Overview: Introduction to Python, its applications and setting up the development environment.

Key Topics: Python syntax, variables, basic input/output, running scripts.

Practical Task: Write a simple “Hello, World!” program and basic calculations.

Overview: Working with Python’s data types and variable assignments.

Key Topics: Integers, floats, strings, type conversions.

Practical Task: Create programs using different data types and perform basic operations.

Overview: Using loops and conditional statements to control program flow.

Key Topics: if, else, elif, for loops, while loops.

Practical Task: Write a program with loops and conditional logic for decision-making.

Overview: Introduction to functions for code reusability.

Key Topics: Defining functions, parameters, return values, scope.

Practical Task: Create a modular program with multiple functions.

Overview: Introduction to common Python data structures.

Key Topics: Lists, tuples, dictionaries, indexing, and basic operations.

Practical Task: Manipulate data using lists and dictionaries.

Overview: String manipulation techniques for text-based data.

Key Topics: String methods, formatting, slicing and concatenation.

Practical Task: Write a program that processes text data.

Overview: Basics of OOP in Python.

Key Topics: Classes, objects, attributes, methods.

Practical Task: Define a simple class and create instances.

Overview: Reading from and writing to files for data storage.

Key Topics: Open, read, write, append and file management.

Practical Task: Create a program that reads from and writes to text files.

Overview: Writing error-free programs with exception handling.

Key Topics: try, except, finally, debugging techniques.

Practical Task: Implement error handling in a program to manage user input errors.

Overview: Using Python libraries to extend functionality.

Key Topics: Importing modules, using libraries (e.g., Math, Random).

Practical Task: Write a program using Math and Random libraries.

Overview: Introduction to data analysis using Pandas.

Key Topics: DataFrames, data manipulation, data cleaning.

Practical Task: Load and manipulate a dataset using Pandas.

Overview: Visualizing data with Python’s Matplotlib library.

Key Topics: Basic plots, histograms, scatter plots, data presentation.

Practical Task: Create visualizations for a dataset to communicate findings.

Coding Assignments: Practical exercises aligned with each module to reinforce understanding.

Quizzes: Periodic quizzes to evaluate knowledge of core concepts.

Final Project: A culminating project where students apply their skills to develop a Python program that solves a real-world problem.