The following designations are used:

G1F - First cycle, has less than 60 credits in first-cycle courses as entry requirements

G2F - First cycle, has at least 60 credits in first-cycle courses as entry requirements

A1N - Second cycle, has only first-cycle courses as entry requirements, at least 120 credits

A1F - Second cycle, has second-cycle courses as entry requirements

A1E - Second cycle, contains degree project for Master of Arts/Master of Science (60 credits)

A2E - Second cycle, degree project for Master of Arts/Master of Science (120 credits)

Semester 1

Period 1

Computational Science

• Scientific Computing, Bridging Course, 5 credits (1TD045) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Mathematics A1N
• Scientific Computing for Partial Differential Equations, 5 credits (1TD354) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Technology A1N
• Computer Programming II, 5 credits (1TD722) Main field(s) of study and in-depth level: Computer Science G1F, Technology G1F

Eligible courses

• Applied Mathematics, 5 credits (1MA148) Main field(s) of study and in-depth level: Mathematics A1N
• Quantum Mechanics, Advanced Course, 5 of 10 credits (1FA352) Main field(s) of study and in-depth level: Physics A1N, Quantum Technology A1N
• Database Design I, 5 credits (1DL301) Main field(s) of study and in-depth level: Computer Science G2F, Sociotechnical Systems G2F, Technology G2F
• Applied Dynamical Systems, 5 of 10 credits (1MA444) Main field(s) of study and in-depth level: Mathematics A1N
• Artificial Intelligence, 5 credits (1DL340) Main field(s) of study and in-depth level: Computer Science A1N, Technology A1N
• Fluid Mechanics, 5 credits (1FA253) Main field(s) of study and in-depth level: Physics A1N, Technology A1N
• Financial Theory, 7.5 credits (2NE831) Main field(s) of study and in-depth level: Economics A1F, Financial Mathematics A1N

Period 2

Computational Science

• Optimisation, 5 credits (1TD184) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Data Science A1N, Technology A1N
• Applied Finite Element Methods, 5 credits (1TD056) Main field(s) of study and in-depth level: Computational Science A1F, Computer Science A1F, Technology A1F
• Scientific Visualisation, 5 credits (1TD389) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Technology A1N

Eligible courses.

• Quantum Mechanics, Advanced Course, 5 of 10 credits (1FA352) Main field(s) of study and in-depth level: Physics A1N, Quantum Technology A1N
• Database Design II, 5 credits (1DL400) Main field(s) of study and in-depth level: Computer Science A1N, Technology A1N
• Computer-Assisted Image Analysis I, 5 credits (1TD396) Main field(s) of study and in-depth level: Computer Science A1N, Technology A1N
• Software Testing, 5 credits (1DL610) Main field(s) of study and in-depth level: Computer Science A1N, Technology A1N
• Chemical Bonding and Computational Chemistry, 10 credits (1KB550) Main field(s) of study and in-depth level: Chemistry A1N, Physics A1N
• Financial Derivatives, 7.5 credits (1MA209) Main field(s) of study and in-depth level: Financial Mathematics A1N, Mathematics A1N
• Statistical Methods in Physics, 5 credits (1FA357) Main field(s) of study and in-depth level: Physics A1N
• Applied Dynamical Systems, 5 of 10 credits (1MA444) Main field(s) of study and in-depth level: Mathematics A1N

Semester 2

Period 3

Computational Science

• High Performance Programming, 10 credits (1TD062) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Technology A1N
• Computational Physics, 5 credits (1FA573) Main field(s) of study and in-depth level: Computational Science A1N, Physics A1N
• Data Engineering I, 5 credits (1TD169) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Data Science A1N, Technology A1N

Eligible courses.

