Data Science and Artificial Intelligence
Abschluss
: Master of ScienceFakultät
: Mathematik, Informatik und NaturwissenschaftenRegelstudienzeit
: 4 SemesterStudiensprache
: EnglischStudienbeginn
: zum WS, SemestertermineBewerbungsfrist
: 01.06. bis 15.07.Zulassungsbeschränkung
: JaStudiengebühren
: keine, aber Semesterbeitrag
Beschreibung des Studiengangs
The convergence of data science and artificial intelligence represents a pivotal advancement in technology with far-reaching implications across industries. At its core, data science harnesses the power of data to extract insights, patterns, and trends, enabling informed decision-making. Meanwhile, artificial intelligence empowers machines to mimic human intelligence, enabling automation, prediction, and problem-solving. Combined together, these two fields have already revolutionized fields such as healthcare, finance, and marketing.
Berufliche Perspektiven
Upon completing the Master of Science in Data Science and Artificial Intelligence, students will be able to join leading companies and academic institutions across diverse sectors, including top research labs, tech giants, healthcare providers, environmental organizations and consulting agencies. Equipped with proficiency in data analysis, machine learning algorithms and practical knowledge of artificial intelligence technologies, they can endorse roles such as data scientist, machine learning engineer, AI researcher, and business analyst. With the demand for data-driven solutions continuously on the rise, graduates of this program find themselves at the forefront of the employment market.
Studienaufbau
The course program comprises of 120 credit points and divides into the following categories:
• Mandatory modules: These modules cover knowledge specific to the Data Science and Artificial Intelligence program, and students have no choice regarding the required modules.• Required elective modules: These are related to Data Science and Artificial Intelligence core concepts and applications. Students have to choose modules from the category “Fundamentals of Data Science and Artificial Intelligence” for a total of 24 ECTS, and modules from the category “Advanced Topics in Data Science and Artificial Intelligence” for a total of 18 ECTS.• Domain Knowledge: These modules cover various application domains and transversal knowledge concepts, enabling the students to apply the core concepts learnt in the mandatory and required elective modules to diverse scientific disciplines, i.e. biology, chemistry, earth systems sciences, informatics, mathematics, physics. In the domain area (Domain Knowledge in Data Science and Artificial Intelligence) DSAI (24 ECTS), courses from at least two application domains with at least 6 ECTS per domain must be selected. Students can choose to study either in depth (specialized and courses from a few application domains) or in breadth (many application domains, with a typical 6 ECTS per module, courses from up to four application domains can be selected). Students also have the opportunity to choose up to 6 ECST from the courses offered by Universität Hamburg within the framework of the 24 ECTS. However, they can also fill the entire 24 ECTS with application domains. The selectable modules are determined in agreement with the departments of the MIN faculty.
Weiterführende Links
Examination Regulations – see « Fachbereichsübergreifende Prüfungsordnungen – Master »
Subject-specific Regulations – see « Fachbereich Informatik – Master »
Angebote zur Studienorientierung
Bewerbung
Zulassungsvoraussetzungen
General admission requirements for all master’s degree programs:
Proof of first degree, language proficiency
Further details ...
Special admission requirements for this degree program:
o B.Sc. Informatik from Universität Hamburgo B.Sc. Computing in Science from Universität Hamburg
o Bachelor’s degree in a related field insofar as the following minimum ECTS credit points were obtained:24 credit points in mathematics, from which 6 credit points were obtained in the field of stochastics; 60 credit points in computer science, from which 6 credit points were obtained in studying algorithms and data structures, or theoretical computer science.
Bewerbungsverfahren
Bewerbungsfristen
Auswahlkriterien
Selection Bylaws for the Faculty of Mathematics, Informatics and Natural Sciences
Kontakt
Allgemeine Studienberatung
Fachspezifische Studienberatung
Stand: 15. Mai 2024