Python Crash Course (for Beginners) ONLINE

Aims

Python is a programming language that makes it easy to enter the world of programming. This course is aimed at people with little to no programming experience. Starting from the basics, we successively approach more advanced programming concepts. We will learn how to write small computer programs and do computations, analyses, and plots with Python. Since programming is mostly "learning by doing", you will complete and execute small program snippets during the course. After this course, you will be able to write simple programs and possess a basis to delve further into programming in Python.

Content

With this workshop we want to provide an overview of the essential tools to start programming in Python. We cover the following topics in the course:
1. Why so popular: Python vs. other programming languages
2. Working with Jupyter Lab
3. How to define variables and work with them
4. Different data structures: Lists, strings, dictionaries, and others
5. “IF – ELSE”: How to use conditional statements
6. Performing repetitive tasks with iterations
7. Useful Python libraries to read in, plot, and analyse data:
NumPy, Pandas, Matplotlib, Seaborn
8. How to define own functions
9. “Real” examples of scripts in Python using SciPy and scikit-learn
The presentation and explanation of concepts is intended to be accessible to participants who have had little to no contact with programming so far.

Methods

We will make use of Jupyter notebooks in this course. The course material is going to be provided prior to the course. Participants can use their own computers on the course days. Videos on how to install your own Python environment will be shared prior to the course. As an alternative, online services can be used which allow running Python scripts within a browser (no further installations required). A setup with two monitors (one to follow the presentation and another to work with the course material) is advisable.

As a central part of the course, the instructor will present different programming concepts and participants will be able to examine and adjust the course scripts themselves. We will make use of breakout rooms for the Python exercises, in which participants can exchange and solve exercises jointly.

Target Group

All Doctoral Candidates & Postdocs

About the Trainer

Maxim Samarin is a Senior Data Scientist at the Swiss Data Science Center. Maxim holds a PhD in Computer Science / Machine Learning and has more than four years of experience teaching Python courses.

Workload

Course attendance 16h, preliminary work 2h

Feature

Once registration is open, applications will be collected for 24 hours and course places allocated by lot. All registrations received after the initial 24h period will be put on a waiting list and assigned on a first come, first served basis.

Course places/places on the waiting list will be confirmed by e-mail. Course registrations can only be canceled before the registration period ends (send an e-mail to grace@unibas.ch). Full course attendance is mandatory. Participants who fail to attend a course without prior notification or withdraw after the registration deadline are subject to a fee of CHF 30. In addition, participants who cancel their course registration at a later point in time, are absent without an excuse or do not attend the entire course will, for reasons of fairness, not be considered for course registration in the following semester and will be removed from other courses offered in the same semester. Please find the detailed regulations on the Transferable Skills Homepage.