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LTH Courses

Faculty of Engineering | Lund University

Courses given 2020/21 by Centre for Mathematical Sciences

 20/21 

Mathematical Statistics

Course Code Link to complete information about the course; study periods, programmes etc. Credits Cycle G1: Basic level
G2: Upper basic level
A: Advanced level
Programme Programme the course belongs to in this academic year. The link points to the programme page for this academic year. S.Ex. stud. The course is suitable for incoming exchange students. Language Language of the course:
E: The course is given in English
E1: The course is given in English upon request
E2: The course may be given in English
S: The course is given in Swedish
Course Name Foot­note Links KS: Course syllabus in Swedish
KE: Course syllabus in English
U: Archive with course evaluations
W: Course Web Page
T: Examination schedule
  20/21
sp1
20/21
sp2
20/21
sp3
20/21
sp4
F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions)
FMSF35 4 G2 IEA - S Basic Probability Theory KS KE U W T 24 24 0 0 54
FMSF15 7.5 G2 D, E, F, I, Pi, MMSR X E Markov Processes X Please see footnote below. KS KE U W T 26 16 6 0 140
FMSF15 C X Please see footnote below. 26 16 6 0 140
FMSF15 BME X Please see footnote below. 26 16 6 0 140
FMSF30 5 G2 IBYA, IBYI, IBYV - S Mathematical Statistics KS KE U W T 30 32 0 0 71
FMSF70 7.5 G2 B, BME, K, N - S Mathematical Statistics X Please see footnote below. KS KE U W T 26 16 8 1 140
FMSF75 7.5 G2 W - S Mathematical Statistics, Basic Course KS KE U W T 16 16 20 2 130
FMSF40 7.5 G2 IDA - S Probability Theory and Discrete Mathematics KS KE U W T 36 38 0 0 126
FMSF10 7.5 G2 BME, C, D, E, F, I, M, MWIR, Pi, MMSR X E Stationary Stochastic Processes X Please see footnote below. KS KE U W T 22 16 6 0 145
FMSN25 7.5 A F, I, Pi X E Valuation of Derivative Assets X Please see footnote below. KS KE U W T 30 26 6 1 130
FMSF80 9 G2 Pi - S Mathematical Statistics, Basic Course X Please see footnote below. KS KE U W T 18 14 4 0 85 18 14 2 2 85
FMSF80 I X Please see footnote below. 18 14 4 0 85 18 14 2 2 85
FMSF80 F X Please see footnote below. 18 14 4 0 85 18 14 2 2 85
FMSN60 7.5 A I X E Financial Statistics X Please see footnote below. KS KE U W T 28 14 16 5 130
FMSN60 F, Pi X Please see footnote below. 28 14 16 5 130
FMSF25 2.5 G2 V - S Mathematical Statistics - Complementary Project X Please see footnote below. KS KE U W T 0 0 8 1 50
FMSF25 V X Please see footnote below. 0 0 8 1 50
FMSF20 7.5 G2 D, E - S Mathematical Statistics, Basic Course KS KE U W T 26 16 8 0 140
FMSF50 7.5 G2 L, V - S Mathematical Statistics, Basic Course KS KE U W T 26 16 8 0 140
FMSN45 7.5 A BME, C, D, E, F, I, Pi, MMSR X E Mathematical Statistics, Time Series Analysis X Please see footnote below. KS KE U W T 24 12 12 5 120
FMSN20 7.5 A BME, C, D, E, F, Pi, MMSR X E Spatial Statistics with Image Analysis X Please see footnote below. KS KE U W T 26 0 18 5 150
FMSF60 7.5 G2 BME, C, Pi, RH - E1 Statistical Methods for Safety Analysis KS KE U W T 28 14 12 0 120
FMSN15 7.5 A F, I, Pi X E Statistical Modelling of Multivariate Extreme Values X Please see footnote below. KS KE U W T 28 14 9 1 120
FMSN50 7.5 A BME, D, F, I, Pi, MMSR X E Monte Carlo and Empirical Methods for Stochastic Inference X Please see footnote below. KS KE U W T 28 0 12 5 140
FMSF05 7.5 G2 BME, F, I, Pi X E Probability Theory X Please see footnote below. KS KE U W T 26 14 0 0 160
FMSN35 7.5 A BME, C, D, E, F, I, Pi X E Stationary and Non-stationary Spectral Analysis X Please see footnote below. KS KE U W T Course on hold Course on hold: The course is not given this academic year, but is planned to be given next academic year.
FMSF65 7.5 G2 BME, D, E, F, MLIV, MWIR, N, Pi, W X E Design of Experiments KS KE U W T 14 14 14 1 150
FMSN30 7.5 A BME, D, F, I, L, Pi, MMSR X E Linear and Logistic Regression X Please see footnote below. KS KE U W T 24 0 26 2 120
FMSN40 9 A I X E Linear and Logistic Regression with Data Gathering X Please see footnote below. KS KE U W T 26 0 30 5 120
FMSF55 7.5 G2 C, M - S Mathematical Statistics, Basic Course KS KE U W T 26 16 8 0 140
FMSN55 7.5 A D, F, I, Pi X E Statistical Modelling of Extreme Values KS KE U W T 28 14 9 1 120

