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1 Programme-specific Section of the Curriculum for the MSc Programme in Computer Science at the Faculty of Science, University of Copenhagen 2009 (Rev. 2016) Contents 1 Title, affiliation and language Title Affiliation Corps of external examiners Language Academic profile Purpose General programme profile General structure of the programme Career opportunities Description of competence profiles Competence profile Admission requirements Applicants with a Bachelor s degree in Computer Science from Danish universities Applicants with a Bachelor s degree in Science and IT Applicants with a related Bachelor s degree from Danish universities Applicants with a Bachelor s degree in Computer Science from international universities Other applicants Language requirements Prioritisation of applicants Structure of the programme Programme components Exemptions Commencement etc Validity Transfer Amendments... 7 Appendix 1 Tables... 8 Appendix 2 Interim arrangements... 9 Page 1 of 20

2 1 Title, affiliation and language A shared section that applies to all BSc and MSc Programmes at the Faculty of Science is linked to this programme-specific curriculum. 1.1 Title The MSc Programme in Computer Science leads to a Master of Science (MSc) in Computer Science with the Danish title: Cand.scient. (candidatus/candidata scientiarum) i datalogi. 1.2 Affiliation The programme is affiliated with the Study Board for Mathematics and Computer Science, and the students can both elect, and be elected, to this study board. 1.3 Corps of external examiners The following corps of external examiners is used for the central parts of the MSc Programme: Corps of External Examiners for Computer Science (datalogi). 1.4 Language The language of this MSc Programme is English. 2 Academic profile 2.1 Purpose Computer science (Danish: datalogi) is concerned with the systematic processing of information, particularly for automatic processing by computers. The concept corresponds to Informatik (German) and informatique (French). Students learn how to identify and analyse complex issues within computation and information processing on a scientific basis and at a high level of abstraction, and, through the application of relevant results and methodologies, to solve computer science problems, both of a theoretical and a practical nature, including, in particular, to design and implement correct, efficient and useful software. 2.2 General programme profile The MSc programme in Computer Science is a research-based two-year programme, building on top of a BSc programme in Computer Science or a closely related field. The programme includes a common compulsory part covering a broad range of core CS topics at a graduate level (first semester); an elective part containing both foundational courses within specific subareas (primarily second semester) and selected advanced and auxiliary topics (primarily third semester); and concluding with a MSc thesis (fourth semester). Computer Science is the key subject area of the programme. 2.3 General structure of the programme The MSc Programme is set at 120 ECTS credits. There are no defined specialisations in this programme. 2.4 Career opportunities The MSc Programme in Computer Science qualifies students for a PhD programme, and depending on the academic specialisation it may also be targeted at business functions and/or areas such as: Research, development, and consulting within the Information and Communication Technology sector. IT development and support within other sectors, such as the financial or biomedical industry, or in public administration. Page 2 of 20

3 3 Description of competence profiles Students following the MSc Programme acquire the knowledge, skills and competences listed below. Students will also acquire other qualifications through elective subject elements and other study activities. 3.1 Competence profile On completion of the programme, an MSc in Computer Science has acquired the following: Knowledge about: State-of-the-art principles for program and system development, including appropriate use of structuring methodologies and programming paradigms. The relevant mathematical, statistical, and logical foundations for constructing effective and efficient solutions to a variety of computational problems. Academic literature, terminology, traditions and research methods within computer science in general, and their area of specialization in particular. Relevant real-world applications of computer science and information technology, e.g. in business, cultural, health, environmental, and other societal contexts. Skills in/to: Identify opportunities for principled application of theoretical or foundational computer-science results or methods within practical or applied contexts. Design, implement, and maintain large and/or complex programs or systems, subject to external quality and performance constraints. Adapt and apply general mathematical models for analysis and classification of data. Combine relevant computer-science and other knowledge in order to analyse a problem with a significant computational or information-processing component, as well as assess previous attempts at solving the same problem and related problems. Select, combine, and where appropriate develop or refine theories and methods, and use these to make a significant contribution to solving computer-science problems or to promoting a scientific understanding of the problems. Evaluate a proposed solution to a problem objectively and systematically, and where appropriate involving experiments analyse the areas in which the solution is successful and unsuccessful, and identify its weaknesses, strengths and consequences. Document their own research results and discoveries in a manner that meets the requirements for academic publications. Apply and disseminate knowledge about information technology and participate in general debates on the subject. Competences in/to: Acquire a comprehensive overview of complex scientific or organizational contexts, identify and analyse the computational or information-processing problems arising in such contexts, and decompose or transform the problems into a form amenable to solution by relevant computer-science methodology. Employ general theoretical results and methods to an extent and level of formality appropriate to the complexity and criticality of the concrete task at hand. Formulate, structure, and run research-based projects, computer-science development work and other advanced assignments within information technology. Participate in larger program- or system-development teams, properly applying the relevant principles for modular software construction, and understanding how the correctness and performance of the full product follows from those properties of the individual components. Page 3 of 20

