Application for continued programme studies, autumn 2021 Applied Data Science Master s Programme N2ADS

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Application for continued programme studies, autumn 2021 Applied Data Science Master’s Programme N2ADS

You apply for your autumn term courses 2021 within your programme at www.antagning.se / www.universityadmissions.se Apply before April 15, 2021.

Note! Since application and tuition fees have been decided for International students (citizens outside EU/EEA) from autumn 2011 and onward it is very important that you apply for your courses as a programme student otherwise you will have to pay these fees.

Application code

Course code

Name of the course

Study Period (SP)

Selecti on

Entry requirements

First cycle courses

SP1 Aug-Nov

PG or HT

48660

^DIT391 Principles of Concurrent Programming

7.5 credits

SP 1 Aug-Nov

PG The student should have successfully completed at least;

-7.5 hec in imperative/object-oriented programming such as DIT012, DIT948 or equivalent, -an additional course in programming or data structures.

-Moreover, the student must also have knowledge in propositional logic, which is acquired by successfully completing courses such as DIT980, DIT725, the part on introductory algebra from MMGD200, or equivalent.

Second cycle courses

SP1 Sep-Nov

PG or HT

48692

^DIT968 Deep machine learning

7,5 hp

SP 1 Aug-Nov

PG To be eligible to the course, the student must have a Bachelor's degree.

In particular, the student must have acquired the following knowledge:

-15 credits of courses in programming or equivalent,

-a course including probability and statistics, such as DIT862 Statistical Methods for Data Science or MSG810 Mathematical Statistics and Discrete mathematics,

-5 credits of linear algebra or equivalent -5 credits of calculus or equivalent,

-a first course in machine learning, such as DIT866 Applied Machine Learning, DIT381 Algorithms for Machine Learning and Inference, or MSA220 Statistical Learning for Big Data

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48688

^DIT285 ^Advanced

Requirements Engineering

7.5 credits

SP 1 Aug-Nov

HT The student should have a Bachelor degree in Software Engineering, Computer Science, Information Technology, Information Systems, or equivalent. Including;

- a successfully completed course in programming (e.g., DIT042 Object-oriented Programming, DIT012 Imperative Programming with Basic Object-orientation, DIT143 Functional Programming, or equivalent);

- a successfully completed project course (or bachelor thesis) in applied software development or software engineering (e.g., DIT212 Object-oriented programming project, or DIT543 Software Engineering Project)

48694

^DIT104 Interaction Design Methodology

7.5 credits

SP 1 Aug-Nov

HT To be eligible for the course the student must have succesfully completed a bachelor thesis course, e.g.

DIT561. In addition, the student must have succesfully completed a 7,5 credit course in Human-computer interaction, e.g. DIT095 or TIG091.

Applicants must prove knowledge of English: English 6/English B or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.

48671

^DIT401 ^Operating

Systems 7.5 credits

SP 1 Aug-Nov

PG Students should have successfully completed courses corresponding to 60 higher education credits of studies within the subject Computer Science, or equivalent. Including the following courses;

-a 7.5 credits course in machine oriented programming (e.g., DIT151 or equivalent), -a 7.5 credits course in data structures (e.g., DIT960 or equivalent),

-a 7.5 credits course in programming (e.g., DIT440, DIT012 or equivalent).

11751

MSA101 Computational Methods for

Bayesian Statistics 7,5 credits

SP1 Aug-Nov

PG Basic skills in mathematical statistics corresponding to at least 15 hp, in addition to the course MSG400 Stochastic Data Processing and Simulation.

11757

MMA620 High Performance Computing

7,5 credits

SP1 Aug-Nov

PG The prerequisite for the course High Performance Computing is the equivalent of 90 credits. Including the courses;

-MMG300 Multivariable Analysis, -MMG410 Numerical Analysis,

-and some basic course in programming.

48690

^DIT431 High Performance Parallel Programming

7,5 credits

SP 1 Aug-Nov

PG To be eligible for the course, students should have successfully completed courses corresponding to 105 credits within the subject of Computer Science, Mathematics, Software Engineering, or equivalent, including a 7.5 credits course in machine-oriented programming (e.g., DIT151 Machine Oriented Programming, or equivalent).

