The digital universe is expanding continuously. This huge amount of information often referred to as big data have a huge potential to answer questions that could not be answered before. For example, in biomedical sciences, researchers increasingly make use of these Big Data, by pooling real-time data from multiple sources including electronic healthcare records in order to e.g. detect diseases at an early stage.
The summer school on big data will provide you with a sound introduction to this exciting new field in health research. Spanning topics such as:
- Introduction to machine learning (ML)
- Automated ML
- Causal inference using big data and ML
- Natural language processing
- Data linkage
This will be embedded in medical research through numerous real-life examples and case-studies.
The target group of this course includes advanced BSc and MSc students in biomedical sciences with a basic understanding of epidemiology and (medical) statistics.
A basics understanding of R or python programming languages is desirable; however self-study tutorials (~2 hours each) will be provided
1 week online
For this course you are required to upload the following documents when applying:
Educational Office Epidemiology | firstname.lastname@example.org