4 Take professional responsibility for the quality of a completed analysis, design, implementation, or evaluation task, based on a sound understanding and application of the relevant assessment methodologies. Acquire new knowledge in an efficient and systematic manner, and familiarise themselves with evolving computer-science subject areas at a high scientific level. 4 Admission requirements With a Bachelor s degree in Computer Science from the University of Copenhagen the student is granted reserved access and guaranteed a place on the MSc Programme in Computer Science if the student applies before the application deadline during the first application period after the completion of the Bachelor s degree. 4.1 Applicants with a Bachelor s degree in Computer Science from Danish universities Applicants with a Bachelor s degree in the following are directly academically qualified for admission to the MSc Programme. Computer Science from the University of Copenhagen Computer Science from Aalborg University Computer Science from Aarhus University Computer Science from the University of Southern Denmark 4.2 Applicants with a Bachelor s degree in Science and IT Applicants with a Bachelor s degree in Science and IT with the MSc admission course package in Computer Science from the University of Copenhagen are directly academically qualified for admission to the MSc programme. 4.3 Applicants with a related Bachelor s degree from Danish universities Applicants with a Bachelor s degree in: Mathematics from the University of Copenhagen Physics from the University of Copenhagen Communication and IT from the University of Copenhagen Software Development from the IT University of Copenhagen Software Technology from the Technical University of Denmark Informatics from Aalborg University Software from Aalborg University IT with a specialisation in Software Development from Aarhus University Information Science from Aarhus University may also be admitted if their programme includes the following: Courses in computer science corresponding to at least 45 ECTS credits, subject to the following distribution constraints: A minimum of 10 ECTS credits within the field of programming, covering at least two substantially different programming paradigms. A minimum of 10 ECTS credits within the field of computer systems architecture, including processor architecture, operating systems, data networks, databases, etc. A minimum of 10 ECTS credits within the field of theoretical computer science, including algorithms and data structures, computability and complexity, formal languages, programming language theory and compilation, etc. Courses in mathematics corresponding to a total of at least 7.5 ECTS credits within the fields of discrete mathematics, linear algebra, and mathematical modelling. Page 4 of 20

5 4.4 Applicants with a Bachelor s degree in Computer Science from international universities Applicants with a Bachelor's degree in Computer Science or an equivalent subject from international universities may also be admitted if their programme includes the following: Courses in computer science corresponding to at least 45 ECTS credits, subject to the following distribution constraints: A minimum of 10 ECTS credits within the field of programming, covering at least two substantially different programming paradigms. A minimum of 10 ECTS credits within the field of computer systems architecture, including processor architecture, operating systems, data networks, databases, etc. A minimum of 10 ECTS credits within the field of theoretical computer science, including algorithms and data structures, computability and complexity, formal languages, programming language theory and compilation, etc. Courses in mathematics corresponding to a total of at least 7.5 ECTS credits within the fields of discrete mathematics, linear algebra, and mathematical modelling. 4.6 Other applicants The Faculty may also admit applicants who, after a thorough academic assessment, are deemed to possess educational qualifications equivalent to those required in Subclauses Language requirements Applicants from Nordic Universities Applicants with a Bachelor s degree from Nordic Universities must as a minimum document English language qualifications comparable to a Danish upper secondary school English B level Non-Nordic applicants Applicants with a non-nordic Bachelor s degree must be able to document English proficiency corresponding to an IELTS test score of minimum 6.5 or a TOEFL test score of minimum 213 (computer-based), 560 (paper-based) or 83 (Internet-based). 5 Prioritisation of applicants If the number of qualified applicants to the programme exceeds the number of places available, applicants will be prioritised as follows: 1) Applicants with a Bachelor s degree in Computer Science from the University of Copenhagen seeking admission by way of direct extension of their completed BSc programme. 2) Applicants with a Bachelor s degree in Computer Science from Danish Universities 3) Applicants with a Bachelor s degree in Science and IT with the MSc admission course package in Computer Science from the University of Copenhagen. 4) Other applicants. Applicants are then prioritised according to their total number of ECTS credits within Computer Science and the grades obtained. 6 Structure of the programme The compulsory subject elements, restricted elective subject elements and the thesis constitute the central parts of the programme (Section 21 of the Ministerial Order on Bachelor and Master s Programmes (Candidatus) at Universities). Page 5 of 20

