Fall 2019

Data Science Seminar

Lecturers: Mourad Khayati and Dingqi Yang 

Teaching language: English

Level: MSc students

Academic year: Fall 2019



Evaluation and Expectations


List of Papers


The seminar on data science involves presentations that cover recent topics on data science. The area of this year’s seminar is neural networks. In the scope of this seminar, we investigate papers that describe algorithms and techniques that use different variants of neural networks to perform data analytics.


The goal for the students is to learn how to critically read and study research papers, how to describe  a paper in a report, and how to present it in a seminar. Under supervision, students will select one paper to study, and to compare with related work. This seminar aims to help students to gather in-depth knowledge of an advanced topic and develop the skills required to describe a complex problem from the neural network area in the form of both a presentation, a written report and an empirical evaluation.

IMPORTANT NOTE: The papers will be distributed on a first come first serve basis.

Evaluation and Expectations

The final grade depends on the quality of the report, presentation, reproducibility experiments and active participation during the seminar. Each participant prepares a self contained report of min 6 pages and gives a presentation of 20 minutes. The report should describe in detail the proposed technique(s). The report might contain a small running example, counter example(s) if any,  and should explore the extreme cases where the proposed approach would perform best and worst. The reproducibility experiments consist of reproducing the same set of experiments introduced in the paper and making a 10 min demo about it.

Advice on how to:

IMPORTANT NOTE: Attendance is mandatory for the two class seminar sessions. The total number of participants will be limited to 10.


Kickoff Meeting. Date: Tue, 24.09.2019, 14:15-15:30, room: C421

Setup and organization of seminar, and paper assignment

Paper Assignment

The papers will be distributed on a first come first serve basis.

Paper & code

Presentation Date



First Report Deadline