FMSF15 (BME, C, D, E, F, I, Pi) Markov Processes: The course is to be studied together with MASC03.
FMSF70 (B, BME, K, N) Mathematical Statistics: The course is to be studied together with MASB02
FMSF10 (BME, C, D, E, F, I, M, MWIR, Pi) Stationary Stochastic Processes: The course is to be studied together with MASC04
FMSN25 (F, I, Pi) Valuation of Derivative Assets: The course is to be studied together with MASM24
FMSF80 (F, I, Pi) Mathematical Statistics, Basic Course: Replaces FMSF45
FMSN60 (F, I, Pi) Financial Statistics: The course is to be studied together with MASM18
FMSF25 (V) Mathematical Statistics - Complementary Project: Only one of the courses FMSF25 and FMSF50 may be included in a degree.
FMSN45 (BME, C, D, E, F, I, Pi) Mathematical Statistics, Time Series Analysis: The course is to be studied together with MASM17.
FMSN20 (BME, C, D, E, F, Pi) Spatial Statistics with Image Analysis: The course is to be studied together with MASM25
FMSN15 (F, I, Pi) Statistical Modelling of Multivariate Extreme Values: The course is offered every other academic year and will be given in 2020/21, 2022/23.
FMSN50 (BME, D, F, I, Pi) Monte Carlo and Empirical Methods for Stochastic Inference: The course is to be studied together with MASM11.
FMSF05 (BME, F, I, Pi) Probability Theory: The course is to be studied together with MASC01
FMSN35 (BME, C, D, E, F, I, Pi) Stationary and Non-stationary Spectral Analysis: The course is offered every other academic year and will next be offered in 2021/22.
FMSN30 (I) Linear and Logistic Regression: Only one of the courses FMSN30 and FMSN40 may be included in a degree.
FMSN40 (I) Linear and Logistic Regression with Data Gathering: Compulsory course in the elective block ‘Mathematical Modelling’ for students admitted autumn 2016. The course is also an optional programme course. Only one of the courses FMSN30 and FMSN40 may be included in a degree.

