Data science is the discipline of making data useful. It is a multidisciplinary field that lies at the intersection of mathematics/statistics, computer science and subject matter expertise. While technology companies were among the first to apply the techniques of data science to extract actionable knowledge from the large amount of data they collect, industries other than tech (medicine, finance, retail, automotive, etc.) are also making great strides in how they extract value from data.
We will focus on some of the important components of data science, such as:
- Business Intelligence - which is turning the company's data into the actionable form of dashboards and reports
- Machine Learning - which is, at its root, an algorithmic technique to devise predictive models, where the data generating process is treated as unknown
- Ethics - which includes the social responsibility around deploying predictive models that have been "trained" on potentially biased data
As this is an applied seminar, the focus will be on practical applications of the material in a business setting. Academic theory will be discussed only to the extent that it is used in practice.