Python Programming Syllabus

Week 1: Introduction to Python and Setup
- Overview of Python and its applications
- Installing Python and setting up an IDE (e.g., Jupyter Notebook, PyCharm)
- Python basics: syntax, variables, data types, and comments
- Input and output statements (`print`, `input`)
- Writing your first Python program

Week 2: Basic Data Types and Operations
- Numbers: integers, floats, and complex numbers
- Arithmetic and comparison operators
- Booleans and logical operators
- Strings: creating, manipulating, and formatting
- Practical exercise: Simple calculator program

Week 3: Data Structures in Python
- Lists: creating, accessing, and modifying elements
- Tuples: immutability and use cases
- Dictionaries: key-value pairs and operations
- Sets: uniqueness and set operations
- Practical exercise: Phonebook application using dictionaries

Week 4: Control Structures
- Conditional statements: `if`, `elif`, `else`
- Loops: `for` loop, `while` loop, and loop control statements
- List comprehensions
- Practical exercise: Number guessing game

Week 5: Functions and Modules
- Defining functions: syntax, parameters, and return values
- Function scope and `global` keyword
- Lambda functions
- Importing and using modules (math, random, etc.)
- Practical exercise: Create a simple Python module with utility functions

Week 6: Error Handling and File I/O
- Introduction to error handling with `try`, `except`, `else`, and `finally`
- Working with files: reading, writing, and appending text files
- Understanding file paths
- Practical exercise: Build a basic text-based task manager

Week 7: Libraries and Packages
- Overview of Python libraries: `math`, `datetime`, and `random`
- Installing packages using `pip`
- Introduction to popular libraries: NumPy for arrays, Pandas for data handling
- Practical exercise: Analyze a small dataset using Pandas and NumPy

Week 8: Data Visualization
- Introduction to data visualization and Matplotlib basics
- Plotting line graphs, bar charts, histograms, and scatter plots
- Customizing plots: titles, labels, legends, and colors
- Practical exercise: Visualize data from a CSV file

Week 9: Object-Oriented Programming (OOP)
- Classes and objects: attributes, methods, and constructors
- Inheritance and polymorphism
- Encapsulation and private variables
- Practical exercise: Create a class for managing employee information

### Additional Resources
- Textbooks: "Python Crash Course" by Eric Matthes, "Automate the Boring Stuff with Python" by Al Sweigart
- Online Resources: Python documentation, Codecademy, freeCodeCamp tutorials
- Practice Platforms: LeetCode, HackerRank, Codewars

This syllabus is designed to build both conceptual understanding and practical skills, providing a solid foundation for more advanced topics like machine learning, or data science.