Machine Learning using Python

When: 30 June - 11 July 2025
Where: TBA

Machine Learning using Python

Machine Learning is the Art and Science of learning patterns from data. It includes the most recent LLMs, such as ChatGPT, which have learned the patterns of human language from all the text available online to such an extent as to be a really helpful conversation partner, but also the less visible algorithms that recommend the next show you should watch on Netflix, or which detect when some unusual activity has been happening on your credit card.

Content

In this course, you will get an overview of Machine Learning, starting with a basic introduction to its underlying concepts.

✅ You'll explore the different types of algorithms, their uses, and limitations, and you'll also touch on the most advanced, but computationally demanding vision and language algorithms.
✅ You'll learn how to preprocess data, select models, and evaluate performance, with a focus on hands-on examples.
✅ You'll work with algorithms for regression, classification, and clustering, as well as delve into neural networks and deep learning.
✅ Throughout the course, you’ll build practical skills in Python using libraries like scikit-learn, pandas, and TensorFlow.
✅ You’ll also tackle challenges such as overfitting, feature selection, and hyperparameter tuning.

Result

By the end of the course, you’ll be ready to start applying Machine Learning to your own data for research and analysis. This course aims to build your skills so you can use these models responsibly.

Prerequisites

We assume you are familiar with the modules introduced in the Python for Data-analysis training, being Panda’s Numpy, Matplotlib and Seaborn.

For if you have prior experience but would like to get a refresher on these modules, we’re planning to create a few practice assignments. You can get on-site support at the Research Support Hub in the weeks leading up to the Machine Learning training.

Please note: Machine Learning has a steep learning curve. Expect you’ll need 2-4 hours between sessions to prepare for the next one and plan accordingly. Please be kind to yourself and allow yourself at least 48 hours to complete the course.

Interactive Learning Experience

This course relies heavily on highly interactive (online or hybrid) sessions where we review what you’ve done in the reader. During a review the teacher will share his screen and go through the code asking you by voting and chatting to find the error or complete the code. These reviews are used to rehearse material, show tips and tricks, warn for common mistakes, explain error messages, show how to use the helpfiles and the program (IDE) in general, and overall to motivate you to keep up the pace. Participants report they are highly involved during these sessions and our courses are consistently highly evaluated.

Enrollment and course fee

Fill out this form to enroll

Late enrollments are fine, but please also contact the teacher to not risk being overlooked. You can unenroll until 8 days prior to the first session. The participants will be mailed the course material a few days prior to the course. For more info, you can mail Theo van Mourik
(t.j.van.mourik rug.nl ).

Prices for individuals:

€100 BSc/MSc student at UG, other Dutch University or Hanze Hogeschool
€300 PHD-student at UG or other Dutch University
€650 Employee UG or other Dutch university/UMCG/Hanze Hogeschool
€650 UG Alumni
€1250 Other participants

Prices for groups joining the course:

20 or more PHD’s €200pp (minimum price of €4.000)

10 or more Employees €400 pp (minimum price of €4.000)

20 or more Employees €250 pp (minimum price of €5.000)

5 or more others €1.000 pp (minimum price of €5.000, we’ll also need to send a separate contract for this)

When enrolling a group of participants, you need to report a single financial contact person/kostenplaatsnummer and the mailing addresses of all participants. You can enroll a group with the normal enrollment link.

You can also order a custom course and discuss dates, audience, and content. For more information mail Theo van Mourik (t.j.van.mourik@rug.nl). This is also possible within the curriculum.

Date, time and location

Below are the dates and times of the next Machine Learning using Python (s). The content of these courses is the same each time. If these dates don’t suit you and you want to be notified on future courses please mail me (Theo van Mourik, t.j.van.mourik rug.nl).

July 2025 – 2 week course

This run of the training will be on-site only.
All sessions take 4 hours and take 3-4 hours of preparation each.
All presentations will be recorded and recordings will be available for about 6 months after the course.
You’ll receive a certificate of attendance for attending 5 of 6 sessions or (if you prefer) after completing a final assignment.

Session	Date (9:00-13:00)	Preparation
1	Mon 30 June	TBA
2	Wed 2 July	TBA
3	Fri 4 July	TBA
4	Mon 7 July	TBA
5	Wed 9 July	TBA
6	Fri 11 July	TBA

If you want to be notified on future courses in Python (or R) please mail the coordinator. (Theo van Mourik, t.j.van.mourik rug.nl)

More information

For more information on this or similar courses, please mail the coordinator, Theo van Mourik (t.j.van.mourik rug.nl)

Last modified:

08 January 2025 11.23 a.m.