Basic skills for Data Management (5 cr)

Evaluation scale

H-5

Content scheduling

Weeks 36 - 48:
Introduction to data management
Introduction to Jupyter Notebook
Data storage formats
Basics of linear algebra (vectors, matrices, linear equations)
Data processing and visualization with Python
Basics of virtualization and Linux shell commands
Introduction to databases
Recap
Week 49: Exam
Week 49: Exam

Objective

After completing the course the student can:
- Describe how data can be managed and processed
- Describe how data can be stored in various places and formats
- Manage and analyze data with suitable tools
- Utilize data management tools to process data
- Understand and describe how mathematics can be used for data management

Content

Introduction to data management
Data storage formats
Data storage
Introduction to data processing
Linear algebra
Data management tools

Materials

Material available via the learning environment (ITS).

Teaching methods

Weekly contact sessions when 3 hours for theory and practical exercises.

Exam schedules

Exam in Week 49.
Retake exam in January 2025.

International connections

The course includes approximately 12 theory sessions and guided exercises sessions where students work with practical tasks.
Around half of the exercises are done during the contact hours.
Additionally, exercises for home work that will be partly demonstrated in during contact sessions.

Student workload

Contact hours
- 12 times 1h theory: 12 x 1h = 12 hours (groups together)
- 12 times 2h practice: 12 x 2h = 24 hours (in own group)
- Exam: 2 hours
- 1h Q&A sessions 5-6 times = 5 hours
TOTAL: 43 hours

Home and independent work: approximately 90 hours

Total: approximately: 130 hours

Further information

Additional information is share via ITS