February 2019
Intermediate to advanced
4h 12m
English
Closed Captioning available in English
Overview
In this 4-hour course, you'll dive into the art of high-performance computing using Python 3.x. By mastering techniques like parallel programming, distributed computing, and code optimization, you'll gain the ability to build fast, efficient, and scalable Python applications. This course combines theory and hands-on practice to ensure you grasp the core concepts and tools for success.
What I will be able to do after this course
- Master using NumPy, SciPy, and Cython to boost the performance of numerical computations.
- Gain expertise in Python's multiprocessing and multithreading modules for efficient parallelism.
- Learn to leverage Dask for distributed data processing and handling large data workloads.
- Optimize code performance using tools like Numba and advanced Python programming techniques.
- Develop robust and scalable reactive applications using Python programming paradigms.
Course Instructor(s)
Your instructor, Mohammed Kashif, brings years of experience in high-performance computing and Python programming. Having contributed to computational problem-solving in various industries, Mohammed enthusiastically shares his in-depth knowledge and practical insights. His teaching approach focuses on simplifying complex concepts and reinforcing learning through hands-on practice.
Who is it for?
This course is designed for Python programmers, data analysts, and aspiring data scientists who already have basic Python knowledge. If you're looking to improve the speed and efficiency of your Python code, scale your programming to handle larger datasets, or explore tools for high-performance computing, this course is for you.
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