Data Analytics
Postgraduate course
- ECTS credits
- 5
- Course code
- HAIS665
- Number of semesters
- 1
- Teaching language
- English
- Resources
- Schedule
Course description
Objectives and Content
Objective
The aim of the course is to provide students with foundational knowledge and practical competence in data analytics as a field and professional practice. The course introduces key theoretical and conceptual foundations of data analytics and develops students’ ability to apply the data analytics process, from data collection and preparation to analysis, visualisation, and interpretation. The course will also provide a critical evaluation of analytical approaches, ethical and legal considerations, and effective communication of data-driven insights to diverse audiences.
Content
The course covers core topics including the data analytics lifecycle, data types and sources, data wrangling and preprocessing, basic analytical techniques, and data visualisation. Ethical, privacy, and legal aspects of data analytics are addressed throughout. The course emphasises applied, real-world cases, interdisciplinary collaboration, and clear communication of analytical reasoning and results.
Learning Outcomes
Upon completion of the course, the student will have the following learning outcomes:
Knowledge
The student can
- Explain the fundamentals of Data Analytics as a field and practice, including its role in data-driven decision-making across domains
- Describe the key stages of the data analytics process, including data collection, wrangling, analysis, visualization, and interpretation
- Describe different types of data structures, file formats, and data sources commonly used in analytics work
- Explain theoretical and conceptual foundations underpinning data analytics
- Recognise ethical, privacy, and legal considerations related to data collection, analysis, and use
Skills
The student can
- Apply the data analytics processes to real-world cases, including the stages of collecting, cleaning, and preprocessing data from diverse sources and digital systems and applying selected analytical techniques for exploring, analysing, and interpreting data
- Interpret data visualizations to communicate insights effectively to different stakeholders
- Critically evaluate data analytics approaches, results, and limitations in applied contexts
General Competence
The student can
- Work in interdisciplinary teams addressing organisational and societal challenges using data analytics
- Communicate analytical reasoning and findings clearly to both technical and non-technical audiences
ECTS Credits
Level of Study
Semester of Instruction
Place of Instruction
Required Previous Knowledge
Recommended Previous Knowledge
Credit Reduction due to Course Overlap
Access to the Course
Participants must have completed one of the following educational programmes:
- Bachelor's degree
- Master's degree
- Other degree or vocational education of at least 3 years' duration
- Education that, in accordance with Section 3-5 of the Act on Universities and University Colleges, is approved as equivalent to the aforementioned degrees or educational programmes
Teaching and learning methods
Compulsory Assignments and Attendance
Compulsory assignments and quizzes given throughout the semester must be completed and approved.
Participation in 80% course seminars.
Approved compulsory requirements are valid for three semesters.
Forms of Assessment
The course uses the following form of assessment:
Portfolio exam, individual:
- Project report (75%)
- Reflection note (25%)