Thesis Applied data science

Course goals

After taking this course, students will be able to:

• formulate a data science problem such that the solution of this data science problem translates to a solution of the domain problem;
• identify and assess relevant dataset(s), while considering potential legal and ethical issues;
• analyze data using state-of-the-art data science methods;
• assess whether results are accurate from a data science point of view;
• draw conclusions on whether results contribute to the solution of the pre-defined problem and suggest areas of improvement;
• independently and timely manage and execute the thesis process;
• give a convincing presentation about the work;
• write a scientific report about the conducted research

Assessment
The assessment is based on the assessment form of a research project at the Graduate School of Natural Sciences.
Total grade:

• thesis and results (60% of the final mark)
• presentation (10%)
• process (30%).

We will provide a thesis guideline, which contains the assessment rubrics, before the start of the thesis projects.

Prerequisites
INFOMDWR Data Wrangling and Analysis plus at least two ADSM elective courses completed.

Content

The thesis writing is based on the final research project of the program.

All graduation research projects are pre-selected by the ADSM program team, and are based on a research question from the domain of applied data science, which are part of the research focus of at least one of the scientific staff members.

Course form
All projects are supervised by two members of the scientific staff.
The student meets the first supervisor regularly, typically once every two weeks.

Study materials
Students are expected to identify relevant reading and study materials in consultation with their supervisors.

Course enrolment
Registration for the thesis has to be done in Osiris Case.