Data science / big data

Specialize within Data science / big data

The obtained profile provides thorough competencies in the analysis of massive data, which cover the whole spectrum from data acquisition through storage, analysis and interpretation to the application and presentation of the results.

What massive data is cannot be defined in absolute terms, but depends on the computational power of the platform used. Also issues on data security and privacy are extremely important to handle correctly and ethically in order to unleash the full potential behind data currently generated.

Entry to the profile

The educational profile is most naturally achieved through one of the following DTU master programs, although others may be eligible:

Mandatory course fulfillments

The profile requires that the student follows at least 45 ECTS out of this total course list - at least 15 ECTS of these must be from the short-list of 6 core-competency courses. This ensures that the students take courses outside their master program. The remaining 25-30 ECTS can be chosen freely on the list. The variety of courses allows the student to focus on a certain topic or to become a generalist in the area.

The general idea behind the profile is to spread the activities within the program to “cover” the full spectrum of competencies in a natural way for a candidate who has specialized in Data Science.

Master thesis

In addition, the topic of M.Sc thesis has to be in the area of data analysis and has to cover at least two of the 4 main topics (Data origins and collection, Data storage, Analytics, Consumers) and show a clear perspective to the whole subject. As a general rule, the thesis should concern a real world data setting – preferably together with an external partner.

Knowledge

The students are expected to have sound basic knowledge in programming, statistics, and algorithms in order to have the prerequisites to follow the relevant courses on the list.

The Value Chain of Data Science and Big Data
The three programs in a broad sense “cover” the figure below in the following way:

Computer Science and Engineering -> leftmost 
Mathematical Modelling and Computation -> middle 
Digital Media Engineering -> rightmost 

Big-Data

 

Ambitious possibility as M.Sc. student

Bjarne Ersbøll, professor at DTU Compute, koordinator for educational profile Data Science/Big Data

The students following the profile receive a special additional certificate documenting their unique competencies in this field.

Big Data Value Association

Big Data Value Association

Contact

Bjarne Kjær Ersbøll
Professor, Head of section
DTU Compute
+45 45 25 34 13

Contact

Signe Møller Jørgensen
Coordinator of studies
DTU Compute
+45 45 25 37 37