Python Syllabus for Class 12

 

Python Syllabus for Class 12

Unit 1: Revision of Class 11 Concepts

Quick recap of Python basics (data types, operators, loops, functions)

OOP concepts (inheritance, polymorphism, encapsulation)

File handling (text, binary, CSV, JSON)

Exception handling (custom exceptions, raising exceptions)

Unit 2: Data Handling with Pandas

Introduction to Pandas library

Series: creation, indexing, operations, attributes, methods

DataFrames: creation, indexing, slicing, adding/deleting rows & columns

Basic DataFrame operations: head(), tail(), info(), describe()

Importing/exporting data (CSV/Excel files)

Unit 3: Data Visualization

Introduction to Matplotlib library

Line plots, bar graphs, histograms, pie charts

Customization: titles, labels, legends, grid, colors

Plotting multiple datasets on the same graph

Saving and displaying plots

Unit 4: Working with Databases (SQL + Python)

Introduction to databases & DBMS concepts

MySQL basics: creating databases & tables, inserting, updating, deleting records

SQL queries: SELECT, WHERE, ORDER BY, GROUP BY, aggregate functions

Connecting Python with MySQL (using mysql.connector)

Executing queries from Python (fetching and updating data)

Unit 5: Functions & Modules (Advanced)

User-defined functions with *args and **kwargs

Recursive functions (mathematical & searching problems)

Anonymous (lambda) functions

Built-in higher-order functions (map(), filter(), reduce())

Python modules: math, random, statistics, datetime, os, sys

Unit 6: Object-Oriented Programming (Advanced Applications)

Review of classes & objects

Inheritance (single, multiple, multilevel, hierarchical, hybrid)

Method overriding & polymorphism

Encapsulation (private/protected/public attributes)

Project examples using OOP (Banking system, Student management system)

Unit 7: File Handling (Applications)

Reading/writing structured data with CSV & JSON files

Binary file operations (storing/retrieving objects using pickle)

Case study: maintaining student records in a binary/CSV file

File handling with error checking

Unit 8: Data Structures & Algorithms

Stack implementation using lists

Queue implementation (simple queue, circular queue, deque)

Linked list (basic introduction)

Searching (linear search, binary search)

Sorting (bubble sort, insertion sort, selection sort, quick sort)

Time complexity analysis (basic Big-O notation)

Unit 9: Advanced Python Libraries

Introduction to NumPy (arrays, operations, mathematical functions)

Using Pandas with NumPy for data analysis

Combining Pandas + Matplotlib for visualization projects

Unit 10: Projects / Capstone

Students create comprehensive projects combining file handling, OOP, Pandas, SQL, and visualization.

Examples:

Student Result Management System (Python + MySQL + CSV)

Library Management System with database connectivity

Sales Data Analysis using Pandas & Matplotlib

Hospital/Employee/Banking Management System

COVID-19/Weather Data Visualization Project

Quiz/Game Application with database