48672

^DIT051 ^Computer

Architecture 7.5 credits

SP1 Aug-Nov

PG The requirement for the course is to have successfully completed two years of studies within Computer Science or equivalent. Including course;

-DIT122 Computer system engineering (Datorsystemteknik) or equivalent is required.

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48687

^DIT246 ^Empirical

Software Engineering

7.5 credits

SP1 Aug-Nov

HT A Bachelor degree in Software Engineering, Computer Science or equivalent.

Applicants must prove knowledge of English: English 6/English B or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.

48644

^DIT878 Seminar course in data science

SP1 Aug-Nov

PG To be eligible to the course, the student should have a Bachelor's degree, and have successfully completed 30 credits of courses within the subject Data Science.

The subject of the proposed seminar course must be within the field of Data Science and have been approved by the Head of the Programme, who also decides whether or not the student has the required prerequisites within the subject area to follow the seminars.

First cycle courses

SP2 Nov-Jan

48621

^DIT621 ^Databases

7.5 credits

If you don’t have a previous course in databases you must take this course or DIT032

(in SP3)

SP2 Nov-Jan

PG The student should have successfully completed university level courses of at least 45 credits. Including;

-at least 15 credits in programming, e.g., DIT440, DIT012, DIT953, or equivalent,

-at least 7.5 credits in mathematics or mathematic reasoning, e.g., DIT980, DIT855, or equivalent, -concepts in logic, sets, functions and relations that could be acquired with, e.g., DIT980, DIT851, or equivalent.

48696

^DIT143 Functional programming

7.5 credits

SP2 Nov-Jan

PG Students must have successfully completed a 7.5 credits course in programming in a paradigm other than functional, e.g., DIT948 Programming, DIT042 Object-Oriented Programming, MVG300 Programming in Matlab, or equivalent.

48674

^DIT083 ^Testing,

debugging and verification

7.5 credits

SP2 Nov-Jan

PG The students should have successfully completed 45 hec of an education aiming at a bachelor degree within Computer Science or equivalent. Including;

-a course in discrete mathematics (such as DIT980),

-a course in object oriented programming (such as DIT012 or DIT953)

48699

^DIT046 Requirements and User Experience 7.5 credits

SP2 Nov-Jan

PG The students must have completed a 7.5 credits course in programming (e.g., DIT042 Object-oriented programming, or equivalent).

11718

MSG500 Linear Statistical Models 7,5 credits

SP2 Nov-Jan

PG For entrance to the course, knowledge corresponding to the courses MSG110 Probability Theory and MSG200 Statistical Inference is required

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Second cycle courses

SP2 Nov-Jan

48540

^DIT875 ^Research

Methods for Data Science 7.5 credits

SP 2 Nov-Jan

PG The student should have a Bachelor's degree, and have successfully completed 15 credits of courses within the subject Data Science.

48620

^DIT245 Machine Learning for natural

language processing 7,5 credits

SP 2 Nov-Jan

PG To be eligible to the course, the student should have a Bachelor's degree in any subject.

In addition, the course requires:

-7.5 credits of courses in programming or equivalent,

-a course including probability and statistics, such as DIT862 Statistical Methods for Data Science or MSG810 Mathematical Statistics and Discrete mathematics

-a first course in machine learning, such as DIT866 Applied Machine Learning,DIT381 Algorithms for Machine Learning and Inference, or MSA220 Statistical Learning for Big Data.

48677

^DIT251 Algorithms, advanced course

7.5 credits

SP2 Nov-Jan

HT Successfully completed courses corresponding to 120 hec within the subject Computer Science or equivalent. Including;

-Successful completion of DIT600 Algorithms, 7.5 hec (or equivalent).

48678

^DIT224 ^Computer

Graphics 7.5 credits

SP2 Nov-Jan

PG The students should have successfully completed courses corresponding to 90 credits within the subject of Computer Science. Including the following courses:

- 7.5 credits in data structures (DIT960 or equivalent), and

- 15 credits in imperative or object-oriented programing (DIT012 and DIT952, or equivalent).

