- Identify the role of data and data science capability as a strategic asset;
- Knowing about descriptive, predictive and prescriptive analytics and appreciate the relationships between these streams;
- Recognize how different data science methods can support business decision-making;
- Knowing some basic data analytic techniques for solving business problems;
- Knowing about Python which is widely used in data analytics;
- Knowing about applications of data science in real world problems.
1 Overview of data science and data-analytic thinking;
2 Introducing Python;
3 Machine Learning with Python;
4 Real-world Applications of Machine Learning;
5 Data Science and Business Strategy;
- Class participation and group discussion: 10%
- Presentation and reporting of assignments: 30%
- Course project: 60%
- Provost, F. and Fawcett, T. (2013) “Data Science for Business: What you need to know about data mining and data-analytic thinking, 1st Edition.
- Jake VanderPlas (2016). “Python Data Science Handbook – Essential Tools for Working with Data”
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Call For Applications 4 PhD Scholarships in Economics, Finance & Management
Applications Doctoral Programme in Economics (with integrated M.Sc. Economic Research)
Fully Funded PhD Scholarships in Economics and Business Administration
MRes/PhD Economics and Finance programmes
PhD Program in Finance at Swiss Finance Institute