Data Science is one of the areas of informatics that has flourished most in the last decade, and the basis of many of the conveniences the internet offers today. It is closely related to artificial intelligence, automated learning, big data, predictions and deep learning - the area where Google, Facebook, Amazon, Apple, IBM and Microsoft invest heavily. In this module students take the position of a real scientist-analyst who has a problem to solve, and work through the steps a data scientist takes, from obtaining the data and describing the problem to solving it.
After the module, students will learn- Different methods of structuring data
- Different data types, with their advantages and disadvantages
- How a data set can be investigated, and what criteria to take into account
- Simple prediction algorithms - decision tree, Random Forest, SVM, KNN
- Statistical concepts for interpreting results
- Simple clustering algorithms - K-Means, DBScan - and their trade-offs
- Ways of displaying results, and simple chart types
Soft skills: work with information, manage attention, and understand your own task within collective work.