GRA 4161 Internship for Data Science for Business
GRA 4161 Internship for Data Science for Business
THIS COURSE WILL BE OFFERED AS A RE-SIT EXAMINATION ONLY IN SPRING 2024.
The internship is an opportunity to work full-time at a company during your studies and gain professional experience in the data science for business domain. As a participant in the internship programme, you have been selected to work at a specific company based on both what the company is seeking and your Master specialization. The internship will give you valuable insights in real-world challenges in the broad area of data science, and should help you in applying your academic learning toward increasing organizational effectiveness and growth.
Note that in order to get a BI Internship approved as part of the degree, the student needs to apply according to BI’s procedures and submit a valid Learning Contract prior to starting their internship and in due time before the deadline.
Please be aware that the Internship period will be any time between May and August, while the examination will be in the autumn semester.
At the end of the internship, the student should be able to grasp the specific challenges faced by the company in creating value, relate academic knowledge and learn how to collaborate in offering solutions and creating new opportunities.
At the end of the internship the student is expected to have acquire an understanding of:
- the practical issues and dilemmas faced by the company on a daily basis
- how the application of data science is/can be used to create business value in the particular institutional setting
At the end of the internship the student is expected to have acquire skills related to:
- defining and executing tasks under conditions of uncertainty, change and time pressure
- supporting suggestions for practical solutions with sound argumentation and academic analysis
- applying theoretical and technical knowledge to specific tasks and problems, and collaborating and working in teams
The student, at the end of the internship, should
- reflect on the complexity of the work environment, the market forces that drive businesses and how companies create value in view of new opportunities, innovation and growth
- learn how to combine practical and theoretical knowledge in relation to data science to solve problems, challenges, and improve efficiency
Students will work for 8 weeks in a selected company and the tasks are assigned by each company. Students must attend work as agreed upon with the company they are assigned to. After the completion of the internship, the student will produce a presentation summarizing their overall internship experience. Each student is entitled to a maximum of 1.5 hours supervision.
As part of this course, it is compulsory to participate in an employability course.
The internship may be paid or unpaid.
Please be aware that the Internship period will be any time between May and August, while the examination will be in the autumn semester.
The internship is for 8 weeks, full time and a completed and an approved internship will give 6 ECTS credits. The evaluation will be based on a final oral presentation, where the students summarize their overall internship experience.
The principal aim of the presentation is to show the student's reflections on what was learned from the internship and the practices encountered, in relation to the knowledge the student acquired during the MSc studies. More specific guidelines on what the presentation should contain will be provided, but in general they should include:
- general information about the company and the department that the student was assigned to
- reflections on the overall professional experience
- information about the internship position and the work assignments
- reflections on the experience in relation to the academic knowledge acquired during the programme
- theories, methods, knowledge or skills acquired in the programme that were useful in carrying out the internship tasks
- evaluation of the student's strengths and weaknesses in doing the internship, as well as useful lessons for the student's future career.
All parts of the assessment must be passed in order to get a grade in the course.
All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
Disclaimer
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
| Assessments |
|---|
Exam category: Submission Form of assessment: Written submission Weight: 50 Grouping: Individual Duration: 1 Week(s) Comment: Students submit a company evaluation. Exam code: GRA 41611 Grading scale: Pass/fail Resit: Examination next semester, thereafter when next scheduled course |
Exam category: Activity Form of assessment: Oral examination Weight: 50 Grouping: Individual Duration: 1 Hour(s) Comment: There will be an individual oral examination, where all the students in the course will be present. Exam code: GRA 41612 Grading scale: Pass/fail Resit: Examination next semester, thereafter when next scheduled course |
All exams must be passed to get a grade in this course.
| Activity | Duration | Comment |
|---|---|---|
Feedback activities and counselling | 1.5 Hour(s) | |
Examination | 3 Hour(s) | |
Individual problem solving | 155.5 Hour(s) |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.