Syllabus

Internship in Data Science

Code
AMI23J
Points
7.5 Credits
Level
Second Cycle
School
School of Information and Engineering
Subject field
Microdata Analysis (XYZ)
Group of Subjects
Other Interdisciplinary Studies
Disciplinary Domain
Natural Science, 100%
This course can be included in the following main field(s) of study
Microdata Analysis1
Progression indicator within (each) main field of study
1A1F
Approved
Approved, 07 November 2019.
This syllabus is valid from 01 December 2019.

Learning Outcomes

The overall goal with this course is for students to have the opportunity to apply their knowledge and skills in Data Science in a professional environment. Upon completion of the course, students will be able to:

  • describe the organisation and its activities and workflow
  • demonstrate personal accountability, and evaluate the importance of interpersonal skills and effective work habits
  • demonstrate the ability to use their previous education to analyse and resolve the business issues of the organisation
  • articulate ideas and solutions effectively in dialogue with different audiences
  • reflect on their future professional role and their own skills with particular emphasis on sustainability, business relations, and the ethical aspects of Data Science
  • identify their need for further knowledge and skills related to the activities of the workplace and workflow

Course Content

The course includes a placement at an organisation that works within the area of the student’s main field of study. The placement is to include various work tasks and is to provide opportunity for the student to gain insight into the organisation’s activities and workflow. Examples of appropriate work tasks are planning, designing, testing, or evaluating the organisation’s Data Warehouse or Data Lake, or performing predictive analytics to support management’s decision making within the organisation and its collaboration with other organisations with which it has production, customer, and supply relations.

Assessment

Compulsory preparatory seminar, workplace placement and individual written report.

Forms of Study

Preparatory seminar and work related to Data Science in an organisation that amounts to at least 150 work hours. The organisation provides a supervisor during the placement period while the course coordinator at the university provides support.

Grades

The Swedish grades U–G.

Prerequisites

  • 30 credits second level within the Mainfield of Microdata Analysis

Other Information

It is the responsibility of students to identify and find a suitable place at which to complete their placement. A description of the placement duties is required for approval by the course coordinator. The organisation at which the placement will be completed must appoint a supervisor. The student is to have continuous contact with both the supervisor at the organisation and the course coordinator at the university. An agreement is to be signed by the student, the organisation, and the university ahead of the placement.
While it is permitted for reimbursements or stipends to be offered by the organisation or other parties to students, the university bears no financial responsibility for a placement.
The window of time in which placements can be approved and assessed is stated in the course handbook.