6 6.1 Programme components The programme is set at 120 ECTS credits and consists of the following: Compulsory subject elements, 30 ECTS credits. Restricted elective subject elements, 45 ECTS credits. Elective subject elements, 15 ECTS credits. Thesis, 30 ECTS credits Compulsory subject elements All of the following subject elements are to be covered (30 ECTS credits): NDAA09013U Advanced Programming AP Block ECTS credits NDAA09023U Advanced Algorithms and Data Structures AADS Block ECTS credits NDAK15006U Advanced Computer Systems ACS Block ECTS credits NDAK15007U Machine Learning ML Block ECTS credits Restricted elective subject elements 45 ECTS credits are to be covered as subject elements from the following list: NDAK16009U Visualization Vis Block ECTS credits NDAK14008U Programming Massively Parallel Hardware PMPH Block ECTS credits NDAK10006U IT Innovation and Change ITIaC Block ECTS credits NDAK16000U Algorithm Engineering AE Block ECTS credits NDAK16002U Computer Supported Cooperative Work CSCW Block ECTS credits NDAK10005U Medical Image Analysis MIA Block ECTS credits NDAK15004U Computer Game Development Project DADIU Block ECTS credits NDAK16007U Software Engineering SE Block ECTS credits NDAK14004U Web Science WS Block ECTS credits NDAA09007U Computability and Complexity CoCo Block ECTS credits NDAK10009U Computational Geometry CG Block ECTS credits NDAA08006U Semantics and Types SaT Block ECTS credits NDAA09027U Signal and Image Processing SIP Block ECTS credits NDAA09009U Numerical Optimization NO Block ECTS credits NDAK16006U Software Architecture SA Block ECTS credits NDAK15005U Information Retrieval IR Block ECTS credits NDAA09031U Proactive Computer Security PCS Block ECTS credits NDAK15018U Large-Scale Data Analysis LSDA Block ECTS credits NDAK16004U Mobile Computing MC Block ECTS credits NDAK16005U Program Analysis and Transformation PAT Block ECTS credits NDAK16005U User Interface Technology UIT Block ECTS credits NDAK14005U Randomized Algorithms RA Block ECTS credits NDAK12006U Computational Methods in Simulation CMIS Block ECTS credits NDAK16001U Approximation Algorithms APX Block ECTS credits NFKK14001U Project outside the course scope Block ECTS credits NFKK14005U Project outside the course scope Block ECTS credits Elective subject elements 15 ECTS credits are to be covered as elective subject elements. BSc subject elements corresponding to 15 ECTS credits may be included in the MSc Programme. Projects outside the course scope may be included in the elective section of the programme with up to 15 ECTS credits. Note that Projects outside the course scope may not exceed 15 Page 6 of 20

7 ECTS credits in total on the restricted elective and elective section of the programme. The regulations are described in Appendix 5 to the shared section of the curriculum. Projects in practice may be included in the elective section of the programme with up to 15 ECTS credits. The regulations are described in Appendix 4 to the shared section of the curriculum Thesis The MSc Programme in Computer Science includes a thesis corresponding to 30 ECTS credits, as described in Appendix 2 to the shared curriculum. The thesis must be written full time and the topic of the thesis must be within the academic scope of the programme Academic mobility Academic mobility requires that the student follows the rules and regulations regarding preapproval and credit transfer. The academic mobility in the MSc Programme in Computer Science is placed in block 1+2 of the second year. This means that the curriculum makes it possible to follow subject elements outside the Faculty of Science. In addition the student has the possibility to arrange similar academic mobility in other parts of the programme. 7 Exemptions In exceptional circumstances, the study board may grant exemptions from the rules in the curriculum specified solely by the Faculty of Science. 8 Commencement etc. 8.1 Validity This subject specific section of the curriculum applies to all students enrolled in the programme see however Appendix Transfer Students enrolled on previous curricula may be transferred to the new one as per the applicable transfer regulations or according to an individual credit transfer by the study board. 8.3 Amendments The curriculum may be amended once a year so that any changes enter into force on the start of the academic year. Amendments must be proposed by the study board and approved by the Dean. Notification about amendments that tighten the admission requirements for the programme will be published online at one year before they come into effect. If amendments are made to this curriculum, an interim arrangement may be added if necessary to allow students to complete their MSc Programme according to the amended curriculum. Page 7 of 20

8 Appendix 1 Tables All of the compulsory subject elements (including the thesis) defined below must be followed at the exact time planned according to the table. Table for students admitted to the programme in September (summer): Table - MSc Programme in Computer Science 1st year Block 1 Block 2 Block 3 Block 4 Advanced Programming Advanced Algorithms and Data Structures Advanced Computer Systems Restricted elective Restricted elective Machine Learning Restricted elective Restricted elective 2nd year Restricted elective Elective Restricted elective Elective Thesis Compulsory. Restricted elective. Elective. Restricted elective and elective subject elements may be taken in any order. Table for students admitted to the programme in February (winter): Table - MSc Programme in Computer Science* 1st year Block 3 Block 4 Block 1 Block 2 Restricted elective Restricted elective Restricted elective Restricted elective Advanced Programming Advanced Algorithms and Data Structures Advanced Computer Systems Machine Learning 2nd year Restricted elective Elective Restricted elective Elective Thesis Compulsory. Restricted elective. Elective. Restricted elective and elective subject elements may be taken in any order. * This table is only relevant for students who begin the MSc Programme in February (block 3) Page 8 of 20

