Unit 10: Object-Oriented Programming

• Classes and objects
• The __init__ method and self
• Instance attributes and methods
• Encapsulation and private members
• Inheritance and method overriding
• Polymorphism
• Special / dunder methods (__str__, __repr__)

Unit 11: Working with Data (Intro Libraries)

• Introduction to NumPy arrays
• Introduction to Pandas DataFrames
• Basic data analysis on CSV data
• Simple plotting with Matplotlib
• When and why to use libraries

Unit 12: Projects and Applications

• Console mini-projects (calculator, quiz, number game)
• Text/file processing automation script
• OOP-based application (e.g. bank/library/inventory manager)
• A small data-driven project using a CSV dataset
• Code organisation, testing and documentation
• Version basics and sharing your code

Exam pattern

Board-independent programming track, so there is no fixed external exam. Assessment is project- and practical-driven: roughly 60% hands-on coding assignments and projects, 40% concept checks/quizzes. For reference, in CBSE Computer Science (which uses Python) the board pattern is 70 marks theory + 30 marks practical.

Practical and project work

Hands-on lab in every unit: learners code along in IDLE/VS Code and complete graded programming assignments. Culminates in multiple projects, console apps (calculator, quiz, game), a file-processing automation script, an OOP-based application, and a small data analysis project on a real CSV dataset using Pandas/Matplotlib. Mirrors CBSE-style practical work (program writing + project + viva).

Reviewed by Kajal Ma'am (MCA), teaching CBSE Computer Science & Informatics Practices since 2006. Weightage per the official CBSE 2026-27 curriculum.