Introduction to data science

The course is an introductory overview of topics relevant to data science. The following topics will be presented to students through lectures by faculty members and guest lecturers from industry and research institutions:

Working with data. Getting. Processing. Storing. Cleaning. Summarizing. Visualizing.

Analytics. Prediction. Clustering. Statistical inference.

Business and social aspects. Privacy. Security. Ethics. Licensing. Intellectual property.

Best practices (tools). Programming, coding standards (Python). Versioning (Github). Reproducibility (Jupyter). Typsetting (LaTeX). Public repositories (ArXiv, Zenodo).