Python Crash Course (for Beginners) ONLINE

Aims

Python is a versatile programming language that offers an accessible entry point into the world of coding. This course is designed for people with little or no prior experience. We begin with the fundamentals and gradually progress to more advanced concepts. Along the way, you will gain hands-on practice by writing small programs and you will see how to perform computations, conduct analyses, and create plots with Python. Because programming is best learned through “learning by doing”, you will complete and run code snippets throughout the course. By the end, you will be able to write simple programs confidently and will have built a strong foundation for further exploration of Python programming.

Content

We aim to introduce the fundamental tools you need to begin programming in Python. We will explore core concepts and practical techniques, covering topics such as:

1. Understanding Python’s popularity compared to other programming languages
2. Getting started with JupyterLab
3. Defining and working with variables
4. Exploring essential data structures: lists, strings, dictionaries, and more
5. Using conditional statements (“if-else”)
6. Performing repetitive tasks with iterations (e.g. for loops)
7. Leveraging key Python libraries for data handling, analysis, and visualisation: NumPy, Pandas, Matplotlib, Seaborn
8. Writing your own functions
9. Applying Python to real-world examples with SciPy and scikit-learn
10. Continuing programming with advanced coding environments and AI-based assistance: Spyder, PyCharm, GitHub Copilot

The course is designed to be accessible to participants with little or no prior programming experience.

Methods

Throughout the course, we will work with Jupyter notebooks. Course material will be made available in advance, and participants can use their own computers during the course days. Videos on setting up an own Python environment will be shared beforehand. Alternatively, participants may use the online platform Renku to run Python directly in the browser, requiring no installation. For the best experience, a dual-monitor setup is recommended (one screen to follow the presentation and another to work with the course material).

A key element of the course is the instructor’s live presentation of programming concepts, during which participants will have the opportunity to explore, modify, and experiment with the provided scripts. We will use breakout rooms for the exercises, enabling participants to collaborate, exchange, and solve tasks together.

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 over six 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.