GRA 4147 Internship for Business Analytics

GRA 4147 Internship for Business Analytics

Course code: 
GRA 4147
Department: 
Marketing
Credits: 
18
Course coordinator: 
Auke Hunneman
Course name in Norwegian: 
Internship for Business Analytics
Product category: 
Master
Portfolio: 
MSc in Business Analytics
Semester: 
2021 Autumn
Active status: 
Active
Level of study: 
Master
Teaching language: 
English
Course type: 
One semester
Introduction

The internship is an opportunity to work full-time at a company during your studies and gain professional experience. This is particularly important for a programme like business analytics, an area in which companies have developed state-of-the-art technology and analytical tools for many relevant business problems. The internship will give you valuable insights in real-world challenges, and should help you in applying your academic background toward increasing organizational effectiveness and growth.

Learning outcomes - Knowledge

At the end of the internship, the student should know the specific challenges faced by companies in using analytics to create value, both for the company and for its relevant stakeholders.

The overall goal of the internship is to increase the employability of the students. More specifically, at the end of the internship, the student should have acquired an understanding of:

  • the practical issues and dilemmas faced by data-driven companies
  • the data value chain and how it can be used to develop a competitive advantage
  • the implications of using data in decision-making for the company’s data infrastructure and organizational culture and structure, and
  • the time and efficiency constraints imposed by competition

 

Learning outcomes - Skills

The student at the end of the internship is expected to acquire skills in relation to:

  • career management and job seeking
  • defining and executing tasks under conditions of uncertainty, change and time pressure
  • supporting suggestions for practical solutions with sound argumentation and grounded in analytics
  • applying theoretical and technical knowledge to specific tasks and problems

 

General Competence

The student should reflect on the complexity of the work environment, the market forces that drive businesses and how companies create value based on analytics in view of new opportunities, innovation and growth.

Course content

Students will work in groups from 1-3 for a minimum of 10 weeks (400 hours) in a selected company and the analytics-related tasks are assigned by the company. The company should be in business for at least 3 years, have 5 or more employees, and a turnover of NOK 5 million or more. Students must attend work as agreed upon with the company they are assigned to. Each student is entitled to a maximum of 3 hours of supervision. Part of the supervision is a mandatory follow-up meeting with the academic supervisor (and other internship students) half-way the semester.

As part of this course, it is compulsory to participate in an employability course. 

The internship may be paid or unpaid.               

Teaching and learning activities

The duration of the internship is a minimum of 10 weeks (400 hours), full-time. The internship will have to be completed by the end of week 43. A completed and an approved internship will give 18 ECTS credits.

Students must attend work as agreed upon with the company they are assigned to. Towards the end of/after the internship, they will write a reflection note and prepare a presentation.

Software tools: The required computer-based tools depend on the type of position the student will be working in. These requirements will be communicated by the employer in the position announcements.

Software tools
Software defined under the section "Teaching and learning activities".
Qualifications

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 spesific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Covid-19 

Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.

Teaching 

Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.

Required prerequisite knowledge

Participation requires that you have no pending courses and that you secure your own internship. See the student portal for detailed practical information.

Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Written submission
Weight: 
50
Grouping: 
Individual
Duration: 
1 Semester(s)
Comment: 
Reflection note:
The reflection note (max 10 pages) should cover the following:
1) A description of what you did during the internship.
2) A reflection on your experiences.
The latter includes answers to questions like how did the internship affect your personal growth, what was useful (and what was not), how did the internship connect to your studies, and how did you grow professionally?

Students submit a company evaluation together with their paper.
Exam code: 
GRA 41471
Grading scale: 
Pass/fail
Resit: 
Examination next semester, thereafter when next scheduled course
Exam category: 
Activity
Form of assessment: 
Presentation
Weight: 
50
Grouping: 
Individual
Comment: 
In the oral presentation, the student is expected to: 1) present general information about the company and the department that (s)he was assigned to, as well as the overall professional experience gained, 2) present specific outcomes related to the data-related internship project, and answer questions that demonstrate the ability to relate the internship experience with the academic knowledge acquired during the programme.
Exam code: 
GRA41472
Grading scale: 
Pass/fail
Resit: 
Examination next semester, thereafter when next scheduled course
Type of Assessment: 
Ordinary examination
All exams must be passed to get a grade in this course.
Total weight: 
100
Sum workload: 
0

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore acourse of 18 ECTS credit corresponds to a workload of at least 480 hours.