Master
2024/2025
Mentor's Seminar
Type:
Compulsory course (Data Science)
Area of studies:
Applied Mathematics and Informatics
Delivered by:
School of Data Analysis and Artificial Intelligence
Where:
Faculty of Computer Science
When:
1 year, 1-4 module
Mode of studies:
offline
Open to:
students of one campus
Master’s programme:
Data Science
Language:
English
ECTS credits:
3
Contact hours:
40
Course Syllabus
Abstract
This is a final class to give to students’ insights into the art of scientific presentation by doing that, using latest publications on advances in AI and Data Science for reviewing and discussing. Special attention will be given to elements of a good review depending on the subject of the paper under review, as well as structure of a critical evaluation of paper.
Learning Objectives
- The goal of the class is two-fold: - Mastering elements of scientific discussion: reviewing, evaluating, questioning - Acquaintance with latest advances in AI and Data Science
- Acquaintance with latest advances in AI and Data Science
Expected Learning Outcomes
- Recognition of the paper’s type (New method, Review, Comparison of methods, Case study, or Discussion) and reviewing it accordingly;
- The structure of a critical evaluation of a talk including a summary, good points and missings;
- Elements for questioning
- Acquaintance with newest trends and results in AI and Data Science.
Course Contents
- The structure of participation in a scientific discussion: reviewing, discussing, questioning
- Seminar meetings
Interim Assessment
- 2024/2025 4th module0.3 * Participation in a discussion + 0.3 * Participation in a discussion + 0.7 * Presentation of a review + 0.7 * Presentation of a review
- 2025/2026 3rd module1 * Questioning + 1 * Questioning