Mathematics

Course Code Link to complete information about the course; study periods, programmes etc. Credits Cycle G1: Basic level
G2: Upper basic level
A: Advanced level
Programme Programme the course belongs to in this academic year. The link points to the programme page for this academic year. S.Ex. stud. The course is suitable for incoming exchange students. Language Language of the course:
E: The course is given in English
E1: The course is given in English upon request
E2: The course may be given in English
S: The course is given in Swedish
Course Name Foot­note Links KS: Course syllabus in Swedish
KE: Course syllabus in English
U: Archive with course evaluations
W: Course Web Page
T: Examination schedule
  20/21
sp1
20/21
sp2
20/21
sp3
20/21
sp4
F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions)
FMAB45 5 G1 BME, M, MD - S Calculus in One Variable A1 KS KE U W T 30 20 0 0 83
FMAB65 7.5 G1 B, BI, C, D, E, F, I, K, L, N, Pi, V, W - S Calculus in One Variable B1 KS KE U W T 50 30 0 0 120
FMAB30 6 G1 B, BI, BME, C, D, IDA, IEA, K, L, N, V, W - S Calculus in Several Variables X Please see footnote below. KS KE U W T 44 16 2 0 100
FMAB30 I, IBYA, IBYI, IBYV X Please see footnote below. 44 16 2 0 100
FMAB30 E, M, MD 44 16 2 0 100
FMAN20 7.5 A BME, C, D, E, F, L, Pi, MMSR X E1 Image Analysis KS KE U W T 32 0 0 2 166
FMAA60 7.5 G1 C, D, F, I, M, MD, N, Pi, W - S Introduction to Real Analysis KS KE U W T 26 0 0 0 174
FMAN80 7.5 A Pi X E1 Functional Analysis and Harmonic Analysis KS KE U W T 20 10 0 0 108 8 4 0 0 50
FMAN80 F, MMSR 20 10 0 0 108 8 4 0 0 50
FMAN70 6 A BME, C, D, E, F, I, Pi X E1 Matrix Theory KS KE U W T 18 10 0 1 56 12 4 0 1 58
FMAN15 7.5 A D, F, Pi, MMSR X E Nonlinear Dynamical Systems KS KE U W T 16 6 0 0 78 14 8 0 0 78
FMAA50 13.5 G1 IBYI - S Calculus KS KE U W T 14 26 0 0 40 44 26 0 0 92 28 26 0 0 66
FMAA50 IBYA, IBYV, IDA, IEA 14 26 0 0 40 44 26 0 0 92 28 26 0 0 66
FMAB55 5 G1 Pi - S Mathematical Communication KS KE U W T 10 8 0 1 17 10 2 0 1 18 4 6 0 4 45
FMAB20 6 G1 F - S Linear Algebra KS KE U W T 40 16 0 0 106
FMAB20 Pi 40 16 0 0 106
FMAB20 I 40 16 0 0 106
FMAB20 M, MD 40 16 0 0 106
FMAB20 C, E, V X Please see footnote below. 40 16 0 0 106
FMAB20 BI, L, N 40 16 0 0 106
FMAB20 D 40 16 0 0 106
FMAB20 BME 40 16 0 0 106
FMAF01 7 G2 F, Pi - E1 Mathematics - Analytic Functions KS KE U W T 42 24 0 1 128
FMAF01 BME, M, N 42 24 0 1 128
FMAF01 BME, E 42 24 0 1 128
FMAF01 C, D, I, M X Please see footnote below. 42 24 0 1 128
FMAB50 5 G1 M, MD - S Calculus in One Variable A2 KS KE U W T 36 20 0 0 77
FMAB50 BME 36 20 0 0 77
FMAB70 7.5 G1 BI, C, E, I, L, Pi, W - S Calculus in One Variable B2 KS KE U W T 50 30 0 0 120
FMAB70 B, D, F, K, N, V 50 30 0 0 120
FMAB75 7.5 G1 C, D, E, F, Pi X E1 Discrete Mathematics KS KE U W T 54 0 0 2 144
FMAB75 BME 54 0 0 2 144
FMAB75 C 54 0 0 2 144
FMAB75 BME, D, E, F, Pi 54 0 0 2 144
FMAN30 7.5 A C, D, F, MMSR X E1 Medical Image Analysis KS KE U W T 32 0 0 3 165
FMAN30 BME, E, Pi 32 0 0 3 165
FMAN60 6 A D, E, I, Pi X E1 Optimization X Please see footnote below. KS KE U W T 32 14 4 1 109
FMAN60 BME, F, M 32 14 4 1 109
FMAN40 3 A C, D, E, F, Pi X E1 Project in Applied Mathematics KS KE U W T 0 0 0 10 70
FMAN40 BME 0 0 0 10 70
FMAN40 C 0 0 0 10 70
FMAN40 BME, D, E, F, Pi 0 0 0 10 70
FMAF05 7 G2 F, Pi - E1 Mathematics - Systems and Transforms KS KE U W T 40 16 0 1 130
FMAF05 BME, M, N 40 16 0 1 130
FMAF05 BME, E 40 16 0 1 130
FMAF05 C, D, I, M X Please see footnote below. 40 16 0 1 130
FMAN35 3 A E, F, Pi X E1 Project in Mathematics KS KE U W T 0 0 0 10 70
FMAN35 D 0 0 0 10 70
FMAN35 E 0 0 0 10 70
FMAN35 D, F, Pi 0 0 0 10 70
FMAN10 7.5 A D, F X E1 Algebraic Structures KS KE U W T 28 10 0 0 162
FMAN10 C, Pi 28 10 0 0 162
FMAF10 5 G2 BME, C, K, M - S Applied Mathematics - Linear systems X Please see footnote below. KS KE U W T 26 10 4 0 93
FMAF10 B, D, L, W X Please see footnote below. 26 10 4 0 93
FMAB60 5 G1 M, MD - S Calculus in One Variable A3 KS KE U W T 36 20 0 0 77
FMAB60 BME 36 20 0 0 77
FMAN95 7.5 A C, D, F, MMSR X E1 Computer Vision KS KE U W T 32 0 0 2 166
FMAN95 BME, E, Pi 32 0 0 2 166
FMAA20 7.5 G1 K, W - S Linear Algebra with Introduction to Computer Tools KS KE U W T 48 24 0 0 130
FMAA20 B 48 24 0 0 130
FMAF35 6 G2 C, D, F X E1 Linear and Combinatorial Optimization KS KE U W T 26 0 4 1 130
FMAF35 BME, E, Pi 26 0 4 1 130
FMAN65 6 A F, Pi - S Mathematical Structures KS KE U W T 28 14 0 0 118
FMAN65 D 28 14 0 0 118
FMAN55 7.5 A D, E, F, M, Pi - S Applied Mathematics KS KE U W T 24 12 2 0 62 22 14 2 0 62
FMAN01 7.5 A F X E1 Biomathematics KS KE U W T 14 6 0 1 79 14 6 0 1 79
FMAN01 E, Pi 14 6 0 1 79 14 6 0 1 79
FMAB35 7.5 G1 F, Pi - S Calculus in Several Variables KS KE U W T 38 14 2 0 79 14 8 0 0 45
FMAN25 7.5 A D, E, F, Pi X E1 Calculus of Variations KS KE U W T 18 0 0 0 82 16 0 0 0 84
FMAN90 7.5 A F, Pi X E1 Advanced Course in a Selected Area of Mathematics KS KE U W T 28 0 0 1 171
FMAN90 D 28 0 0 1 171
FMAN50 3 A Pi - E International Project Course - Mathematical Modelling X Please see footnote below. KS KE U W T 0 0 0 10 40
FMAN45 7.5 A D, E, I, Pi - E1 Machine Learning KS KE U W T 28 0 0 2 170
FMAN45 BME, F, MSOC, MMSR 28 0 0 2 170
FMAB40 4 G1 Pi - S Mathematical Modelling X Please see footnote below. KS KE U W T 6 0 0 3 98
FMAF25 3 G2 Pi - S Mathematical Modelling with Statistical Applications, Project KS KE U W T 18 0 0 3 59
FMAA55 4.5 G1 IBYI, IBYV, IEA - S Mathematics, Linear Algebra KS KE U W T 28 26 0 0 66
FMAA55 IBYA, IDA 28 26 0 0 66

