D.9. Key Learning Outcomes

1. Recognizes data types and decides which method is appropriate for data. Recognizes the problem.

2. Understands the connection between theory and practice. Solves the problems experienced in practice with theoretical background.

3. Allows diversification in software languages.

4. Has scientific ethics; be aware of the correct and meaningful interpretation of the results.

5. Improves constantly the knowledge and adapts to the developing age with the gained background.

6. Has the ability to use the acquired knowledge in interdisciplinary studies.

7. Leads to team work as well as individual work.

8. Supports the development of analytical thinking system.

9. Understands the concepts that can follow the international literature.

10. Analyzes, interprets, visualizes, evaluates and uses the applied knowledge acquired in the field of Data Science analytically and systematically.

11. Provides the ability to apply data analytics technology and tools to real-life business problems.

12. Generates solutions in line with the requirements of the age with the synthesis of mathematics, probability, basic statistics and programming.

13. Has the ability to design and implement experimental-based research.

14. Has the skills to collect data from different sources, organize it and make it ready for use.

15. Can extract data from data sources and create related database systems.