STKD6510 Data Science for Social Innovations II Course description

One representative of the clinical training establishment and one representative of the university. The final decision on whether to award a pass or fail grade is made by the university.

SKOMPPRA4, SYBAPRA4 and SYBASPRA4 overlap 100%.

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

The course is organized around a series of lectures, workshops, home work, and a project. The lectures will introduce the topic, the workshops will provide some hands-on experience on the topic, and the home works are aimed at deepening the knowledge and consolidating the skills needed to complete the project. The project will be focused on solving a real-world problem. The content of the course, the details and depth of the topics will be adjustable according to the level of the students. The same goes for the project, that will give the opportunity to advanced students to choose the right level of challenge for them. The solution will be presented at the end of the course in the form of a sales pitch for a startup, as to convince potential investors.

This course is a blended learning course that combines four weeks full time in-person instruction with eight weeks independent study, with online supervision when required. The four week in-person module culminates in an oral exam. Feedback from the oral exam acts as a basis for independent study, which then again culminates in a submission of the final report.

None.

• 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.

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.

Two internal examiners will be used.