According to a new and extensive report by the McKinsey Global Institute ("Game changers: Five opportunities for US growth and renewal"), "by 2018 the United States will experience a shortage of 190,000 skilled data scientists, and 1.5 million managers and analysts capable of reaping actionable insights from the big data deluge. With an estimated 40,000 exabytes of data being collected by year 2020 — up from 2700 exabytes in year 2012 — the implications of this shortage become apparent." The wide range of economic sectors that will leverage big data analytics in the next decade (including retail, finance, manufacturing, healthcare, and government services) is driving this explosion in data collection and the demand for skilled practitioners even further. Since the trend towards data is being widely covered by the media, we expect a high demand for a curriculum aimed towards data science in the near future.
The Institute for Computer Science at the University of Bayreuth is offering a program in Data Science. It offers courses in various fields of Data Science like algorithms, computer systems, exploring and analyzing data, probability and statistics, statistical inference and modeling, management of big and complex data, machine learning, visualizing and communicating data (see table below). Most of the courses will be taught in English.
Obligatory prerequisite:
In order to apply for the Data Science Certificate, students have to be enrolled in one of the following Master Programs: Computer Science, Angewandte Informatik, Informatik. Thus, this certificate is only pursuable for students enrolled in one of those master programs.
Students can obtain a "Certificate in Data Science" when they obtain 60 credits in lectures, practical courses, seminars, and/or the Master thesis in courses eligible for the Master program in Applied Computer Science (M.Sc.), Informatik (M.Sc.) or Computer Science (M.Sc.) that are associated with the fields identified above. A list of eligible courses can be found below.
Students interested in obtaining this Certificate in Data Science are asked to contact Prof. Stefan Jablonski for further information. Students have to be enrolled in a regular Master Program (Computer Science (M.Sc.), Angewandte Informatik (M.Sc.), Informatik (M.Sc.)). Then they can (informally) subscribe to the Data Science program (send an informal email to Prof. Stefan Jablonski). Since the courses eligible for the Data Science program are also courses of the three Master Programs Computer Science (M.Sc.), Angewandte Informatik (M.Sc.), Informatik (M.Sc.) or Computer Science (M.Sc.), the Data Science certificate will be completed "alongside" the Master Programs by studying eligible courses (see table below).
Contact
Prof. Dr.-Ing. Stefan Jablonski
E-Mail: stefan.jablonski [@] uni-bayreuth.de
Büro: 0.20 (EG)
Gebäude: Angewandte Informatik
Data Science Courses (as of February 2022)
LP ECTS | ||
Section A: Lectures Bereich A: Vorlesungen | ||
INF 201 | Parallel and distributed systems II Parallele und Verteilte Systeme II | 5 |
INF 202 | Computer graphics I Computergraphik I | 5 |
INF 210 | Artificial intelligence II Künstliche Intelligenz II | 5 |
INF 305 | High Performance Computing High Performance Computing | 8 |
INF 307 | Data Analytics Vormals: Databases and information systems III Datenbanken und Informationssysteme III | 8 |
INF 314 | Algorithms and data structures III Algorithmen und Datenstrukturen III | 5 |
INF 316 | Pattern recognition Mustererkennung | 5 |
INF 318 | Computer graphics III Computergraphik III | 5 |
INF 321 | Foundations of Semi-Structured Data Foundations of Semi-Structured Data Vormals: Theoretische Informatik III | 5 |
INF 326 | Foundations of Data Management Foundations of Data Management Vormals: Foundations of Data Science Foundations of Data Science | 5 |
INF 218 | Programming, Data Analysis and Deep Learning in Python Vormals: Programming in Java Programmieren in Java | 5 |
Section B: Projects and Seminars Bereich B: Projekte und Seminare | ||
INF 351 | Small Master project *) Kleines Master-Projekt *) | 8 |
INF 352 | Big Master project *) Großes Master-Projekt *) | 15 |
INF 353 | Big Master seminar *) Großes Master-Seminar *) | 8 |
Section C: Master Thesis Bereich C: Masterarbeit | ||
INF 301 | Master thesis *) Masterarbeit *) | 30 |
INF 302 | Master seminar Master-Seminar | 5 |
INF 303 | Master practical course Master-Praktikum | 8 |
*) These courses are only creditable if it is confirmed to be eligible by the instructor.