FMAB30 (IBYA, IBYI, IBYV) Calculus in Several Variables: The course will be held in Lund
FMAB30 (IDA, IEA) Calculus in Several Variables: The course will be held in Lund.
FMAB20 (V) Linear Algebra: The course is an admission requirement for FMNF15 Scientific Computing.
FMAF01 (D) Mathematics - Analytic Functions: Can together with FMAF05 replace FMAF10. Can also be taken as an elective course in the 4th or 5th year.
FMAN60 (I) Optimization: Compulsory course in the elective block ‘Mathematical Modelling’ for students admitted autumn 2015. The course is also an optional programme course.
FMAF05 (C) Mathematics - Systems and Transforms: Only one of the courses FMAF05 and FMAF10 may be included in a degree.
FMAF05 (D) Mathematics - Systems and Transforms: Can together with FMAF01 replace FMAF10. Only one of the courses FMAF05 and FMAF10 may be included in a degree.
FMAF10 (C) Applied Mathematics - Linear systems: Only one of the courses FMAF05 and FMAF10 may be included in a degree.
FMAF10 (D) Applied Mathematics - Linear systems: Can be replaced by FMAF01 and FMAF05 together. Only one of the courses FMAF10 and FMAF05 may be included in a degree.
FMAN50 (Pi) International Project Course - Mathematical Modelling: Specific application procedure. The course is given in August.
FMAB40 (Pi) Mathematical Modelling: All the projects must be approved during the current academic year. Thus one may not save results on single projects till a later year.

