lunduniversity.lu.se

LTH Courses

Faculty of Engineering | Lund University

Courses for MMSR Programme and Class H21

Master's programme in Machine Learning, Systems and Control  H21     

Study Year 1, Academic Year 2021/22 (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
  21/22
sp1
21/22
sp2
21/22
sp3
21/22
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)
FMAN20 7.5 A X E1 Image Analysis KS KE U W T 32 0 0 2 166
FRTF25 7.5 G2 - E Introduction to Machine Learning, Systems and Control KS KE U W T 16 0 12 0 72 14 0 6 0 80
FRTN65 7.5 A X E Modelling and Learning from Data KS KE U W T 16 10 4 0 70 14 10 8 0 68
EXTQ40 7.5 A - E1 Introduction to Artificial Neural Networks and Deep Learning KS KE U W T 34 10 30 0 126

Study Year 1, Academic Year 2021/22 (Elective 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
  21/22
sp1
21/22
sp2
21/22
sp3
21/22
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)
EDAP01 7.5 A X E Artificial Intelligence KS KE U W T 28 0 0 0 170
FMSN50 7.5 A X E Monte Carlo and Empirical Methods for Stochastic Inference X The course is to be studied together with MASM11. KS KE U W T 28 0 12 5 140
FRTN60 7.5 A - E Real-Time Systems KS KE U W T 34 22 12 0 132
FMAN45 7.5 A - E1 Machine Learning KS KE U W T 28 0 0 2 170
FRTN70 7.5 A X E Project in Systems, Control and Learning KS KE U W T 0 0 0 40 160

FMSN50 Monte Carlo and Empirical Methods for Stochastic Inference: The course is to be studied together with MASM11.

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)
EDAN70 7.5 A 1 1 X E1 Project in Computer Science KS KE U W T 2 4 0 12 182
EDAN70 2 4 0 12 182
FMAN95 7.5 A 1 1 X E1 Computer Vision KS KE U W T 32 0 0 2 166
FRTN75 7.5 A 1 1 X E Learning-Based Control X Replaces FRTN15 Predictive Control. KS KE U W T 28 28 12 0 130
BMEN20 7.5 A 1 1 X E1 Project Course in Signal Processing – from Idea to App KS KE U W T 8 0 12 8 172
EDAN70 7.5 A 1 1 X E1 Project in Computer Science KS KE U W T 2 4 0 12 182
EDAN15 7.5 A 1 1 X E Design of Embedded Systems KS KE U W T 24 4 14 0 150
EDAN40 7.5 A 1 1 X E Functional Programming KS KE U W T 28 6 0 0 166
EITN45 7.5 A 1 1 X E Information Theory KS KE U W T 26 14 0 0 160
FMSN30 7.5 A 1 1 X E Linear and Logistic Regression KS KE U W T 24 0 26 2 120
FRTN30 7.5 A 1 1 X E Network Dynamics KS KE U W T 28 28 16 0 130
EDAN70 7.5 A 1 1 X E1 Project in Computer Science KS KE U W T 2 4 0 12 182

FRTN75 Learning-Based Control: Replaces FRTN15 Predictive Control.