Program Overview

Program Overview

The Python Crash Course (for Beginners) is an online course designed for doctoral candidates and postdocs with little or no prior programming experience. The course aims to introduce the fundamental tools needed to begin programming in Python, covering core concepts and practical techniques.

Course Details

• Dates: The course will take place on the following dates:
  • Monday, March 2, 2026, 08:30 - 12:30
  • Tuesday, March 3, 2026, 08:30 - 12:30
  • Monday, March 9, 2026, 08:30 - 12:30
  • Tuesday, March 10, 2026, 08:30 - 12:30
• Registration:
  • Registration begins on January 21, 2026, at 09:00
  • Registration ends on February 2, 2026, at 12:00
• Cost: The course is free of charge for doctoral candidates and postdocs of the University of Basel.
• Instructor: Maxim Samarin, Senior Data Scientist at the Swiss Data Science Center, with a PhD in Computer Science/Machine Learning and over six years of experience teaching Python courses.

Course Objectives

The course is designed to provide participants with a strong foundation in Python programming, enabling them to write simple programs confidently. The objectives include understanding Python's popularity, getting started with JupyterLab, defining and working with variables, exploring essential data structures, and leveraging key Python libraries for data handling, analysis, and visualization.

Course Content

The course will cover the following topics:

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

Target Audience

The course is designed for all doctoral candidates and postdocs.

Course Format

• The course will be conducted online via Zoom.
• Participants will work with Jupyter notebooks, and course material will be made available in advance.
• A dual-monitor setup is recommended for the best experience.
• Breakout rooms will be used for exercises, enabling participants to collaborate and solve tasks together.

Workload

• Course attendance: 16 hours
• Preliminary work: 2 hours

Special Conditions

• Once registration is open, applications will be collected for 24 hours, and course places will be allocated by lot.
• All registrations received after the initial 24-hour 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 email.
• Full course attendance is mandatory, and participants who fail to attend without prior notification or withdraw after the registration deadline are subject to a fee.