WIMEK course in programming with Python (for PhDs)

Course coordinator: dr. A (Antonija) Rimac-van Heerwaarden
Mail to: antonija.rimac@wur.nl or wimek@wur.nl
Lecturers: Jacob van Peet & dr. K.E. Bennin

Scope

Programming can serve multiple purposes. Purposes like developing applications and working with data are also very useful for research. For dealing with these issues, Python offers many libraries. Getting the skills of working with some of these libraries will enable future learning. This can be for more advanced programming applications, but also for self-learning to apply different libraries.

Learning goals

After the course, students should be able to:

• Create a computer program based on a given basic algorithm expressed in plain English;
• Adapt and combine standard algorithms to solve a given problem (includes numerical as well as non-numerical algorithms)
• Detect and repair coding errors in a given piece of programming code
• Use existing libraries taught during the course in programs, e.g., for data manipulation and visualization (Numpy, Pandas and Matplotlib)
• Create useful code commenting for sharing and working together on programs.

Assumed knowledge

The following programming principles, in general and/or in Python:

• Basic types: float, integer, string, list, tuple, dictionary
• Conditionals: if-elif-else structures
• Functional programming
• Iterating: loops for a known and an unknown number of iterations
• Text formatting: string formatting
• File handling: reading to and writing from txt-files

This is reflected in the following materials: 'Think Python' chapters 1 through 14

Study materials

Textbook (for preparation):
'Think Python, how to think like a computer scientist', by Allen B. Downey, available on-line at: https://greenteapress.com/wp/think-python-2e

Also available as printed book: 2nd edition by O'Reilly, ISBN: 978-1-491-93936-9. There will be a number of copies available in the WURshop (StudyStore) for about 39 EUR.

Software:

• PyCharm and Anaconda

Principal themes

Software libraries (modules). Modern programming languages consist of a relatively small core and many additional parts. Those additional parts are called libraries or (especially in Python) modules. The course teaches how to use a number of the modules that come with Python, and also how to define your own modules.

Some of the most relevant libraries have to do with data. In particular, dealing with array-like data is possible in Python, but the mathematical capabilities are limited. Using Numpy allows more efficient and intuitive use of array-like data. Many data formats are tabular, such as excel files, cv-files, json-files. Dealing with these kinds of data in Python is easily done using pandas.
Using pandas allows easy data manipulation and a link to Python, which means programming functionalities can be used on such data files.
Visualizing data unlocks value and insight data written or tabular data can not. Using Pyplot, many visualization options are available. Being familiar with this library enables the making of proper plots and is also a stepping stone to the use of more advanced plotting libraries.

Outline of the course

• Day 1: Programming for research and data science introduction (morning). Refresher on basic principles of programming (in Python) (afternoon).
• Day 2: Data structures and data sources (morning). Array-like (numpy) and tabular (pandas) data (afternoon).
• Day 3: Data manipulation and handling (numpy and pandas) (morning) and data visualization (pyplot) (afternoon).
• Day 4: Debugging and Error handling in Python (morning). Recap and assignment for handing in (afternoon).
• Day 5: Introduction to Machine learning: train a basic model, examine and evaluate its performance, and apply it for your research.
• Day 6: Bring your code. Discussing the relevant programming problems of course participants. Introduction and group discussions (morning) and plenary discussions and processing of findings (afternoon).

Activities

Days one, two, three and four will be split up in the morning (9.00 – 12.00) and afternoon (13.30 – 17.00). Each day part will be structured as follows: short lecture on the topic (±30 min), a class exercise on the topic (±60 min), and individual assignments (± 2.5 hours). During the class exercises an assignment will be done together with all participants. During the final day, a mix of plenary and group discussions combined with individual work time to work on brought in problems will be offered. Supervision will be available during all six days to offer support when needed. The course will be spread over two weeks: 3 full days in the first week and 3 full days in the second week.

Assessment

During the fourth day, one of the assignments made during the afternoon and will be graded using criteria specified for that assignment. Also a pass-fail structure will be applied on the attendance. A passing grade (>5.5) and a pass on attendance will be resulting in a passing grade for this course. 

The use of generative artificial intelligence to create ready-made content in assignments is considered fraud.

General information

Registration

• Early bird registration deadline: 13 December, 2026 
• Regular registration deadline: 11 January 2027.

Click here to start your registration. Please note that you must be ready to pay. There you will fill out your information and decide on your payment method. As WUR PhD candidate you can pay via the project number (unless you are associated with an institute and they are paying, then you can pay via the invoice option). 

When clicking the project number option, you will be required to enter your Project Number and Cost Center Code (Kostenplaats in Dutch).

If you have questions about what this numbers should be, please check with the MOA of your chair group. All payments for this course are expected to be completed via this process, and not via ProQme. 

If questions persist, please reach out to us at wimek@wur.nl

IMPORTANT: Please note that your registration is confirmed only when your payment has been completed.

Course duration

6 full days spread over 2 weeks.

Credit points

1.8 ECTS

Language

English

Group size

20-30 people

Frequency

Once per year.

Fee

The course fee includes coffee, tea and lunch on all 6 days.

The fee does not include accommodation, breakfast or dinner. Accommodation is not included in the fee of the course, but there are several possibilities in Wageningen. For information on B&B’s and hotels in Wageningen please visit proefwageningen.nl/overnachten. Another option is Short Stay Wageningen. Furthermore, Airbnb offers several rooms in the area. Note that besides the restaurants in Wageningen, there are also options to have dinner at Wageningen Campus.

Reminder: Are you within the first six months of your PhD and you don't have your TSP approved yet? Within the first six months or your project you have the right to a discounted fee nevertheless. Therefore, you can select the fee with TSP even if you don't have one, as long as you are within that first period of your trajectory. 

Cancellation conditions

• Up to 4 (four) weeks prior to the start of the course (before December 28), cancellation is free of charge.
• Up to 2 (two) weeks prior to the start of the course (before January 11), the fee of €150,- will be charged.
• In case of cancellation within less than two weeks to the start of the course, or if you do not show at all, the full course fee will be charged. 
• If a cancellation comes between Friday at 15:00 and Monday 10:00, we treat it as if it was sent on Monday at 10:00. Please keep this in mind.

Note: If you would like to cancel your registration, ALWAYS inform us. By NOT paying the participation fee, your registration is NOT automatically cancelled (and do note that you will be kept to the cancellation conditions).

Also note that when there are not enough participants, we can cancel the course. We will inform you if this is the case a week after the early bird deadline. Please take this into account when arranging your trip to the course (I.e. check the re-imburstment policies).