9 Appendix 2 Interim arrangements The Shared Section of the BSc and MSc Curricula for Study Programmes applies to all students. The interim arrangements below only consist of parts where the current curriculum differs from the rules and regulations that were previously valid. Therefore, if information about relevant rules and regulations are missing, it can be found in the curriculum above. 1 General changes for students admitted in the academic year 2016/17 Students admitted to the MSc Programme in the academic year 2016/17 must finish the programme with the original curriculum structure under which they were admitted. Prioritisation of applicants Applicants with a Nordic Bachelor s degree in Computer Science will be prioritised together with applicants with a Danish Bachelor s degree in Computer Science. 2 General changes for students admitted in the academic year 2015/16 Students admitted to the MSc Programme in the academic year 2015/16 must finish the programme with the original curriculum structure under which they were admitted. Restricted elective subject elements 15 ECTS credits may be covered by subject elements from the list in the curriculum above and by courses from following list: Restricted elective subject elements offered as part of the curriculum (see above) NDAK15017U Interactive Data Exploration IDE Block ECTS credits NDAK12002U Vision and Image Processing VIP Block ECTS credits NDAK13000U Extreme Multiprogramming XMP Block ECTS credits NDAK15012U Advanced Topics in Human-Centered ATHCC Block ECTS credits Computing NFYK13012U Cluster Architectures and Computations CAC Block ECTS credits NDAK14003U Discrete optimization* DO Block ECTS credits *The course is not offered in the academic year 2016/17 3 General changes for students admitted in the academic year 2014/15 Students admitted to the MSc Programme in the academic year 2014/15 must finish the programme with the original curriculum structure under which they were admitted. Structure of the programme The programme is continued in the present curriculum but has been changed in its composition of the restricted elective and elective subject elements. The specialisation is set at 120 ECTS credits and consists of the following: Compulsory subject elements, 30 ECTS credits Restricted elective subject elements, 30 ECTS credits Elective subject elements, 30 ECTS credits Thesis, 30 ECTS credits. Compulsory subject elements The following subject elements are to be covered (30 ECTS credits): NDAA09013U Advanced Programming Block ECTS credits Page 9 of 20

10 NDAA09023U Advanced Algorithms and Data Structures Block ECTS credits NDAA09004U Principles of Computer Systems Design Discontinued* 7.5 ECTS credits NDAA09028U Statistical Methods for Machine Learning Discontinued* 7.5 ECTS credits * See course specific interim arrangements below. Restricted elective subject elements 30 ECTS credits are be covered by subject elements from the following list: Restricted elective subject elements offered in this curriculum (see above) Subject elements held by Department of Computer Science on MSc level (30 ECTS credits) Project outside the course scope with principal advisor from the Department of Computer Science (up to 15 ECTS credits). Thesis The thesis may either be prepared by as a full time project at the end of the study programme or concurrently with other subject elements. However, the thesis must conclude the programme. 4 Structure of the programme for students admitted in the academic year 2013/14 or earlier Students admitted to the MSc Programme in the academic year 2013/14 or earlier must finish the programme with the original curriculum structure under which they were admitted. 4.1 Specialisations Students admitted to the MSc Programme in the academic year 2013/14 are allowed to finish their programme with one of the specialisations that were outlined in the curriculum General profile Structure of the programme The specialisation is set at 120 ECTS credits and consists of the following: Compulsory subject elements, 30 ECTS credits Restricted elective subject elements, 30 ECTS credits Elective subject elements, 30 ECTS credits Thesis, 30 ECTS credits. Compulsory subject elements The following subject elements are to be covered (30 ECTS credits): NDAA09023U Advanced Programming Block ECTS credits NDAA09023U Advanced Algorithms and Data Structures Block ECTS credits NDAA09004U Principles of Computer Systems Design Discontinued* 7.5 ECTS credits NDAA09028U Statistical Methods for Machine Learning Discontinued* 7.5 ECTS credits * See course specific interim arrangements below. Restricted elective subject elements 30 ECTS credits are be covered by subject elements from the following list: Restricted elective subject elements offered in this curriculum (see above) Subject elements held by Department of Computer Science on MSc level (30 ECTS credits) Project outside the course scope with principal advisor from the Department of Computer Science (up to 15 ECTS credits). Competence profile On completion of the programme, an MSc in Computer Science has acquired the following: Page 10 of 20

