DS404B Big Data Computing
| Lecturer: | Jakob Zgonc, M.Sc. |
| Course description: | DS404B |
| Language: | English |
| Recommended for this semester or higher: | 2 |
| ECTS-Credits: | 6 |
| Course can be taken as part of following programs/modules: | See alma |
| Prerequisites: | Exam DS400 Data Science Project Management successfully passed (or equivalent, please contact the lecturer). |
| Limited attendance: | 20 |
| Course Type: | Lecture (2 weekly lecture hours) |
| Date: |
First lecture on April 15, 2025 |
| Registration: | By March 23 via alma. No first-come, first-served. If the number of applications exceeds the number of places available (limited to 20), we unfortunately will not be able to accept all of the applicants. In this case, a random selection will be made from all the applications received. Preferred access for master students from the Data Science in Business and Economics program. |
| Method of Assessment: |
|
| Content: | This course deals with the computational challenges that arise when working with large datasets and/or computationally expensive methods, and introduces potential solutions to those challenges. The focus of the first part of this module will be on solutions that can be implemented locally (i.e., on one’s own machine), while the second part discusses external solutions (i.e., in the cloud / on a computing cluster). The course will primarily be taught in python and R, but several concepts are language-independent or can easily be extended to other languages. |
| Objectives: | Students can reflect the applicability of different concepts for different problems related to large datasets and complex computations. They can apply the taught methods and extensions independently to new problems; they are able to solve advanced computational problems with state-of-the-art methods independently. |
| Literature: | Announced in the course |
| Downloads: | -- |
| ILIAS: | Click here |