Enroll Course: https://www.udemy.com/course/master-parallel-concurrent-programming-using-python2-in-1/
Are you looking to unlock the full potential of your Python code by harnessing the power of parallel and concurrent programming? Look no further than Udemy’s “Master Parallel & Concurrent Programming Using Python: 2 in 1” course. This comprehensive offering is designed to demystify the often-confusing world of multithreading and multiprocessing, making it accessible even to experienced developers.
This 2-in-1 course expertly guides you through the intricacies of concurrent and parallel processing in Python. You’ll start by building a solid foundation in parallel computing, delving into Python’s fundamental concepts. The first part of the course focuses on thread-based parallelism, where you’ll master the Python `threading` module, learning essential synchronization techniques like locks, mutexes, semaphores, queues, and understanding the Global Interpreter Lock (GIL) and thread pools.
Next, you’ll transition to process-based parallelism, exploring how to synchronize processes using message passing and evaluating the performance of MPI Python Modules. The course doesn’t stop there; it also introduces asynchronous parallel programming with Python’s `asyncio` module, covering exception handling and exploring distributed computing with Python, including setting up brokers and creating workers with the Celery module.
The second course included in this bundle sharpens your skills in various aspects of concurrent programming. You’ll learn the principal approaches to concurrency that Python offers, along with the necessary libraries and tools to leverage your processor’s performance. The course provides a clear understanding of the basic theory and history of parallelism, equipping you to choose the most effective approach for your parallel processing needs.
What sets this course apart is its practical, real-world examples that solidify your understanding. Furthermore, it offers hands-on experience with GPU programming using the PyCUDA module, allowing you to evaluate performance limitations and push the boundaries of your applications.
Authored by Giancarlo Zaccone, a physicist with extensive experience in scientific computing, and BignumWorks Software LLP, a reputable Indian software consultancy, this course is backed by robust expertise. Whether you’re looking to speed up computationally intensive tasks, build more responsive applications, or simply gain a deeper understanding of modern programming paradigms, this course is an invaluable resource. Highly recommended for anyone serious about optimizing their Python development.
Enroll Course: https://www.udemy.com/course/master-parallel-concurrent-programming-using-python2-in-1/