Data Science is one of the areas of informatics that has flourished most in the last decade and is the basis of many of the amenities that the internet offers us today. This is closely related to popular concepts such as
artificial intelligence, automated learning, big data, predictions, deep learning and many more. This is the area where big companies like Google, Facebook, Amazon, Apple, IBM, Microsoft and others invest a lot of money.
In this module, students will find themselves in the position of
real scientist - analyst who needs to solve a problem. They will follow the instructions of the instructor and implement the steps taken by the Data Scientist - from obtaining the data and describing the problem to solving it.
After completing the module, students
learn:
- Different methods of data structuring
- Different data types with advantages and disadvantages
- How the data set can be investigated and what criteria can be taken into account
- Simple prediction algorithms (solution tree, Random Forest, SVM, KNN)
- Statistical concept for interpretation of results
- Simple clustering/grouping algorithms (K-Means, DBScan) with advantages, disadvantages
- Ways of displaying results and simple chart types
- Soft skills: to work with information, manage attention and understand your task in collective work