Checking date: 07/05/2018

Course: 2018/2019

Big Data for Business Intelligence
Study: Bachelor in Finance and Accounting (201)


Department assigned to the subject: Department of Statistics

Type: Electives
ECTS Credits: 6.0 ECTS


Students are expected to have completed
Competences and skills that will be acquired and learning results. Further information on this link
Description of contents: programme
Learning activities and methodology
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40
Basic Bibliography
  • Bradley Efron, Trevor Hastie.. Computer Age Statistical Inference: Algorithms, Evidence and Data Science.. Cambridge University Press. 2016
  • E. Alpaydin. Introduction to Machine Learning. MIT Press.. 2010
  • James, G., Witten, D., Hastie, T., Tibshirani, R.. An Introduction to Statistical Learning with Applications in R. Springer. 2013.
  • T. Hastie, R. Tibshirani, J. Friedman.. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer. . 2009
  • Trevor Hastie, Robert Tibshirani, Martin Wainwright. Statistical Learning with Sparsity: the Lasso and Generalizations. Chapman & Hall. 2015

The course syllabus and the academic weekly planning may change due academic events or other reasons.