11 Knowledge about: Their area of specialisation at a high scientific level, and in adjacent subject areas at a general scientific level. Academic literature within their area of specialisation, as well as within several other areas of computer science. Computer science's academic traditions. Real-world applications of information technology, e.g. in business, cultural, environmental and other social contexts. Skills to: Conduct scientific work, including critically analysing and evaluating others' research, and assessing the results of this work in multiple contexts. Program using algorithmics, design computer systems, and apply mathematical methods to the analysis of data and program. Combine relevant computer science and other knowledge in order to analyse a computerscience problem, as well as evaluate previous attempts at solving the same problem and related problems. Critically evaluate and select, combine and if appropriate develop theories and methods, and use these to make a significant contribution to solving computer science problems or promoting understanding of the problems. Evaluate a computer-science solution to a problem objectively and systematically, and where appropriate involving experiments analyse the areas in which the solution is successful and unsuccessful, and identify its weaknesses, strengths and consequences. Document their own research results and discoveries in a manner that meets the requirements for academic publications of international standard. Apply and disseminate knowledge about information technology and participate in general debates on the subject. Competences to: Acquire new knowledge in an efficient and systematic manner, and familiarize themselves with computer-science subject areas at a high scientific level Identify and analyse complex computer-science problems in a scientific manner, and apply computer-science methodology in a systematic manner to devise both theoretical and practical solutions. Acquire an overview of and analyse large volumes of data and complex computer science contexts. Formulate, structure and run research projects, computer-science development work and other advanced assignments within information technology. Participate as an independent contributor in computer-science research groups, including international groups Algorithms and Data Structures Structure of the programme The specialisation is set at 120 ECTS credits and consists of the following: Compulsory subject elements, 60 ECTS credits Restricted elective subject elements, 15 ECTS credits Elective subject elements, 15 ECTS credits Thesis, 30 ECTS credits. Compulsory subject elements The following subject elements are to be covered (60 ECTS credits): Page 11 of 20

12 NDAA09013U Advanced Programming Block ECTS credits NDAA09023U Advanced Algorithms and Data Structures Block ECTS credits NDAA09007U Computability and Complexity Block ECTS credits NDAK10009U Computational Geometry Block ECTS credits NDAK11006U Topics in Algorithms and Data Structures Block ECTS credits NDAA09004U Principles of Computer Systems Design Discontinued* 7.5 ECTS credits NDAA09028U Statistical Methods for Machine Learning Discontinued* 7.5 ECTS credits NDAA09012U Data Structures: Theory and Practice Discontinued* 7.5 ECTS credits * See course specific interim arrangements below. Restricted elective subject elements 15 ECTS credits are be covered by subject elements from the following list: Restricted elective subject elements offered in this curriculum (see above) Subject elements held by Department of Computer Science on MSc level (15 ECTS credits) Project outside the course scope with principal advisor from the Department of Computer Science (up to 15 ECTS credits). Competence profile On completion of the programme, an MSc in Computer Science with a specialisation in Algorithms and Data Structures has acquired the following additional: Knowledge about: Fundamental algorithms and data structures. Formal models of computation and complexity Techniques for proving correctness and complexity. General algorithm paradigms (e.g. incremental, divide-and-conquer, dynamic programming, plane sweep; randomised and approximation algorithms). Selected advanced subjects, e.g. parallel algorithms. Conducting and evaluating computer-based comparisons of algorithms. Skills to: Prove correctness of algorithms and data structures. Argue about time- and space complexity (worst-case, expected). Decide whether a problem can be solved in polynomial time. Solve NP-hard optimisation problems by both exact and heuristic methods. Implement, test and conduct experimental analyses of algorithms and data structures. Competences to: Construct, verify, compare and evaluate algorithms in relation to particular questions. Identify sub-problems in complex questions, for which effective algorithms, data structures and paradigms can be used Computational and Mathematical Modelling Structure of the programme The specialisation is set at 120 ECTS credits and consists of the following: Compulsory subject elements, 60 ECTS credits Restricted elective subject elements, 15 ECTS credits Elective subject elements, 15 ECTS credits Thesis, 30 ECTS credits. Compulsory subject elements The following subject elements are to be covered (60 ECTS credits): Page 12 of 20

13 NDAA09023U Advanced Programming Block ECTS credits NDAA09023U Advanced Algorithms and Data Structures Block ECTS credits NDAA09027U Signal and Image Processing Block ECTS credits NDAA09009U Constrained Continuous Optimization Block ECTS credits NDAK12006U Computational Methods for Simulation Block ECTS credits NDAA09022U Advanced Topics in Data Modelling Block ECTS credits NDAA09004U Principles of Computer Systems Design Discontinued* 7.5 ECTS credits NDAA09028U Statistical Methods for Machine Learning Discontinued* 7.5 ECTS credits * See course specific interim arrangements below. Restricted elective subject elements 15 ECTS credits are be covered by subject elements from the following list: Restricted elective subject elements offered in this curriculum (see above) Subject elements held by Department of Computer Science on MSc level (15 ECTS credits) Project outside the course scope with principal advisor from the Department of Computer Science (up to 15 ECTS credits). Competence profile On completion of the programme, an MSc in Computer Science with a specialisation in Computational and Mathematical Modelling has acquired the following additional: Knowledge about: Numerical methods for data analysis, modelling and simulation. Optimization methods for data analysis, modelling and simulation. Statistical methods for data modelling and analysis. Conduct and evaluation of computer-based experiments. Skills to: Represent and analyse data derived from 'noisy' digitized measurements, e.g. physical observation of signals, images and sequences. Apply, implement and evaluate mathematical models for analysis, synthesis and simulation. Report back on analyses, implementations and evaluations, including explaining the limitations on the use of specific models, as well as choices made during the modeling of a concrete problem. Formulate and evaluate hypotheses that can be tested experimentally, and design, perform and process results of experiments. Competences to: Analyse, critically evaluate, compare and process complex problems involving data analysis, modeling and simulation of scientific and related conditions. Independently combine existing mathematical models for the analysis and synthesis of discrete data, and manage development situations that require the development of new models and methods Specialisation in Computer Science Innovation Structure of the programme The specialisation is set at 120 ECTS credits and consists of the following: Compulsory subject elements, 60 ECTS credits Restricted elective subject elements, 15 ECTS credits Elective subject elements, 15 ECTS credits Thesis, 30 ECTS credits. Page 13 of 20

