GRA 4163 Consultancy Project for Data Science
GRA 4163 Consultancy Project for Data Science
This course will give students a sense of how to solve a problem for a concrete company or public entity. Students will experience first-hand how to solve a concrete business problem in groups acting as consultants. The assignments will depend on the problem at hand, but studnets can expect to use several of their skills from other courses, but with a strong focus on problem solving for a client.
- After having completed this course, students should be familiar with tools and knowledge allowing them to solve a specific problem for a company/entity. The problems can be of national or international application.
- Specifically students will obtain an understanding of how consultants work with analytical problems, and how such problems and solutions are presented to a client.
- Students will identify a problem and analyse a dataset in order to apply specific statistical tools to solve the probllem.
- Data management skills will also be required to turn data into information and further into insight.
- Through the application of previous learnt knowledge and skills, the students will experience writing a consultancy report and presenting the report to key decision makers.
- Working in groups the students will experience and learn skills related to group related problem-solving.
- Students will specifically learn how to scope a problem, how to analyse the problem at hand, and finally how to present the findings to a client.
- Students learn how to evaluate a business problem from several angles and will experience firsthand the importance of reflecting on how the suggested solution will add value to the organization and/or sustainability to the public sector through the suggested solutions.
- The students have to be critical to any data provided and also need to critically evaluate their suggested solution.
The student groups are presented with data and a real problem from a concrete company or public entity. The data will be of a structured/semi structured format, and the inherent business problem will be roughly outlined. The students spend a total of 5 weeks applying various methods/tools to analyse the data in order to outline a suggested course of action for the business in question. The students provide a written report for evaluation.
During the course students will meet with individuals from consultancy companies sharing their insights into business analytic problem solving.
- Scoping a problem
- Analysing a business related problem using logic trees, decision trees, MECE, etc.
- Presenting the findings/solution/recommendation to a client
The learning process will be as follows (sequence changes may occur):
- Handout of data/problem 1
- Consultancy session 1 – How do consultants work?
- Q/A session from the company/entity in question
- Hand-in Solution 1
- All sessions will be held online as Webinars
Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.
Students are expected to utilize software/digital tools previously learnt in the programme.
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: 100 Grouping: Group/Individual (1 - 3) Duration: 5 Week(s) Exam code: GRA 41631 Grading scale: ECTS Resit: Examination when next scheduled course |
| Activity | Duration | Comment |
|---|---|---|
Webinar | 24 Hour(s) | |
Group work / Assignments | 100 Hour(s) | |
Prepare for teaching | 24 Hour(s) | |
Student's own work with learning resources | 12 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.