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LTH Courses

Faculty of Engineering | Lund University

Courses for MMSR Programme and Class H19

Master's programme in Machine Learning, Systems and Control  H19 

Study Year 2, Academic Year 2020/21 (Mandatory Courses)

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
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)
FRTN55 7.5 A X E Automatic Control, Advanced Course KS KE U W T 30 28 12 0 130

Elective Courses - MMSR

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
Year Study year the course belongs to according to normal study plan. From year Students are permitted to read the course from this year of study. 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
  sp1 sp2 sp3 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 2 - 20/21 2 X E1 Advanced Course in Numerical Algorithms with Python/SciPy KS KE U W T 28 0 0 3 169
FRTF20 7.5 G2 2 - 20/21 2 X E Applied Robotics KS KE U W T 28 22 8 20 100
EDAF80 7.5 G2 2 - 20/21 2 X E Computer Graphics KS KE U W T 26 0 10 0 160
EITG05 7.5 G2 2 - 20/21 2 X E Digital Communications KS KE U W T 24 28 4 0 144
INTN01 7.5 A 2 - 20/21 2 X E Innovation Engineering KS KE U W T 80 4 0 15 100
EDAP20 7.5 A 2 - 20/21 2 X E Intelligent Autonomous Systems KS KE U W T 28 0 14 0 156
EDAN20 7.5 A 2 - 20/21 2 X E Language Technology KS KE U W T 20 0 14 0 160
FMSF15 7.5 G2 2 - 20/21 2 X E Markov Processes KS KE U W T 26 16 6 0 140
FMNN01 7.5 A 2 - 20/21 2 X E Numerical Linear Algebra KS KE U W T 36 0 0 6 160
FRTN50 7.5 A 2 - 20/21 2 X E Optimization for Learning KS KE U W T 28 28 0 10 130
FMSF10 7.5 G2 2 - 20/21 2 X E Stationary Stochastic Processes KS KE U W T 22 16 6 0 145
FMAN80 7.5 A 2 - 20/21 2 X E1 Functional Analysis and Harmonic Analysis KS KE U W T 20 10 0 0 108 8 4 0 0 50
FMAN15 7.5 A 2 - 20/21 2 X E Nonlinear Dynamical Systems KS KE U W T 16 6 0 0 78 14 8 0 0 78
EDAN95 7.5 A 2 - 20/21 2 X E Applied Machine Learning KS KE U W T 28 0 14 0 156
EITN70 7.5 A 2 - 20/21 2 X E Channel Coding for Reliable Communication KS KE U W T 28 14 0 2 156
EDAN01 7.5 A 2 - 20/21 2 X E1 Constraint Programming KS KE U W T 20 0 12 0 160
EDIN01 7.5 A 2 - 20/21 2 X E1 Cryptography KS KE U W T 36 14 0 2 148
FMSN45 7.5 A 2 - 20/21 2 X E Mathematical Statistics, Time Series Analysis KS KE U W T 24 12 12 5 120
FMAN30 7.5 A 2 - 20/21 2 X E1 Medical Image Analysis KS KE U W T 32 0 0 3 165
FRTN05 7.5 A 2 - 20/21 2 X E Non-Linear Control and Servo Systems KS KE U W T 28 28 12 0 130
FRTN40 7.5 A 2 - 20/21 2 X E Project in Automatic Control KS KE U W T 0 0 0 40 160
BMEN15 7.5 A 2 - 20/21 2 X E Signal Separation - Independent Components KS KE U W T 14 28 8 0 150
FMSN20 7.5 A 2 - 20/21 2 X E Spatial Statistics with Image Analysis KS KE U W T 26 0 18 5 150

Degree Projects - MMSR

The list contains the degree project courses that are included in the MMSR programme.

Course Code Credits 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
FRTM05 30 Degree Project in Automatic Control KS KE U
EDAM01 30 Degree Project in Computer Sciences KS KE U
EITM02 30 Degree Project in Electrical and Information Technology KS KE U W
FMSM05 30 Degree Project in Mathematical Statistics KS KE U
FMAM02 30 Degree Project in Mathematics KS KE U