EPN-V2

STKD6510 Data Science for Social Innovations II Emneplan

Engelsk emnenavn
Data Science for Social Innovations II
Studieprogram
International Summer School - Faculty of Technology, Art and Design
Omfang
10.0 stp.
Studieår
2017/2018
Programplan
Emnehistorikk

Innledning

None.

Forkunnskapskrav

One half year of university studies (30 ECTS), in addition to the international summer school's general requirement. The requirement needs to be met by 1 March.

Læringsutbytte

After completing this course the student should have the following learning outcome:

Knowledge

On successful completion of this course the student has leading knowledge of:

  • the potential of data analytics for solving different real-life problems
  • the core principles of data analytics (machine learning, statistics)
  • the main components of data analytics from infrastructure/technical perspectives
  • the visualization techniques to understand and/or communicate data and findings
  • programming languages applicable to data analytics including, for example, SQL, Python, Matlab, R, or SPSS

Skills

On successful completion of this course the student has a progressive ability to:

  • apply data analytics techniques to formulate a hypothesis, collect data, analyze it and reach conclusions about the data
  • critically draw conclusions from different sources of data
  • plan and design a real-world data analytics application
  • analyze real-world data by building an app with a real-world application
  • clearly identify and define a problem and craft a solution using data analytics
  • construct a data analytics solution from a set of general requirements such as organizational goals or user scenarios.
  • synthesize primary and secondary data sources the ability to accurately pinpoint trends, correlations and patterns in complex data sets
  • identify new opportunities for organizational change including process improvements, cost reduction or efficiency improvements.

General Competence

On successful completion of this course the student is proficient and can master:

  • data analytics principles
  • methods/tools for data analytics and data visualization
  • using data analytics to solve real-world problems
  • data analytics visualizations in presentations

Arbeids- og undervisningsformer

The course comprises 40 hours of language instruction (4 hours * 10 weeks) organized as whole class instruction.

Arbeidskrav og obligatoriske aktiviteter

None.

Vurdering og eksamen

  • Oral examination of a group project, which counts for 60% of the grade.
  • A 4,000 to 6,000-word group project report, which counts for 40% of the grade

Each group may consist of 2-5 candidates.

Oral presentations cannot be appealed.

Both exams must be passed in order to pass the course.

Vurderingsuttrykk

The final assessment will be graded on a grading scale from A to E (A is the highest grade and E the lowest) and F for fail.

Sensorordning

Two internal examiners will be used.