WIAS/PE&RC course Statistics for Data Science
Course schedule
Dates | Start time | End time | Location | Coordinator | registrations app/max |
||
---|---|---|---|---|---|---|---|
10-13 February 2025 | 09:00 | 17:00 | Wageningen campus | WIAS | 2 / 24 | Apply |
Course description
Background
In many areas of science new tools and strategies are developed to measure multiple features at subjects and objects of interest. Typical for these new types of data is that they occur in large volumes, are high-dimensional, or are hierarchically structured. For example, in genetics (humans, animals, plants) data can be available at the levels of DNA, RNA, proteins, metabolites and all kinds of phenotypes. These new data require new techniques for analysis and visualization which are provided by a new science that combines elements of statistics and machine learning: Data Science.
Objectives
This course will make you familiar with a modern toolbox of analysis techniques at the interface of statistics and machine learning. You will develop the skills to build and evaluate modeling strategies for complex (big, high-dimensional, hierarchically-structured) data as occurring in the areas relevant to WIAS and PE&RC. Moreover, the course will give you insights in the connections between modern modeling strategies and will teach you to ask the right questions in order to choose the best method for the data at hand. Illustrations will come from relevant case studies.
General Information
Target Group |
PhD candidates |
Course level |
In-depth, post graduate |
Group size |
A minimum of 10 and a maximum of 24 participants |
Course duration |
4 days and given yearly |
Style of teaching |
This will be a hands-on course in which each (interactive) lecture is followed by an illustrative practical. |
Materials |
- James, Witten, Hastie & Tibshirani (2021). An Introduction to Statistical Learning. Freely available here: https://hastie.su.domains/ISLR2/ISLRv2_website.pdf - R and RStudio. |
Language |
English |
Credit points |
1,2 ECTS |
Name lecturers |
Gerrit Gort, Carel Peeters and Jasper Engel (Biometrics, WUR) |
Teaching methods |
Lectures, computer practicals, discussions |
In-person |
Wageningen University campus, Wageningen, the Netherlands. |
Programme
The course spans four days. The following topics will be discussed:
Day 1: Recap linear regression, resampling (bootstrap, jackknife, cross validation), regularized regression: ridge and lasso
Day 2: Extend linear model with splines, Generalized Additive Models (GAM)
Day 3: Classification: logistic regression and linear discriminant analysis; regression trees, random forests, boosting and bagging
Day 4: Clustering (hierarchical clustering, k-means), graphical modeling
Fee (includes coffee/tea and lunches)
Reduced fee: WUR PhD candidates with a TSP |
€ 375 |
University fee: All other PhD candidates / post-docs and staff of Wageningen University |
€ 750 |
Cancellation condition
You may cancel free of charge up to 1 month before the start of the course. After this date you will be charged with the University fee. Unless:
- You can find someone to replace you in the course and supply the course coordinator with the name and contact information of your replacement. In this case you will be charged a €50,- cancellation fee.
- PhDs of Wageningen University who have a valid reason to cancel (illness or death in the family 1st or 2nd degree). In this case you will be charged the reduced fee and your supervisor/PI must send a mail indication the reason for cancellation.
More information: Please contact: WIAS Office wias@wur.nl