Advanced Skill Test: Python Professional Level 2 (PCPP2™)

Description

The Python Professional Level 2 (PCPP2™) course is an advanced, hands-on training program designed for Python developers who want to take their programming skills to the next level. Whether you're aiming to earn the PCPP2™ certification or simply advance your knowledge of professional Python development, this course covers the most crucial concepts required for tackling complex programming challenges. The course focuses on mastering advanced Python topics such as design patterns, concurrency, network programming, optimization, and database interaction. By the end of the course, you'll be equipped to design, develop, and optimize high-performance Python applications for real-world use cases.

Who This Course Is For

This course is ideal for developers who have a solid foundation in Python and are looking to deepen their knowledge in advanced programming techniques. If you're an experienced Python developer, software engineer, backend developer, data scientist, or IT professional looking to master the complexities of Python development, this course is for you. The course also prepares you for the PCPP2™ certification exam, making it the perfect choice for those aiming to validate their Python expertise.

Course Prerequisites

Before starting this course, students should have a good understanding of Python's core features and functionality. Ideally, you should be familiar with the topics covered in the PCPP1™ certification, which includes knowledge of object-oriented programming, file handling, Python libraries, and working with basic algorithms. This course builds upon that foundational knowledge and dives into more advanced areas such as design patterns, concurrency, networking, and optimization.

Course Overview

The course covers a broad spectrum of advanced Python concepts that are essential for professional developers. You’ll learn how to leverage Python’s most powerful features to write efficient, scalable, and maintainable code. The topics are broken down into several key modules that provide a comprehensive approach to mastering professional Python programming.

Module 1: Advanced Object-Oriented Programming (OOP)

In this module, we focus on advanced object-oriented programming concepts that are fundamental for creating scalable and maintainable applications. You'll explore the following topics:

• Metaclasses: Learn how metaclasses control the creation and behavior of Python classes, and when to use them for advanced use cases.

• Abstract Base Classes (ABCs): Implement abstract base classes and abstract methods to enforce consistent interfaces and class behavior.

• Multiple Inheritance: Gain a deeper understanding of multiple inheritance in Python, and how to manage method resolution order (MRO) issues.

• Design Principles: Apply SOLID principles in your code to improve maintainability, readability, and scalability of Python applications.

Module 2: Design Patterns

Design patterns are proven solutions to recurring problems in software design. This module introduces you to key design patterns that will help you write efficient and reusable code:

• Creational Patterns: Explore patterns like Singleton, Factory, and Builder, which deal with object creation and initialization.

• Structural Patterns: Understand patterns such as Decorator and Adapter, which allow you to alter the structure of your application without modifying existing code.

• Behavioral Patterns: Study patterns like Observer, Command, and Strategy to manage object behavior and interactions in complex systems.

Module 3: Concurrency and Parallelism

Python’s ability to handle concurrency and parallelism is crucial for building high-performance applications. In this module, we cover:

• Multithreading: Learn how to implement threading to allow multiple threads to run in parallel and handle I/O-bound tasks more efficiently.

• Multiprocessing: Discover how to use Python’s multiprocessing module to split CPU-bound tasks across multiple CPU cores, improving performance in computation-heavy applications.

• Async Programming with asyncio: Gain an understanding of asynchronous programming and how to use the asyncio library to write non-blocking, concurrent code.

• Synchronization: Learn how to safely share data between threads and processes using synchronization mechanisms like locks, semaphores, and condition variables.

Module 4: Network Programming

Python excels at network programming, making it ideal for developing applications that interact with remote servers, APIs, and other networked systems. This module covers:

• Socket Programming: Learn how to use the socket module to build networked applications, such as creating client-server communication systems and handling connections.

• HTTP Requests: Master the use of the requests module to interact with web services and APIs, including handling GET, POST, PUT, and DELETE requests.

• Secure Communication: Implement secure communication protocols (SSL/TLS) to encrypt network traffic and protect sensitive data.

• Web Frameworks: Get an introduction to web frameworks like Flask and Django, and learn how to build simple APIs or web applications.

Module 5: Database Interaction

Python is widely used for building applications that interact with databases. In this module, you'll learn how to:

• SQL and NoSQL Databases: Work with both SQL databases (such as PostgreSQL and MySQL) and NoSQL databases (like MongoDB), writing efficient queries and managing connections.

• Object-Relational Mapping (ORM): Understand how to use ORM libraries like SQLAlchemy to map Python objects to database tables, making it easier to interact with databases in an object-oriented way.

• Database Transactions: Learn about transactions, rollbacks, and ensuring database consistency in multi-user environments.

Module 6: Optimization Techniques

Optimizing your Python code is critical when working with large datasets or building performance-critical applications. In this module, you'll focus on:

• Profiling and Benchmarking: Use tools like cProfile and timeit to identify bottlenecks in your code and measure performance improvements.

• Memory Management: Learn about Python’s memory model and techniques for optimizing memory usage in large-scale applications.

• Algorithm Optimization: Refactor algorithms to improve performance, and understand how to select the best data structures and algorithms for various use cases.

Module 7: Testing and Debugging

Testing and debugging are crucial parts of software development. In this module, you’ll learn:

• Unit Testing: Understand how to write unit tests using unittest and pytest, and explore test-driven development (TDD) to improve code quality.

• Mocking and Fixtures: Use mocking and fixtures to isolate components and test your code effectively.

• Advanced Debugging: Master debugging tools like Python’s pdb and PyCharm’s built-in debugger to troubleshoot complex applications.

Learning Objectives

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

• Implement advanced object-oriented programming techniques, including metaclasses and abstract base classes.

• Apply design patterns to create efficient, reusable, and maintainable code.

• Work with Python's concurrency and parallelism tools to build high-performance applications.

• Develop networked applications, interact with APIs, and implement secure communication.

• Connect to databases using SQL and NoSQL solutions and manage data efficiently.

• Optimize your Python code for better performance, memory usage, and scalability.

• Write and maintain high-quality, testable code using best practices for testing and debugging.

Course Info