Big Data (Summerschool)

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Course
Big Data
Date
Aug 12 - 16, 2024 (Summerschool)
Course co-ordinator


Course description

Introduction

The digital universe is expanding continuously. This huge amount of information is often referred to 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 prove 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 embed in medical research through numerous reall-life examples and case-studies.

Course objectives
  • Run and understand basic Python scripts to perform machine learning analyses of large datasets;
  • Interpret results of a simple machine learning pipeline, including its design and performance;
  • Understand and explain basic concepts of machine learning, including: supervised/unsupervised learning, overfitting, cross-validation, evaluation metrics, bias-variance tradeoffs, and benchmarking;
  • Understand and explain basic concepts of deep learning;
  • Understand and explain basic concepts of causal modeling;
  • List several existing and potential applications of machine learning and AI in medical research.
Prerequisite knowledge
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
Course days
Weekdays
Course format
1 week course (approx. 40 hours), including lectures, computer practicals, a group assignment, and self-study. Each day is split in two blocks of three hours. Blocks will consist of lecture and practical exercises.
Assessment
 80% attendance and (Closed book) Exam.
Number of participants
50
Course fee€ 980,-
Prerequisite for participation is sufficiënt capacity in terms of teachers and locations.