Health and life science nowadays produce large and complex data sets on a routine basis – small wonder that Big Data is a hot topic. Handling big data in R, one of the most popular modern data elaboration platforms, can sometimes be a challenge, even for experienced R users. Through hands-on computer labs and lectures you will get a thorough basis for achieving this task.
When enrolling at this course you may apply for the use of the STAP-budget.
To see if you are eligible for this financial support please click here.
Why follow this course?
The course provides background in the possibilities R provides for handling big data, both in terms of execution speed and memory management. This includes good programming practices particular to R, but also more general background on high-performance computing, applied to the R ecosystem. Special attention will be devoted to reproducible research in R. After the course, participants are able to apply the techniques discussed in the course in their own research, and use this as a basis on which to build and include future developments in the R world.
For whom is this course?
This course targets professionals working in health and life sciences (e.g., food industry, breeding and seed business, biotech and agro chemical industry). Presumed knowledge: we aim at individuals with a strong basic understanding of R and experienced in programming in R. If you are unsure whether your R skill level is sufficient to attend this course, please contact Wageningen Academy.
Programme and topics
The course is set up in four blocks, and is presented in an attractive mix of lectures and hands-on computer practicals. This set-up offers participants an ideal opportunity to learn how to:
- Find bottlenecks in terms of execution speed and memory usage
- Perform calculations efficiently (as opposed to easily
- Use R in a way that leads to reproducible research
- Include high performance computing (HPC) in R analyses
The teachers are experts in the field of R and Big Data in health and life-science research, offering interactive tuition with Q&A sessions and the opportunity to discuss case studies submitted by the participants.
Participants need to bring their own device for computer practicals.