Data Science Education Materials
On this page, you will find links to files accompanying WDCC courses and trainings. Find your course or training below to download presentations, documents and other files.
Machine Learning
![Machine Learning.png Machine Learning.png](/upload_mm/e/6/1/eaf8808b-c8db-466a-a70b-d0861fd719f2_Machine%20Learning_d6918268_239x135.png)
Lecture by Paul van Leeuwen, Rutger Vlek and Ron Wehrens. The lectures took place on October 26, 2020 at WUR as part of Knowledge Management project, part of KB program ‘Data Driven and High Tech’ (DDHT)
Programme:
During the workshop four topics will be introduced will be introduced and will be followed by a discussion:
Topic 1: Overview of Machine Learning methods (Rutger Vlek)
Topic 2: Validation and tuning of ML methods (Ron Wehrens)
Topic 3: Preprocessing, visualisation and quality of data (Paul Van Leeuwen)
Topic 4: Incorporating prior knowledge (Paul van Leeuwen and Rutger Vlek)
Personal Data
![Personal Data in Research.png Personal Data in Research.png](/upload_mm/8/1/2/0521cb3a-046f-4ce1-a681-cdc3b8e10098_Personal%20Data%20in%20Research_2d428d1a_239x161.png)
Lecture by Dr. Jacques Flores Dourojeanni
Dr. Jacques P. Flores Dourojeanni discusses the basic principles of the GDPR and how they apply to research data. The workshop aims to explain how one can become compliant whilst collecting personal data, taking into account the derogations that exist for research purposes. In this workshop you will learn to recognize personal and sensitive personal data, understand the legal basis for collection, as well as how to formulate informed consent forms. Furthermore, this workshop also covers diverse security and privacy measures that can be taken to protect the privacy of your data subjects. These include pseudonymization, anonymization and encryption amongst others.
Vision on Data Science and AI at WUR
![Vision on Data Science and AI at WUR.png Vision on Data Science and AI at WUR.png](/upload_mm/a/d/9/140703ce-b253-4cfd-a89b-f99ed3177675_Vision%20on%20Data%20Science%20and%20AI%20at%20WUR_7aa94fd9_239x117.png)
In this panel discussion we relate research questions from the WUR domains with (im)possibilities in the fields of AI and data science. Too often these different disciplines have difficulties in understanding each other, if they meet at all. With this workshop we aim to connect leaders from the WUR domains with researchers in the digital disciplines.
Our panel consists of 5 programme leaders of the Knowledge Base programmes:
- Saskia Visser
- Ivo Demmers
- Lawrence Jones-Walters
- Gulden Yilmaz
- Willem Jan Knibbe
Interoperability
![Interoperability.png Interoperability.png](/upload_mm/a/e/5/a6fba326-ef53-4506-9614-4336cbad468f_Interoperability_d79cb948_239x117.png)
This short interactive webinar on the topic of the FAIR data component of Interoperability was designed for our WUR Data Stewards and researchers from the KB programme Data Driven & High Tech.
- Welcome by Jan Top
- Presentation by Lieke Melsen on how she integrates interoperability into her research on hydrological modelling (20 min). See Lieke’s work
- Presentation by Maarten Voors on how he integrates interoperability into his research on household behaviour in African countries (20 min)
- Introduction on interoperability, linked data concept, and tools (WDCC, Erik van den Bergh) (15 minutes)
National AI Course
![De Nationale AI cursus.png De Nationale AI cursus.png](/upload_mm/d/1/c/f367942a-0997-44ad-80d5-f03fe58c2062_De%20Nationale%20AI%20cursus_86b022e1_239x172.png)
The aim of the course is to prepare Dutch society for the future with AI by getting participants acquainted with basic principles, techniques, rules and regulations of artificial intelligence. The course is available fully online in Dutch and English. It consists of 8 modules and 36 documents to read optionally. The duration of the whole course is 4-6 hours and participants receive a certificate upon completion of the course. The course has been founded by the AI for GOOD foundation, the knowledge centre ICAI, and the company RMMBR.com and is freely available to anyone interested in AI.
Elements of AI
![Elements of AI.jpg Elements of AI.jpg](/upload_mm/e/f/d/5fc622c2-c972-402e-8cb4-952e0b31d9f7_Elements%20of%20AI_0fdafad0_239x239.jpg)
The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace.
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