When

Dec 01, 2021 from 09:00 AM
(Europe/Berlin / UTC100)

Where

Online course

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Speed up Python programs using optimisation and parallelisation techniques

The Python programming language is popular in scientific computing because of the benefits it offers for fast code development. The performance of pure Python programs is often suboptimal, but there are ways to make them faster and more efficient.

On this course, you’ll find out how to identify performance bottlenecks, perform numerical computations efficiently, and extend Python with compiled code. You’ll learn various ways to optimise and parallelise Python programs, particularly in the context of scientific and high performance computing.

What topics will you cover?
  • Performance challenges of Python programming language
  • Performance analysis of Python programs
  • Efficient numerical calculations with NumPy
  • Using compiled code with Python
  • Interfacing Python to libraries written in other programming languages
  • Parallel programming with Python
When would you like to start?

Start straight away and learn at your own pace. If the course hasn’t started yet you’ll see the future date listed below. You can take this self-guided course and learn at your own pace. On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

Who is the course for?

The course is designed for Python programmers who want to speed up their codes. You should be familiar with the basics of the Python programming language.

Enroll here for the course.