Numerical Analysis

Course Code Link to complete information about the course; study periods, programmes etc. Credits Cycle G1: Basic level
G2: Upper basic level
A: Advanced level
Programme Programme the course belongs to in this academic year. The link points to the programme page for this academic year. S.Ex. stud. The course is suitable for incoming exchange students. Language Language of the course:
E: The course is given in English
E1: The course is given in English upon request
E2: The course may be given in English
S: The course is given in Swedish
Course Name Foot­note Links KS: Course syllabus in Swedish
KE: Course syllabus in English
U: Archive with course evaluations
W: Course Web Page
T: Examination schedule
  20/21
sp1
20/21
sp2
20/21
sp3
20/21
sp4
F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions) F Lectures h (45-minute sessions) O Exercises h (45-minute sessions) L Laboratory exercises h (45-minute sessions) H Time with supervisor for projects h (45-minute sessions) S Time for self studies h (45-minute sessions)
FMNN25 7.5 A E, F, Pi X E1 Advanced Course in Numerical Algorithms with Python/SciPy KS KE U W T 28 0 0 3 169
FMNN25 D, MSOC, MMSR 28 0 0 3 169
FMNN01 7.5 A F, Pi X E Numerical Linear Algebra KS KE U W T 36 0 0 6 160
FMNN01 BME, MMSR 36 0 0 6 160
FMNN10 8 A F, I X E1 Numerical Methods for Differential Equations KS KE U W T 48 0 0 3 160
FMNN10 BME, Pi 48 0 0 3 160
FMNF15 6 G2 V - S Scientific Computing KS KE U W T 24 0 26 1 69 2 0 10 1 27
FMNF05 6 G2 D X E1 Numerical Analysis KS KE U W T 48 12 0 3 100
FMNF05 C 48 12 0 3 100
FMNN05 7.5 A F, Pi X E1 Simulation Tools KS KE U W T 28 0 0 3 169
FMNN05 D 28 0 0 3 169
FMNN30 7.5 A Pi X E Iterative Solution of Large Scale Systems in Scientific Computing X Please see footnote below. KS KE U W T Course on hold Course on hold: The course is not given this academic year, but is planned to be given next academic year.
FMNN30 F X Please see footnote below. Course on hold Course on hold: The course is not given this academic year, but is planned to be given next academic year.
FMNF10 6 G2 E, I, N X E1 Numerical Analysis X Please see footnote below. KS KE U W T 48 10 0 3 100
FMNF10 BME, M 48 10 0 3 100

FMNN30 (F, Pi) Iterative Solution of Large Scale Systems in Scientific Computing: The course is offered every other academic year and will next be offered in 2021/22.
FMNF10 (I) Numerical Analysis: Compulsory course in the elective block ‘Mathematical Modelling’ for students admitted autumn 2015. The course is also an optional programme course.

Bachelor's Projects of the Department

The list contains the bachelor's projects which are given by the department and which programme each bachelor's project is included in.

Course Code Credits Programme Programme the course belongs to in this academic year. The link points to the programme page for this academic year. Course Name Links KS: Course syllabus in Swedish
KE: Course syllabus in English
U: Archive with course evaluations
W: Course Web Page
T: Examination schedule
FMSL01 15 C, D, E, F, I, Pi Bachelor Project in Mathematical Statistics KS KE U W
FMAL01 15 C, D, E, F, Pi Bachelor Project in Mathematics KS KE U
FMNL01 15 D, E, F, Pi Bachelor Project in Numerical Analysis KS KE U W

Degree Projects of the Department

The list contains the degree projects which are given by the department and which programme each degree project is included in.

Course Code Credits Programme Programme the course belongs to in this academic year. The link points to the programme page for this academic year. Course Name Links KS: Course syllabus in Swedish
KE: Course syllabus in English
U: Archive with course evaluations
W: Course Web Page
T: Examination schedule
FMSM05 30 MMSR Degree Project in Mathematical Statistics KS KE U
FMSM01 30 BME, C, D, E, F, I, Pi, RH Degree Project in Mathematical Statistics for Engineers KS KE U W
FMAM02 30 MMSR Degree Project in Mathematics KS KE U
FMAM05 30 BME, C, D, E, F, I, M, Pi Degree Project in Mathematics for Engineers KS KE U
FMNM01 30 D, E, F, I, Pi Degree Project in Numerical Analysis KS KE U W