14 Compulsory subject elements The following subject elements are to be covered (60 ECTS credits): NDAA09023U Advanced Programming Block ECTS credits NDAA09023U Advanced Algorithms and Data Structures Block ECTS credits NDAK10006U IT Innovation and Change Block ECTS credits NFYA08007U Knowledge-based Entrepreneurship Block ECTS credits NDAA09029U Project course: Development Studio Discontinued* 15 ECTS credits NDAA09004U Principles of Computer Systems Design Discontinued* 7.5 ECTS credits NDAA09028U Statistical Methods for Machine Learning Discontinued* 7.5 ECTS credits * See course specific interim arrangements below. Restricted elective subject elements 15 ECTS credits are be covered by subject elements from the following list: Restricted elective subject elements offered in this curriculum (see above) Subject elements held by Department of Computer Science on MSc level (15 ECTS credits) Project outside the course scope with principal advisor from the Department of Computer Science (up to 15 ECTS credits). Competence profile On completion of the programme, an MSc in Computer Science with a specialisation in Computer Science Innovation has acquired the following additional: Knowledge about: Understanding organisations. Feasibility studies. Business models. Concept development. Generating ideas. Entrepreneurship. Innovation processes. Skills to: Evaluate the need for computer-based innovation, initiate a process, and move innovation forward in an organization or as a start-up company. Analyse the interaction between IT and social stakeholders in an organizational context. Develop and implement innovative IT projects within existing organizations. Analyse a company's current problems and opportunities, and develop visions for ITbased change. Identify and analyse user- and market-driven development of sustainable solutions. Develop business opportunities and assess their commercial potential based on a variety of business models. Competences to: Identify specific development needs and opportunities. Plan, develop and create viable new computer-based technologies, products and services Digital Interactive Entertainment Structure of the programme The specialisation is set at 120 ECTS credits and consists of the following: Compulsory subject elements, 60 ECTS credits Restricted elective subject elements, 15 ECTS credits Page 14 of 20

15 Elective subject elements, 15 ECTS credits Thesis, 30 ECTS credits. Compulsory subject elements The following subject elements are to be covered (60 ECTS credits): NDAA09023U Advanced Programming Block ECTS credits NDAA09023U Advanced Algorithms and Data Structures Block ECTS credits NDAK15004U Computer Game Development Project Discontinued* 30 ECTS credits NDAA09004U Principles of Computer Systems Design Discontinued* 7.5 ECTS credits NDAA09028U Statistical Methods for Machine Learning Discontinued* 7.5 ECTS credits * See course specific interim arrangements below. Restricted elective subject elements 15 ECTS credits are be covered by subject elements from the following list: Restricted elective subject elements offered in this curriculum (see above) Subject elements held by Department of Computer Science on MSc level (15 ECTS credits) Project outside the course scope with principal advisor from the Department of Computer Science (up to 15 ECTS credits). Competence profile On completion of the programme, an MSc in Computer Science with a specialisation in Digital Interactive Entertainment has acquired the following additional additional: Knowledge about: Numerical methods for data analysis, modeling and simulation. Methods of representation and visualization of virtual worlds. The organization of games-development groups, including both the typical roles and special role of the programmer. Factors in the interaction between humans and machines. Conducting and evaluating experiments involving humans. Skills to: Program as part of a development team capable of producing games or similar interactive entertainment products. Apply, implement and evaluate mathematical and psychological models for analysis, synthesis and simulation. Report back on analyses, implementations and evaluations, including explaining the limitations on the use of specific models and choices made during the modeling of a concrete problem. Formulate and evaluate hypotheses about human use of interactive entertainment systems that can be tested experimentally, including planning for, conducting and disseminating the results of the experiments. Competencies to: Analyse, critically evaluate, compare and process complex problems involving interactive applications, with particular emphasis on entertainment. Independently and in groups, deal with development situations in which existing mathematical and psychological models, as well as experimental hardware, are combined in a new way in order to analyse and synthesize new entertainment products. Page 15 of 20

