• Created by Unknown User (drosshau), last modified by Unknown User (trulsmp) on 06.02.2017

Master DT 2017, ref. karies@stud.ntnu.no

UWA-fagStpOverlappStp uspes ITStp uspesKommentarOK
CITS 1001 - Object-oriented Programming & Software Engineering7,5TDT4100 Java (7,5)   2016.07.07 RS
CITS 2401 - Computer Analysis & Visualization7,5TDT4105 ITGK_Matlab (5)2,5 Prog-delen2016.07.07 RS
CITS 4401 - Software Requirements and Design7,5

IT3010 Research-based Innovation Methods CS

   2015.07.30 RS
CITS 4401 - Software Requirements and Design7,5TDT4242 Advanced Software Design    2015.07.30 RS
CITS 5501 - Software Testing and Quality Assurance7,5TDT4242 - Kravspesifikasjon og testing   2015.04.24 RS
CITS 5551 - Software Engineering Design Project 17,5TDT4290 - KPro   2015.04.24 RS
GENG 5505 - Project Management and Engineering Practice7,5EiT   2015.04.24 RS
  • No labels

1 Comment

  1. Unknown User (sebasto)

    CITS5508

    http://handbooks.uwa.edu.au/unitdetails?code=CITS5508

     

    • Extract meaningful knowledge from large amounts of data
    • Understanding of mining techniques used for science and businessTopics
      • Association rule mining (rule-based)
      • Market basket analysis (model-based)Unsupervised machine learning
        • K-means clustering
        • Density based clustering
        • Hierarchical clustering
        • Subspace clustering
    • Supervised machine learning (case-based)
      • Neural networks
      • Decision trees/graphs
      • Vector machines
      • Bayesian networks
    		6 credits -> 7.5 ECTS

    TDT4171

    https://www.ntnu.edu/studies/courses/TDT4171/2018#tab=omEmnet

    • TDT4171
      • 3 ways of reasoning
        • rule-based
        • model-based
        • case-based
    • reasoning based on uncertainty or missing info
    • basis for machine learning
    • reasoning frameworks:
      • Bayesian networks
      • Decision graphs
    • Intro to neural networks
    • Learning outcomes:
      • Principles of AI
      • Efficient representation of uncertain knowledge
      • Decision making
      • Learning systems

    7.5 ECTS

     

    Red text highlights similarities in course descriptions

    		Pending Approval

    GENG5507

    http://handbooks.uwa.edu.au/unitdetails?code=GENG5507

     

    This unit develops students' technical and statistical skills in risk and reliability and also covers the social and organisational contexts which are so important in ensuring that products and services are designed, constructed and operated safely and reliably. The unit is taught with all the engineering disciplines in one class to reinforce the need for cross-discipline collaboration in risk and safety management.

     

    Students are able to (1) use appropriate tools to quantify risk and uncertainty; (2) select appropriate risk identification approaches; (3) use specific risk evaluation tools and models; (4) identify risk and safety controls; and (5) calculate standard reliability metrics.

    		 6 credits -> 7.5 ECTS 

    TPK5115 

    https://www.ntnu.edu/studies/courses/TPK5115/2018/1#tab=omEmnet

    		 

    Course content

    Terminology related to risk and uncertainty in projects. Main elements of risk management to deal with risk and uncertainty in projects. Review of central practical methods for identification and analysis of risk and uncertainty. Quantitative modelling of schedule and time in project. Decision theory. Cost analysis in a life time perspective. Statistical methods for parameter estimation. Use of expert judgement for assessment of parameters. Case studies related to turnarounds.

    Learning outcome

    Knowledge: Basic insight into the theoretical foundation risk management in projects. 

    Skills: Be able to perform practical risk analysis for identification, structuring and modelling risk. Be able to apply the models in the various trade-off situations related to risk. Be able to assess model parameters used in project risk management. 

    		 7.5 ECTSPending Approval 

    GENG5505

    http://handbooks.uwa.edu.au/unitdetails?code=GENG5505    		This unit introduces students to relevant aspects of project management and engineering practice that they need to successfully transition from formal education to professional practice. As the industry becomes increasingly 'project focused', employers are seeking engineers who possess strong project management knowledge, skills and capabilities in line with sustainable principles and ethical standards, to be applied to 'real world projects'. The unit focuses on real world engineering projects and benefits the students significantly by enhancing their capabilities and employability skills. In the unit, students learn to (1) research and analyse a real world engineering project to which key concepts and theories of sustainable and ethical project management are applied—implement a rigorous approach to analysing the project by applying a globally recognised project life cycle framework; (2) identify and analyse the problems encountered in each stage of the project and establish relevant inferences; (3) provide prioritised recommendations based on the benefits and consequences deriving from them; and (4) analyse project stakeholders' input and influence and manage them accordingly. Students enhance their interpersonal skills as they are required to take an active part in group meetings, share group coordination and leadership and learn how to negotiate and solve conflict. Students also liaise with key industry representatives, giving them the opportunity to establish professional relationships. 6 credits -> 7.5 ECTS

    IT3010

     

    https://www.ntnu.edu/studies/courses/IT3010#tab=omEmnet

    The course will give insight in the most important challenges for research and innovation methods in computer science, as well as theories of science. Challenges of research design and presentation of results will be covered. The course gives insight in the most used empirical research methods: Case studies, design science and surveys, with emphasis on qualitative methods. The course will also teach students to conduct methodological hypothesis testing in a given market. 

    		7.5 ECTSPending Approval