People studying Chemistry, Biology, Physics, Life Sciences and a whole lot of other sciences will have a lot of need in processing and analyzing the data they collected. This involves a lot of manual work, but plenty of this can be automated. There are many ready-made applications that can handle some of the computations, but there are even more that need special treatment.

This course was designed to be given at the Weizmann Institute of Science in Rehovot, Israel. It includes a basic Python course with specific extensions for scientific computational needs. It also touches other areas of programming that can help scientists to use software the best possible way they can.

The recordings include clarifying questions and the solution of the exercises by Nóra Doleschall.

The slides used during the recording are available here. Since the recording was mate some of the slides were updated, hopefully improved. Don't be alarmed if they are not exactly the same as in the video.

What to watch and in which order to watch?

The videos are in the order we recorded them. They are more-or-less along the lines of the chapters, except at the beginning where some chapters are split into multiple videos and some videos contain parts from multiple chapters.

• There are timestamps on this page pointing you where each sections starts.
• Many sections contain discussions about solving the exercises. I think they can be very useful after you solved the respective exercise, but you can learn the material without them too.
• Part 40 is towards the end, but it can give you a lot of background about programming so you might want to watch it early.
• The Tk video (Part 30) is extra, you don't necessarily need it to complete the course.
• The PyCharm chapter is Part 34, but you might want to watch it earlier, maybe as soon as after Part 10, and then switch to use PyCharm instead of Notepad++
• The Jupyter notebook is Part 42, you might want to watch it earlier. Maybe before SciPy in Part 37.