16 4.1.6 Programming Languages and Systems Structure of the programme The specialisation is set at 120 ECTS credits and consists of the following: Compulsory subject elements, 60 ECTS credits Restricted elective subject elements, 15 ECTS credits Elective subject elements, 15 ECTS credits Thesis, 30 ECTS credits. Compulsory subject elements The following subject elements are to be covered (60 ECTS credits): NDAA09023U Advanced Programming Block ECTS credits NDAA09023U Advanced Algorithms and Data Structures Block ECTS credits NDAA08006U Semantics and Types Block ECTS credits NDAA09007U Computability and Complexity Block ECTS credits NDAA09026U Topics in Programming Languages Block ECTS credits NDAA09004U Principles of Computer Systems Design Discontinued* 7.5 ECTS credits NDAA09028U Statistical Methods for Machine Learning Discontinued* 7.5 ECTS credits NDAA09032U Advanced Language Processing Discontinued* 7.5 ECTS credits * See course specific interim arrangements below. Restricted elective subject elements 15 ECTS credits are be covered by subject elements from the following list: Restricted elective subject elements offered in this curriculum (see above) Subject elements held by Department of Computer Science on MSc level (15 ECTS credits) Project outside the course scope with principal advisor from the Department of Computer Science (up to 15 ECTS credits). Competence profile On completion of the programme, an MSc in Computer Science with a specialisation in Programming Languages and Systems has acquired the following additional: Knowledge about: Formal languages and computational models, decidability and complexity. Semantics, type systems and logics of programming languages. Implementation techniques for programming languages, including automated program analysis and transformation. Skills to: Formalise well-formedness and meaning of both programmes and programming languages, for the purposes of further analysis and processing. Formulate and provide mathematical proof for relevant properties of programmes and languages. Implement programming languages on modern computation platforms via appropriate combinations of interpretation and compilation. Operationalise logical and mathematical methods through use and/or development of tools for automated processing of programs. Competences to: Construct and verify programs and program components based on specifications, including arguing with precision about the program s correctness, efficiency, and safety. Work systematically with programmes as data objects, particularly in order to construct programs for the analysis and transformation of other programs. Page 16 of 20

17 Design and implement programming and languages and language constructs, especially for use in domain-specific applications Software Development Structure of the programme The specialisation is set at 120 ECTS credits and consists of the following: Compulsory subject elements, 60 ECTS credits Restricted elective subject elements, 15 ECTS credits Elective subject elements, 15 ECTS credits Thesis, 30 ECTS credits. Compulsory subject elements The following subject elements are to be covered (60 ECTS credits): NDAA09023U Advanced Programming Block ECTS credits NDAA09023U Advanced Algorithms and Data Structures Block ECTS credits NDAA09017U Research Methods in Human-Centered Discontinued* 7.5 ECTS credits Computing NDAA09029U Project course: Development Studio Discontinued* 15 ECTS credits NDAK11001U Software Design and Software Discontinued* 7.5 ECTS credits Architecture NDAA09004U Principles of Computer Systems Design Discontinued* 7.5 ECTS credits NDAA09028U Statistical Methods for Machine Learning Discontinued* 7.5 ECTS credits * See course specific interim arrangements below. Restricted elective subject elements 15 ECTS credits are be covered by subject elements from the following list: Restricted elective subject elements offered in this curriculum (see above) Subject elements held by Department of Computer Science on MSc level (15 ECTS credits) Project outside the course scope with principal advisor from the Department of Computer Science (up to 15 ECTS credits). Competence profile On completion of the programme, an MSc in Computer Science with a specialisation in Software Development has acquired the following additional: Knowledge about: IT architecture, process models and system-development methods. Human computer interaction and interaction design. The interplay between IT and organizational and business development. Technology management, processes of change and innovation. Skills to: Identify, analyse and specify user needs and design requirements for new IT solutions. Plan and conduct design and system-development processes in such a way that space is generated for creativity, experimentations and learning, and so that the users are actively involved in the process. Analyse the interaction between IT and organization in order to identify the technical and organizational prerequisites for the successful implementation of new IT solutions. In co-operation with users and other stakeholders, draw up plans for the implementation of new IT solutions in order to effectively contribute to realizing the desired business and organizational-development processes. Page 17 of 20

