GRA 4163 Consultancy Project for Data Science
GRA 4163 Consultancy Project for Data Science
This course intends to 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 and to make a presentation of the solution.
After having completed this course, students should be familiar with tools and knowledge to allow them to map a specific problem for a company/entity. The problems can be of national or international application. The students will also gain domain knowledge in the industry under analysis.
Students will need to 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.
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 students will learn how to identify the correct problem, how to outline and structure this problem. Then they will be given tools to analyse the problem using common consulting tools like MECE, SCQA, Logic Trees, Decision trees, hypothesis driven solution generation, etc,..
In the presentation part, the students will learn how to structure and present a solution to a client, and also how Storytelling can be a forceful toold for conveying a suggested solution.
A combination of webinars and asynhronous videos will constitute the main bulk of the course.
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: Portfolio Assessment PDF Exam/hand-in semester: First Semester Weight: 100 Grouping: Group/Individual (1 - 3) Duration: 1 Semester(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.
B - Approximately 8 weeks into the semester there will be a peer review process where you give feedback to each other
C - Approximately 12 weeks into the semester, there will be 1-on-1 feedback with the course coordinator via Zoom
It is expected that you are active in A, that you follow up on the assignment during B (you will also be evaluated based on the input you have given), and that you submit during C.