Introduction to machine learning
Introduction to machine learning

Introduction to Machine Learning with R and R studio (RSS4.05) - Confirmed

Machine learning currently enjoys renewed attention due to more powerful computers and advanced algorithms. The course will introduce you to various techniques of machine learning and how R and Rstudio can be used to perform both supervised and unsupervised techniques of this specific type of learning

Duration: one-week.

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General

The application deadline has passed, applying is no longer possible

During this course you will learn about the entire process from creating datasets to the evaluation of the output and interpretability of Machine Learning models. 

After participation in this course, you will be able to use R and Rstudio to perform machine learning and to decide which type of machine learning technique is best for a given classification or predictive research problem. Furthermore, you will understand how to setup a Machine Learning project from start to end and the possibilities and limitations of different Machine Learning techniques. Finally you will be able to assess ethical issues involved in machine learning. 

Starting date

08 July 2024, 9 am
Costs
€600
Educational method
On-site
Main Language
English
Sessions
08 July 2024, 9 am - 12 July 2024, 5 pm
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Teacher(s)
Dr M.R.M. Vergeer (Maurice)
Unique code
RSS4.05

Factsheet

Type of education
Course
Entry requirements
See the requirements in cost and admission
Study load (ECTS)
2
Result
Certificate
Organisation
Radboud Summer School

Startdate: 08 July 2024, 9 am - 12 July 2024, 5 pm
ECTS credits: 2 ECTS. For more information see credits and certificate.

Course programme

The course will start with a short refresher on how to use R and Rstudio, after that a you will be taught different classes of Machine Learning. Furthermore, you will be introduced to both supervised and unsupervised techniques, how and when to use these techniques, and finally you will learn about text analysis and ethical issues in Machine learning.

  • Weekly schedule and social events

    The weekly programme of Radboud Summer School is carefully designed for the best experience. On this page you will find the timetables and social events.

Watch what our participants say about their experience!

Course list

Overview courses and discplines

Course list
Communication, Marketing and Media

Communication, Marketing en Media

Cursusoverzicht
Maurice Vergeer

dr. M.R.M. Vergeer (Maurice)

Maurice Vergeer is an expert on social media. His research focuses on how political actors use the internet during election campaigns. Furthermore, he studies how journalists use the internet in their daily work. His work uses quantitative research methods applied on large data sets. His work gets published in highly-ranked academic journals. 

The application deadline has passed, applying is no longer possible

 

Costs

  • Regular: €600 (application deadline 31st of May) 

Includes: your course, coffee and tea during breaks, a warm lunch every day, Official Opening, Official Closing (with some drinks and snacks). 

Excludes: transport, accommodation, social events and other costs.  

Discounts and Scholarships

Admission

Level of participant: 

  • Advance Bachelor
  • Master
  • PhD
  • Postdoc
  • Professional

Admission requirements: A basic understanding of statistical analysis and R and Rstudio is needed. If you have no experience at all with writing scripts (in R or SPSS) you are advised to participate in the other course in week 3 ''Introduction to Data Science with R and Rstudio'' (RSS3.01)

Admission documents: Motivation letter. 

Cannot join us this year? 

We can keep you informed about the 2025 course program! Do you want to broaden your knowledge in 2025 over courses about sustainability, law, research methods & skills, data science and more. Get an email when the new proposal is ready. Because you have a part to play!

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