Datan analysointi ja hyödyntäminen
| Structure Type: | Study unit |
|---|---|
| Code: | IK00BF08 |
| Curriculum: | KT 2021V |
| Level: | Bachelor of Engineering |
| Year of Study: | 3 (2023-2024) |
| Semester: | Spring |
| Credits: | 5 cr |
| Responsible Teacher: | Agbejule, Adebayo |
| Language of Instruction: | English |
Courses During the Academic Year 2023-2024
| Impl. | Group(s) | Study Time | Teacher(s) | Language | Enrolment |
|---|---|---|---|---|---|
| 3001 | ET2021V-3B, KT2021V-3B | 2024-01-08 – 2024-05-25 | Viktor Asplund | Finnish | 2023-12-01 – 2024-01-12 |
Learning Outcomes
Upon completing this course, students will be able to:
understand the concepts needed for data science
learn how to work with different types of data
learn how to plot different types of data
learn skills on how make data driven decisions
Student's Workload
70h scheduled studies
65h autonomous studies
The assessment of student’s own learning 1 h is included in contact lessons.
Prerequisites / Recommended Optional Courses
Basic knowledge of Excel
Basics of Probability and Statistics
Contents
This course teaches students how to use data in organisations. The course would prepare students to learn how to work with different types of data and make data driven decisons. This would include understanding the challenges and capabilities of making decisions using data. Topics to be covered include data manipulation, descriptive and predictive analysis. The course will include working with data and software. Contents of course include:
Evidence-based analysis
Business Analytics
Descriptive Analytics
Predictive Analyttics
Data Mining
Regional Impact
Students would be do decisions on based sound scientific principles related to issues afftect Finland and the EU.
Internationality
Students would be able to do analysis on global issues such the enviironment and climate change.
Recommended or Required Reading and Other Learning Resources/Tools
Business Analytics, 2nd Edition by John Evans
Mode of Delivery / Planned Learning Activities and Teaching Methods
Lectures, assignments, team works and project work
Assessment Criteria
1: The student is able, with guidance, to utilise the methods learnt during the study unit.
3: The student is able to utilise the methods learnt during the study unit independently.
5: The student is able to utilise the methods learnt during the study unit independently and is able apply the learnt knowledge in new contexts
Assessment Methods
Active participation, team works, exams and project work