48602

^DIT743 Computational Methods in Bioinformatics

7,5 hp

SP2 Nov-Jan

PG The student should have successfully completed 60 credits of studies in Computer Science, Software Engineering, Data Science, or equivalent. Also successfully completed;

-a course in Programming (DIT012 Imperative Programming with Basic Object-orientation, DIT042 Object-oriented Programming, DIT143 Functional programming, or equivalent)

-a basic course in discrete mathematic (DIT980, DIT856 or equivalent).

48679

^DIT250 Cryptography 7.5 credits

SP2 Nov-Jan

PG The student should have successfully completed courses corresponding to 60 hec in the subject of Computer Science or Mathematics. Including;

-7.5 hec in discrete mathematics (for example DIT980 Discrete Mathematics for Computer Scientists, the sub-course Introductory Algebra of MMG200 Mathematics 1 or equivalent);

-7.5 hec in programming (for example DIT142 Functional Programming,

DIT012 Imperative Programming with Basic Object-orientation, MVG300 Programming with MatLab or equivalent).

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48680

^DIT240 Distributed systems 7.5

credits

SP2 Nov-Jan

HT Successfully completed courses corresponding to 120 hec within the subject Computer Science or equivalent. Within the 120 hec the following courses are required;

-DIT663 Computer Networks, 7.5 hec or DIT420 Computer Communication, 7.5 hec (or equivalent) -DIT400 Operating systems, 7.5 hec or DIT390 Concurrent programming, 7.5 hec (or equivalent)

48681

^TIA106 ^Graphical

interfaces 7.5 credits

SP2 Nov-Jan

HT The student must have a Bachelor degree of 180 hec. Additionally;

-The course TIG095 Human Computer Interaction 7.5 credits, or the equivalent is required.

48683

^DIT231 Programming Language Technology

7.5 credits

SP2 Nov-Jan

PG Successfully completed courses corresponding to 60 hec in the subject of Computer Science. Including;

-7.5 hec in programming (for example DIT142 Functional programming, DIT952 Objektorienterad programmering and design, or equivalent);

-7.5 hec in data structures (for example DIT960 Data structures, DIT725 Logic, algorithms and data structures or equivalent).

48641

^DIT098 Gameplay Design 7.5 credits

SP2 Nov-Jan

HT The student must have a Bachelor's degree, 180 higher education credits or have passed 60 higher education credits in the subject Computer Science.

48643

^TIA082 Communication:

Interpersonal Communication 7.5 credits

SP 1 Sep-Nov

HT To be eligible for the course the student must have a university education of 180 hec, of which a minimum of 90 hec in a major subject

42411

^LT2114 Practical natural language processing 7.5 credits

SP2 Nov-Jan

PG Successful completion of at least 7.5 credits in programming courses such as: Programming, DIT948; Imperative Programming with Basic Object-orientation, DIT012; Functional programming, DIT142; Introduction to programming, LT2111; or equivalent.

Courses to apply for via the department Application

method

Course code

Name of the course

Study Period (SP)

Selection PG or HT

Entry requirements

Apply via the department

DIT374 Python for Data Scientists

7,5 HP (this course should

be taken the first year of studies at the programme)

SP 1 Aug-Nov

PG To be eligible in the course, the student needs a bachelor degree. Furthermore, the student needs 7.5 hec programming.

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Apply via the department

DIT891 Project in Data Science 7.5 credits

SP1 PG The student should have a Bachelor's degree and have successfully completed 15 credits of courses within the subject Data Science.

The subject of the proposed project must be within the field of Data Science and have been approved by the Head of the Programme, who also decides whether or not the student has the required prerequisites within the subject area to carry out the particular project

Apply via the department,

for instructions:

https://chal mers.instruc ture.com/co urses/232

DIT911 Master thesis in Applied data

science 30 credits

SP2 onwards PG To be eligible for this course, 60 credits of completed courses on the advanced level is required, not counting credits from an earlier, first cycle (Bachelor) degree. At least 30 credits must come from completed courses on the advanced level within the main field of study. A first cycle Bachelor degree is required. The subject of the proposed thesis must be within the chosen main field of study and have been approved by the Head of the Programme. The thesis proposal must have been approved by an examiner appointed by the department. The examiner decides whether or not the student has the required prerequisites within the subject area to carry out the particular thesis project.