Erasmus Summer Programme Courses
Take a look at all the courses in the Erasmus Summer Programme, and find the course right for you.
View all ESP coursesData Science in Epidemiology [ESP80]
Course highlights
EC points
0.7
Start date
22 August 2022
End date
26 August 2022
Course days
Monday to Friday (5 afternoons)
Course time
From 13:00 till 16:00 CEST
Faculty
Dr. Daniel Bos and Dr. Gennady Roshchupkin
Course fee
€ 490
Location
Erasmus MC, Rotterdam NL
Level
Intermediate
Prerequisites
Basic understanding of biostatistics, and epidemiology (as covered in ESP03 and ESP01).
Basic knowledge of programming (experience with R, python or any other scripting language).
Disciplines
- Epidemiology
- Clinical Research
- Methodology
Course Materials
Digitally, download instructions will be sent before the start of the course, by e-mail.
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Detailed information about this course:
Description
Faculty: Dr. Gennady Roshchupkin, PhD and Dr. Daniel Bos, MD, PhD
Data science is a multi-disciplinary field that uses scientific methods and algorithms to extract knowledge and insights from structured and unstructured data. Recent advances in technology allows for the collection of enormous amounts of health-related data. Consequently, skills pertaining to handle and manipulate these data and to extract relevant information have become crucial to perform high quality research. Unfortunately, many researchers without a technical background frequently experience troubles obtaining or developing these skills. The aim of this course is to bridge this gap in knowledge by providing an interactive and hands-on programme about data science and how it can be applied in epidemiological research.
Objectives
- Understand the concept of data science in the epidemiological environment;
- Learn basic skills in Python and Jupyter notebooks for data science: the most popular and efficient programming software for high-performance scientific analysis;
- Apply the general methods of data visualization using Python;
- Understand Machine Learning methods and neural networks algorithms in epidemiology;
- Appraise the role of big data/data science in terms of study design and scientific value
Participant profile
Clinical researchers, clinical epidemiologists, computer scientists, those in health technology assessment or value-based healthcare.
Assessment
Attendance