| Kredit: | 6 |
|---|---|
| Role předmětu: | Anglicky Bakalářský - povinně volitelný Bakalářský - vše Bankovnictví a podnikové finance - povinně volitelné BEF - elective Centrální bankovnictví a finanční regulace - povinně volitelný CSF - elective Finanční trhy a datová analýza - povinně specializační Magisterský - vše MEF - elective MFDA - core Semestr - zimní |
| Garanti: | prof. PhDr. Ladislav Krištoufek Ph.D. |
| Stránky kurzu: | JEM227 |
| Literatura: | Mandatory literature: - Ledolter, Johannes (2013): Data Mining and Business Analytics with R, John Wiley & Sons, Hoboken, New Jersey, NJ, USA - Toomey, Dan (2014): R for Data Science, Packt Publishing Ltd., Birmingham, UK - Zumel, Nina & Mount, John (2014): Practical Data Science with R, Manning Publications Co., Shelter Island, NY, USA Additional suggested literature: - Grolemung, Garret (2014): Hands-On Programming with R, O'Reilly Media Inc., Sebastopol, CA, USA - Ojeda, Tony et al. (2014): Practical Data Science Cookbook, Packt Publishing Ltd., Birmingham, UK On-line sources: DataCamp.com The course is currently sponsored by Ernst & Young, s.r.o. (EY). We thank EY for their sponsorship! |
| Popis: | Introductory course to Data Science with applications in the R programming environment. Special focus is put on understanding of basic practical programming in R, covering model evaluation, memorization methods, advanced regression techniques, and training variance reduction. The Data Science with R I course will be followed by Data Science with R II covering clustering, text mining, support vector machines, neural networks, and networks. |