• Markov Processes, 10 credits (1MS012) Main field(s) of study and in-depth level: Mathematics A1N
• Natural Computation Methods for Machine Learning, 5 of 10 credits (1DL073) Main field(s) of study and in-depth level: Computer Science A1N
• Introduction to Partial Differential Equations, 5 credits (1MA053) Main field(s) of study and in-depth level: Mathematics A1N
• Computer Graphics, 10 credits (1TD388) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N

Period 4

Computational Science

• Parallel and Distributed Programming, 5 credits (1TD070) Main field(s) of study and in-depth level: Computational Science A1F, Computer Science A1F, Technology A1F
• Numerical Modelling of the Atmosphere, 10 credits (1ME406) Main field(s) of study and in-depth level: Computational Science A1N, Earth Science A1N, Physics A1N
• Modelling Complex Systems, 10 credits (1MA256) Main field(s) of study and in-depth level: Computational Science A1N, Mathematics A1N
• Degree Project D in Computational Science, 15 credits (1TD908) Main field(s) of study and in-depth level: Computational Science A1E
• Data Engineering II, 7.5 credits (1TD075) Main field(s) of study and in-depth level: Computational Science A1F, Computer Science A1F, Data Science A1F
• Applied Linear Algebra for Data Science, 7.5 credits (1TD060) Main field(s) of study and in-depth level: Computer Science A1F, Data Science A1F

Eligible courses.

• Computer Graphics, 10 credits (1TD388) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N
• Analysis of Time Series, 10 credits (1MS014) Main field(s) of study and in-depth level: Financial Mathematics A1N, Mathematics A1N
• Natural Computation Methods for Machine Learning, 5 of 10 credits (1DL073) Main field(s) of study and in-depth level: Computer Science A1N

The course 1TD908 is for one-year Masters.

Semester 3

Period 1

Computational Science

• Advanced Numerical Methods, 10 credits (1TD050) Main field(s) of study and in-depth level: Computational Science A1F, Computer Science A1F, Technology A1F
• Computational Finance: Pricing and Valuation, 5 credits (1TD186) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Financial Mathematics A1N
• Accelerator-Based Programming, 7.5 credits (1TD055) Main field(s) of study and in-depth level: Computational Science A1F, Computer Science A1F

Eligible courses.

• Statistical Thermodynamics: Theory and Simulation Methods, 5 of 10 credits (1KB362) Main field(s) of study and in-depth level: Chemistry A1F, Physics A1F
• Data Mining I, 5 credits (1DL360) Main field(s) of study and in-depth level: Computer Science A1N, Technology A1N
• Energy Physics I, 5 credits (1FA404) Main field(s) of study and in-depth level: Physics G2F, Technology G2F
• Microeconomic Theory, 7.5 credits (2NE811) Main field(s) of study and in-depth level: Economics A1N
• Electromagnetic Field Theory, 5 credits (1FA252) Main field(s) of study and in-depth level: Physics A1N, Technology A1N

Period 2

Computational Science

• Project in Computational Science, 15 credits (1TD307) Main field(s) of study and in-depth level: Computational Science A1F, Computer Science A1F, Technology A1F

Eligible courses.

• Computer-Intensive Statistics and Applications, 10 credits (1MS049) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Financial Mathematics A1N, Mathematics A1N
• Statistical Thermodynamics: Theory and Simulation Methods, 5 of 10 credits (1KB362) Main field(s) of study and in-depth level: Chemistry A1F, Physics A1F
• Macroeconomic Theory, 7.5 credits (2NE814) Main field(s) of study and in-depth level: Economics A1N

Semester 4

Period 3

• Degree Project E in Computational Science, 15 of 30 credits (1TD808) Main field(s) of study and in-depth level: Computational Science A2E

Period 4

• Degree Project E in Computational Science, 15 of 30 credits (1TD808) Main field(s) of study and in-depth level: Computational Science A2E

In addition to the eligible courses listed above, there are also the courses 1TD322 and 1TD326, see below, that allow for individualised specialisation. Courses, up to 30 credits, also can be chosen from other main fields.

• Advanced Course on Topics in Scientific Computing I, 5 credits (1TD322) Main field(s) of study and in-depth level: Computational Science A1F, Computer Science A1F
• Advanced Course on Topics in Scientific Computing II, 10 credits (1TD326) Main field(s) of study and in-depth level: Computational Science A1F, Computer Science A1F