Introduction to Python Programming for Neuroscientists

Course manual 2024/2025

Course content

This course comprises a basic introduction to Python, designed to be suitable for students with little or no prior programming knowledge. The course consists of introductory lectures and hand-on assignments, with the help and supervision of expert programmers. During the first half of the course the students will be guided to program their first tool to acquire actual neuroscientific data. In the second half students come up with a neuroscientific research question themselves. They will use their new knowledge to create a tool to acquire data to answer this question.

Study materials

Software

• Python

• Visual Studio Code

Objectives

• Demonstrate a basic understanding of Python
• Solve simple programming problems, as they appear in the daily practice of research neuroscientists
• Apply Python knowledge to a problem of data acquisition of behavioural data
• Create a Python programme to gather behavioural data to answer a self-developed hypothesis
• Demonstrate the basics of good coding practice

Teaching methods

• Lecture
• Computer lab session/practical training
• Presentation/symposium
• Self-study
• Working independently on e.g. a project or thesis

Every week starts with a lecture to introduce the topics and guide the students through the most challenging parts.

During computer lab sessions the students can practice what they have learned under supervision and guidance based on assignments.

The course ends with a presentation of the final project to a) practice elevator pitches and b) give the students a better idea on possible applications of their knowledge.

During self-study students have to a) acquire new knowledge and in depth knowledge on their own (the lectures only contain the challenging parts and an overview of the topics) and b) have to finish the assignments that couldn't be finished during the computer lab sessions.

Learning activities

Attendance

Requirements of the programme concerning attendance (OER-B):

1. In the case of practicals, the student must attend at least 80%. Should the student attend less than 80%, he/she must redo the practical, or the Examinations Board may have one or more supplementary assignments issued.
2. In the case of study-group sessions with assignments, the student must attend at least 80% of the study-group sessions. Should the student attend less than 80%, he/she must redo the study group, or the Examinations Board may have one or more supplementary assignments issued.

Assessment

The exam is a on campus exam where students bring their own device. It is not possible to do it remotely.

Inspection of assessed work

The manner of inspection will be communicated via the digitial learning environment.

Assignments

Week 1 & Week 2: short programming assignment in Python

Week 4: code of the visual search task (group) and report about the programming process (group)

Week 7: code, article and elevator pitch about self chosen experiment (group) and report about programming process (group) 

For week 1 and 2 are assignments that are graded on correctness. A short feedback on the most important points will be given on Canvas.

For week 4 and 7 there are rubrics for all parts of the assignments.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Last year's student feedback

The book we used last year was too math based for a lot of students and many exercises lacked the connection with neuroscience. We corrected this this year by mostly changing to the book Python for Biologists and creating more relevant less math based exercises.

Contact information

Coordinator

• dr. Julia Dawitz