Comprehensive Python Programming - Syllabus

Course Overview

This comprehensive Python programming course is designed to take students from complete beginners to intermediate-level programmers. The course emphasizes hands-on learning through practical projects and real-world applications.

Duration: 12-16 weeks (3-4 months) Prerequisites: Basic computer literacy, no prior programming experience required Target Audience: Beginners to programming

Learning Objectives

By the end of this course, students will be able to:

  • Write clean, readable Python code following best practices
  • Understand fundamental programming concepts and data structures
  • Build command-line applications and simple web applications
  • Work with files, databases, and external APIs
  • Debug and test Python programs effectively
  • Use version control with Git and GitHub

Course Structure

Module 1: Python Fundamentals (Weeks 1-2)

Week 1: Getting Started

  • Installing Python and setting up the development environment
  • Introduction to IDEs and text editors (VS Code, PyCharm)
  • Running Python programs
  • The interactive Python shell (REPL)
  • Basic syntax and indentation
  • Comments and documentation

Week 2: Basic Data Types and Operations

  • Variables and naming conventions
  • Numbers (integers, floats, complex)
  • Strings and string methods
  • Boolean values and logical operations
  • Basic input/output with input() and print()
  • Type conversion and type checking

Module 2: Control Structures and Functions (Weeks 3-4)

Week 3: Control Flow

  • Conditional statements (if, elif, else)
  • Comparison and logical operators
  • Loops (for, while)
  • Loop control (break, continue, pass)
  • Nested loops and conditionals

Week 4: Functions

  • Defining and calling functions
  • Parameters and arguments (positional, keyword, default)
  • Return statements and return values
  • Variable scope (local vs global)
  • Lambda functions
  • Built-in functions overview

Module 3: Data Structures (Weeks 5-6)

Week 5: Lists and Tuples

  • Creating and manipulating lists
  • List methods and operations
  • List comprehensions
  • Tuples and their use cases
  • Packing and unpacking

Week 6: Dictionaries and Sets

  • Dictionary creation and manipulation
  • Dictionary methods and operations
  • Dictionary comprehensions
  • Sets and set operations
  • When to use each data structure

Module 4: Advanced Python Concepts (Weeks 7-8)

Week 7: String Processing and Regular Expressions

  • Advanced string manipulation
  • String formatting (f-strings, format method)
  • Introduction to regular expressions
  • Pattern matching and text processing

Week 8: Error Handling and Debugging

  • Understanding exceptions and error types
  • Try-except blocks and exception handling
  • Raising custom exceptions
  • Debugging techniques and tools
  • Writing defensive code

Module 5: Object-Oriented Programming (Weeks 9-10)

Week 9: Classes and Objects

  • Introduction to OOP concepts
  • Creating classes and objects
  • Instance variables and methods
  • Constructor method (__init__)
  • Class vs instance attributes

Week 10: Inheritance and Advanced OOP

  • Inheritance and method overriding
  • Multiple inheritance
  • Special methods (magic methods)
  • Property decorators
  • Class methods and static methods

Module 6: Working with External Resources (Weeks 11-12)

Week 11: File Operations and Data Persistence

  • Reading and writing files
  • Working with CSV and JSON data
  • File paths and directory operations
  • Introduction to databases (SQLite)
  • Pickle for object serialization

Week 12: Libraries and Package Management

  • Installing packages with pip
  • Virtual environments
  • Popular Python libraries overview
  • Importing modules and packages
  • Creating your own modules

Module 7: Web and API Development (Weeks 13-14)

Week 13: Web Scraping and APIs

  • Making HTTP requests with requests library
  • Parsing HTML with BeautifulSoup
  • Working with REST APIs
  • JSON data handling
  • Rate limiting and ethical scraping

Week 14: Web Development Basics

  • Introduction to Flask framework
  • Creating simple web applications
  • Templates and static files
  • Handling forms and user input
  • Basic web security concepts

Module 8: Testing and Best Practices (Weeks 15-16)

Week 15: Testing and Code Quality

  • Writing unit tests with unittest
  • Test-driven development basics
  • Code formatting with Black
  • Linting with pylint or flake8
  • Documentation with docstrings

Week 16: Final Project and Review

  • Version control with Git and GitHub
  • Project planning and structure
  • Code review practices
  • Final project presentation
  • Career guidance and next steps

Assessment Methods

  • Weekly coding assignments (40%)
  • Mid-term project (20%)
  • Final project (30%)
  • Class participation and quizzes (10%)

Projects

  1. Calculator Application (Week 4)
  2. Text-based Adventure Game (Week 8)
  3. Data Analysis Project (Week 12)
  4. Web Scraper (Week 13)
  5. Personal Web Application (Final Project)

Technical Requirements

  • Computer with Python 3.8+ installed
  • Text editor or IDE (VS Code recommended)
  • Git for version control
  • Internet connection for package installation and research

Beginner Level

  1. “Python Crash Course” by Eric Matthes (3rd Edition)
    • Excellent for complete beginners with hands-on projects
    • Covers basics through web development and data visualization
  2. “Automate the Boring Stuff with Python” by Al Sweigart (2nd Edition)
    • Practical approach focusing on automation and real-world tasks
    • Available free online at automatetheboringstuff.com
  3. “Learning Python” by Mark Lutz (5th Edition)
    • Comprehensive coverage of Python fundamentals
    • Detailed explanations of core concepts

Intermediate Level

  1. “Effective Python” by Brett Slatkin (2nd Edition)
    • Best practices and advanced techniques
    • Great for improving code quality
  2. “Python Tricks: The Book” by Dan Bader
    • Intermediate concepts and Python-specific features
    • Clean code practices and design patterns

Reference and Advanced

  1. “Fluent Python” by Luciano Ramalho (2nd Edition)
    • Deep dive into Python’s advanced features
    • For students wanting to master the language
  2. “Python Cookbook” by David Beazley and Brian K. Jones (3rd Edition)
    • Problem-solving recipes and advanced techniques
    • Excellent reference for practical solutions

Web Development Focus

  1. “Flask Web Development” by Miguel Grinberg (2nd Edition)
    • Comprehensive guide to web development with Flask
    • Perfect follow-up for students interested in web development

Data Science Track

  1. “Python for Data Analysis” by Wes McKinney (3rd Edition)
    • Essential for students interested in data science
    • Covers pandas, NumPy, and data manipulation
  2. “Think Python” by Allen B. Downey (2nd Edition)
    • Computer science approach to learning Python
    • Emphasizes problem-solving and thinking like a programmer

Additional Resources

  • Official Python Documentation: https://docs.python.org/
  • Python Package Index (PyPI): https://pypi.org/
  • Real Python: https://realpython.com/
  • Python.org Beginner’s Guide: https://wiki.python.org/moin/BeginnersGuide
  • Stack Overflow for troubleshooting and community support

Fees

This course costs ₹ 25,0000/- , which should be paid at the beginning of the course.