Programme Structure



Year 2 Spring Master thesis (30)
Year 2 Autumn DAT300 Applied machine learning II (10) DAT390 Data Science Seminar (10) Elective specialisation course*  
Year 1 Spring DAT200 Machine Learning and Deep Learning (10) MATH280 Applied Linear Algebra (10) INF230 Data Handling and Data Bases (10) INF221 Computer Science for Data Scientists (10)
Year 1 Autumn INF200 Advanced programming (10) Elective specialization course* Elective specilisation course*  
Year 1 August DAT121 Introduction Course for Data Scientists (5)      
*Choose at least 10 ECTS at 300-level.


Mandatory courses (105 ECTS)

DAT121 Introduction Course for Data Scientists August 5 ECTS
INF200 Advanced programming Autumn 10 ECTS
DAT200 Machine Learning and Deep Learning Spring 10 ECTS
MATH280 Applied Linear Algebra Spring 10 ECTS
INF221 Computer Science for Data Scientists Spring 10 ECTS
INF230 Data Handling and Data Bases Spring 10 ECTS
DAT300 Applied machine learning II Autumn 10 ECTS
DAT390 Data Science Seminar  Autumn 10 ECTS
M30-DV Master's Thesis 30 ECTS

In addition, choose a minimum of 15 ECTS elective specilisation courses. Of these, at least 10 ECTS must be at 300-level. Bellow you will find a list of recommended elective courses.
Elective courses should be chosen with your Master's Thesis topic in mind. 

If one or more of the mandatory courses are equivalent to courses from your prior education, these can be replace with other relevant courses from the list bellow.
Please contact one of our student advisors and they will assist you in revising your study plan. 

Choose specilisation courses from the list bellow. 

Data analysis and statistics       
DAT320 Sequential and time series data analysis
INF205 Resourse-efficient programming 
 Image Analysis 
STAT200 Regression
STAT210 Analysis of Variance   
STAT340 Applied methods in statistics
STAT351 Statistical Theory
STIN300 Statistical Programming in R      

HFA301 Calculation of breeding values
BIN300 Statistical Genomics
BIN310 Selected Topics in Genome Analysis       
BIN315 Selected Topics in Functional Genomics       

Data Science in Energy physics       
FYS377 Future Digital Power Systems       
FYS301 Modelling Absorption and Scattering of Electromagentic Radiation       

Data Science in Biological physics       
FYS388 Computational Neuroscience

Big Data in Geosciences
GMGI210 Geographical Modelling and Analysis    
GMGI300 Geographical Database Systems   

Big Data in Construction
TBA210 Building Structures
TBA331 Building Performance Simulation   

Big Data in Economics
BUS323 Energy and commodity market analysis
 Applied Financial Econometrics
BUS313 Strategic Performance Management
BUS332 Decision Analysis ad Capital Budgeting (only in norwegian)
BUS340 Supply Chain Management
ECN301 Econometric methods
ECN303 Impact assessment
INN351 Enterprise Architecture for the Digital Age
INN352 Development and Implementation of Information Systems
INN353 Monitoring and Control of Business Processes
INN358 Machine Learning with Discrete Event Stream Data


Data Science
Prof. Kristin Tøndel
- Assoc.Prof. Oliver Tomic
- Assoc.Prof. Kristian Hovde Liland

High-dimensional data in life sciences: 
Prof. Cecilia Futhsæther
Assoc.Prof. Ulf Indahl
Prof. Achim Kohler

Robotics and machine learning:
Prof. Pål From

Large-scale simulation
Prof. Hans Ekkehard Plesser

Big data in neurosciences
Prof. Gaute Einevoll

Assoc.Prof. Mareile Wolff

Cell phone sensoring
Assoc.Prof. Leif Daniel Houck

Big data in Economics and Business-organisational science
Assoc.Prof. Nicolay Andre Melsæter Worren

Environmental economcis (land use change)
Prof. Arild Angelsen

Assoc.Prof. Trygve Almøy
Prof. Thore Egeland
Assoc.Prof. Ellen Sandberg
Prof. Solve Sæbø

Prof. Torgeir Hvidsten
Assoc.Prof. Lars Snipen

Published 13. July 2017 - 11:19 - Updated 7. September 2022 - 12:54