Advanced Python Programming
Course Summary:

The Advanced Python Programming course offered by Magna Skills is designed for experienced Python developers who want to deepen their understanding and proficiency in the language. This course covers advanced topics, best practices, and techniques for leveraging Python's powerful features to develop complex applications, solve challenging problems, and optimize performance.

Course Objectives:

  1. Advanced Language Features: Explore advanced Python language features such as generators, decorators, context managers, and metaprogramming techniques to write more concise, efficient, and expressive code.

  2. Concurrency and Parallelism: Learn how to leverage Python's concurrency and parallelism capabilities using libraries like asyncio, threading, and multiprocessing to develop scalable and high-performance applications.

  3. Advanced Data Structures and Algorithms: Dive into advanced data structures and algorithms implemented in Python, including graph algorithms, dynamic programming, and advanced sorting and searching techniques.

  4. Pythonic Design Patterns: Understand Pythonic design patterns and idiomatic approaches to software design, including object-oriented design patterns, functional programming concepts, and code organization principles.

  5. Performance Optimization: Discover strategies for optimizing Python code performance, including profiling, code optimization techniques, and leveraging C extensions and libraries for computationally intensive tasks.

Course Outline

Module 1: Advanced Language Features

  • Generators and iterators
  • Decorators and context managers
  • Metaprogramming with metaclasses

Module 2: Concurrency and Parallelism

  • Asynchronous programming with asyncio
  • Multithreading and multiprocessing
  • Parallel computing with concurrent.futures

Module 3: Advanced Data Structures and Algorithms

  • Graph algorithms and network analysis
  • Dynamic programming and memoization
  • Advanced sorting and searching techniques

Module 4: Pythonic Design Patterns

  • Object-oriented design patterns (e.g., Singleton, Factory)
  • Functional programming concepts (e.g., map, filter, reduce)
  • Design patterns for clean and maintainable code

Module 5: Performance Optimization

  • Profiling and benchmarking Python code
  • Optimization techniques (e.g., memoization, vectorization)
  • Using C extensions and libraries for performance-critical tasks

Module 6: Advanced Libraries and Frameworks

  • Deep learning with TensorFlow or PyTorch
  • Web development with Django or Flask
  • Data science with pandas, NumPy, and scikit-learn

Module 7: Testing and Debugging

  • Unit testing and test-driven development (TDD)
  • Debugging techniques and tools (e.g., pdb, logging)
  • Continuous integration and automated testing pipelines

Module 8: Deployment and Scalability

  • Packaging and distributing Python applications
  • Containerization with Docker
  • Scalability considerations for distributed systems

Module 9: Security and Best Practices

  • Secure coding practices and vulnerabilities
  • Handling sensitive data and encryption
  • Compliance with industry standards and regulations

Module 10: Real-world Applications and Case Studies

  • Building complex applications and systems using advanced Python techniques
  • Analyzing real-world case studies and examples of Python in action

The Advanced Python Programming course equips experienced Python developers with the knowledge and skills to tackle complex challenges, optimize performance, and develop high-quality applications using Python. Through a combination of in-depth theoretical learning, hands-on exercises, code reviews, and real-world applications, participants will gain the expertise needed to become proficient Python developers capable of building scalable, maintainable, and efficient software solutions