Introduction to Biostatistics and Machine Learning
Date: 7 - 11 April 2025
Timezone: Stockholm
The course is geared towards life scientists wanting to be able to understand and use basic statistical methods. It would also suit those already applying biostatistical methods but have never got a chance to reflect on and truly grasp the basic statistical concepts, such as the commonly misinterpreted p-value.
● Probability theory
● Hypothesis testing and confidence intervals
● Resampling
● Linear regression methods
● Introduction to generalized linear models
● Model evaluation
● Unsupervised learning incl. clustering and dimension reduction methods
● Supervised learning incl. classification
Apply here!
Important dates and information
Application open: now
Application closes: 2025-03-14
Confirmation to accepted students: 2025-03-19
Responsible teachers: Olga Dethlefsen, Eva Freyhult
If you do not receive information according to the above dates please contact edu.ml-biostats@nbis.se
Education
In this course we focus on an active learning approach. The course participants are expected to do some pre-course reading and exercises, corresponding up to 40h studying. The education consists of teaching blocks alternating between lectures, group discussions, live coding sessions etc.
Course fee
A course fee* of 3000 SEK for academic participants and 15000 SEK for non-academic participants will be invoiced to accepted participants. The fee includes lunches, coffee and snacks.
*Please note that NBIS cannot invoice individuals
The course can accommodate a maximum of 24 participants. If we receive more applications, participants will be selected based on several criteria. Selection criteria include correct entry requirements, motivation to attend the course as well as gender and geographical balance.
We also welcome applications from outside of Sweden and from the non-academic sector; for more information contact us!
Contact: edu.ml-biostats@nbis.se
Keywords: Biostatistics, Machine Learning, bioinformatics
Venue: BMC Trippelrummet Husargatan 3, entrance C11
City: Uppsala
Country: Sweden
Prerequisites:
● Basic R programming skills (check your skills by taking our self-assessment test)
● BYOL (bring your own laptop) with R and RStudio installed
● No prior biostatistical knowledge is assumed, only basic math skills (pre-course studying materials will be available upon course acceptance)
Learning objectives:
● Summarize and visualize data using descriptive statistics.
● Understand probability, random variables, and key distributions
● Compute sampling distributions and standard errors
● Perform hypothesis testing using resampling techniques and parametric testing
● Implement and interpret linear regression and classification models
● Assess (generalized) linear model performance and assumptions
● Apply Principal Component Analysis for dimensionality reduction
● Use clustering methods like k-means and hierarchical clustering
● Understand and apply Random Forest for classification and regression
● Compare machine learning models using evaluation metrics
● Use structured machine learning model building and evaluation
Target audience: PhD Students, postdocs, researchers, non-academic, international, everyone
Event types:
- Workshops and courses
Activity log
