Teaching
Programming in Python

Programming in Python

Python programming with a comprehensive curriculum!

PLAYPEN offers Cambridge 4162: Programming in Python, a course designed to equip students with the skills to develop applications ranging from small scripts to large systems. Students will explore Python’s extensive standard library and its applications in various domains.

Course Outline

1. Introduction to Python

  • Overview of Python programming language.
  • Setting up the development environment.
  • Writing and executing basic Python scripts.

2. Python Basics

  • Variables, data types, and operators.
  • Control structures: conditionals and loops.
  • Functions and modules.

3. Data Structures

  • Lists, tuples, and dictionaries.
  • Sets and their operations.
  • Comprehensions and generators.

4. File Handling

  • Reading from and writing to files.
  • Working with different file formats.
  • Exception handling during file operations.

5. Object-Oriented Programming (OOP) in Python

  • Classes and objects.
  • Inheritance, polymorphism, and encapsulation.
  • Magic methods and operator overloading.

6. Modules and Packages

  • Importing and using standard libraries.
  • Creating and managing custom modules.
  • Understanding package structures.

7. Error and Exception Handling

  • Handling exceptions using try-except blocks.
  • Creating custom exceptions.
  • Debugging techniques and tools.

8. Testing and Debugging

  • Writing unit tests using frameworks like unittest.
  • Test-driven development practices.
  • Debugging tools and best practices.

9. Working with Databases

  • Connecting to databases using libraries like sqlite3.
  • Performing CRUD operations.
  • Using Object-Relational Mappers (ORMs).

10. Web Development with Python

  • Introduction to web frameworks like Flask or Django.
  • Building simple web applications.
  • Handling HTTP requests and responses.

11. Networking and Multithreading

  • Socket programming basics.
  • Creating client-server applications.
  • Understanding multithreading and multiprocessing.

12. Advanced Topics

  • Introduction to data analysis with libraries like NumPy and pandas.
  • Basics of machine learning with scikit-learn.
  • Exploring Python’s role in automation and scripting.

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