Course Description:

The Python Advanced course is designed to provide students with an in-depth understanding of advanced Python programming concepts and techniques. The course builds upon the foundational knowledge of Python and covers advanced topics such as object-oriented programming, data structures, algorithms, and advanced libraries and frameworks. Students will learn how to write efficient and scalable Python code, design and implement complex data structures, and leverage advanced Python libraries for various applications. The course also covers best practices for code organization, testing, and debugging.

Course Objectives:

1. Build upon foundational Python knowledge and develop advanced programming skills.
2. Understand and apply object-oriented programming principles in Python.
3. Learn advanced data structures and algorithms for efficient problem-solving.
4. Explore and utilize advanced Python libraries and frameworks.
5. Develop skills in code organization, testing, and debugging.
6. Apply advanced Python concepts to real-world projects and effectively communicate the results.

Course Outline:

Module 1: Object-Oriented Programming in Python

– Review of object-oriented programming concepts
– Classes, objects, and inheritance in Python
– Polymorphism and encapsulation

Module 2: Advanced Data Structures and Algorithms

– Advanced data structures (e.g., linked lists, stacks, queues, trees, graphs)
– Algorithm analysis and complexity
– Sorting and searching algorithms

Module 3: Functional Programming in Python

– Lambda functions and higher-order functions
– List comprehensions and generators
– Functional programming techniques

Module 4: Advanced Python Libraries and Frameworks

– NumPy for numerical computing and array manipulation
– Pandas for data manipulation and analysis
– Matplotlib and Seaborn for data visualization
– Flask or Django for web development

Module 5: Concurrency and Parallelism

– Multithreading and multiprocessing in Python
– Asynchronous programming with asyncio

Module 6: File Handling and Input/Output Operations

– Reading and writing files in different formats (e.g., CSV, JSON, XML)
– Working with binary files and serialization

Module 7: Testing and Debugging

– Unit testing and test-driven development (TDD)
– Debugging techniques and tools
– Error handling and exception handling

Module 8: Code Organization and Best Practices

– Modular programming and code organization
– Documentation and code commenting
– Code style and best practices (e.g., PEP 8)

Module 9: Advanced Topics in Python

– Regular expressions and pattern matching
– Decorators and metaprogramming
– Context managers and resource management

Module 10: Real-World Applications and Projects

– Applying advanced Python concepts to real-world projects
– Hands-on projects and simulations to reinforce learning