18 Draw up time and resource plans for small and medium-sized system development projects. Communicate effectively with users and other stakeholders. Competencies to: Design and develop effective, useful and user-friendly software products and information systems in close co-operation with users and other stakeholders. Work systematically with the technical and organizational implementation of new IT solutions in an actual business context. Manage system development projects. 4 Course specific changes Discontinued course Interim arrangement Information Retrieval and The course was restricted elective in the academic year 2014/15 or earlier. Interaction (NDAK13001U), 7.5 ECTS credits The course was offered for the last time in the academic year 2014/15 and a third exam is offered in the academic year 2015/16. Advanced Language Processing (NDAA09032U) ), 7,5 ECTSpoint Computer Game Development Project (DADIU) (NDAK12001U), 30 ECTS-point Constrained Continuous Optimization, (NDAA09009U), 7.5 ECTS credits Principles of Computer Systems Design (NDAA09004U), 7.5 ECTS credits The course is identical to Information Retrieval (IR) (NDAK15005U), 7.5 ECTS-point. The course was a compulsory course on the specialisation in Programming Languages and Systems in the academic year 2014/15 or earlier. The course was offered for the last time in the academic year 2014/15 and a third exam is offered in the academic year 2015/16. The course is equivalent to X (X), 7.5 ECTS-point. The course was a restricted elective course on the specialisation in Digital Interactive Entertainment in the academic year 2013/14 or earlier. The course was offered for the last time in the academic year 2014/15 and a third exam is offered in the academic year 2015/16. The course is equivalent to Computer Game Development Project (DADIU) (NDAK15004U), 30 ECTS-point The course was a restricted elective course on Computational and Mathematical Modelling in the academic year 2013/14 or earlier. The course was offered for the last time in the academic year 2013/14 and a third exam is offered in the academic year 2013/14. The course has changed title in the academic year 2014/15 and is equivalent to Numerical Optimization (NO) (NDAA09009U), 7.5 ECTS credits. The course was a compulsory subject element on the specialisation General profile in computer science and restricted elective on all the other specialisations in the academic year 2013/14 or earlier. The course also was compulsory subject element on the programme in the academic year 2014/15. The course was offered for the last time in the academic year 2014/15 and a third exam is offered in the academic year 2015/16. The course has changed title and is equivalent to Advanced Computer Systems (ACS) (NDAK15006U), 7.5 ECTS credits. Page 18 of 20

19 Project course: Development Studio (NDAA09029U), 15 ECTS-point The course was a compulsory course on the specialisations Computer Science Innovation and Software Development in the academic year 2013/14 or earlier. The course was offered for the last time in the academic year 2014/15 and a third exam is offered in the academic year 2015/16. Research Methods in Human- Centered Computing (NDAA09017U), 7,5 ECTS-point Software Design and Software Architecture (NDAK11001U), 7,5 ECTS-point Statistical Methods for Machine Learning (NDAA09028U), 7.5 ECTS credits The course is equivalent to X (X), 15 ECTS credits The course was a compulsory course on the specialisation Software Development in the academic year 2013/14 or earlier. The course was offered for the last time in the academic year 2014/15 and a third exam is offered in the academic year 2015/16. The course is equivalent to X (X), 7.5 ECTS-point. The course was a compulsory course on the specialisation Software Development in the academic year 2013/14 or earlier. The course was offered for the last time in the academic year 2015/16 and a third exam is offered in the academic year 2016/17. The course is equivalent to X (X), 7.5 ECTS-point. The course was a compulsory subject element on the specialisation General profile in computer science and restricted elective on all the other specialisations in the academic year 2013/14 or earlier. The course also was compulsory subject element on the programme in the academic year 2014/15. The course was offered for the last time in the academic year 2014/15 and a third exam is offered in the academic year 2015/16. The course has changed title and is equivalent to Machine Learning (ML) (NDAK15007U), 7.5 ECTS credits Page 19 of 20

20 Appendix 3 Description of objectives for the thesis After completing the thesis, the student should have: Knowledge about: The core subject area of the thesis, as well as - where applicable - any relevant auxiliary areas, both within and outside of computer science. General principles for scientific research work, including adaptive project planning, hypothesis generation and testing, and design and execution of experiments. General principles for scientific and technical writing, including an appropriate level of formality, and correct use of references and citations. Skills in/to: Clearly formulate, delineate, motivate, and situate a scientific problem, containing a substantial computer-science component. Employ state-of-the-art methods and theories to analyze and decompose the problem, and to survey and evaluate previous attempts at solving the problem and/or related problems. Critically evaluate, select, and non-trivially combine or extend relevant results and techniques, to make significant contributions to the solution of the problem, or to the scientific understanding of the problem. Give a precise, operational description of all important aspects of the developed solution, with particular emphasis on own contributions. Objectively and systematically, and where appropriate involving experiments, assess to what extent the problem under study has been solved, and point out particular strengths, weaknesses, and consequences of the solution. Report the findings of the project in a well-structured, coherent, and comprehensive report, in accordance with academic standards for referencing and integrity, and including illustrations, tables, formulas, code, and other non-textual elements to an extent appropriate to the nature of the problem and its solution. Orally summarize and explain the main objectives, methods, results, and conclusions of the project; and interactively discuss and justify the chosen approach and resulting findings at a scientific level. Demonstrably meet the project-specific learning objectives stipulated in the thesis contract. Competences in/to: Identify and solve a non-trivial problem within computer science, or with a significant computational or IT content. Independently plan and execute, with limited supervision, a research project around the problem, and report its findings and conclusions to high standards of correctness and integrity. Assess and discuss the significance and relevance of the obtained results to the scientific discipline of computer science, as well as any possible technological or societal implications. Page 20 of 20