====== B4M36SAN -- Statistical Data Analysis ======

===== Annotation =====

This course builds on the skills developed in introductory statistics courses. It is practically oriented and gives an introduction to applied statistics. It mainly aims at multivariate statistical analysis and modelling, i.e., the methods that help to understand, interpret, visualize and model potentially high-dimensional data. It can be seen as a purely statistical counterpart to machine learning and data mining courses.

===== Information =====

  * Lecturers: [[http://ida.felk.cvut.cz/klema/|Jiří Kléma]], [[http://cs.felk.cvut.cz/en/people/pevnytom|Tomáš Pevný]], [[http://dcgi.felk.cvut.cz/people/xmikovec|Zdeněk Míkovec]]
  * Course Assistants: [[http://cs.felk.cvut.cz/en/people/lequyanh|Anh Vu Le]], [[http://cs.fel.cvut.cz/en/people/barvijac|Jáchym Barvínek]]
  * [[Evaluation|Requirements and evaluation]]
  * [[Finals|Final assignments]].
  * [[Content|Program and content of lectures and tutorials]].
  * [[Exam|Exam]].

===== Links =====

  * [[https://www.fel.cvut.cz/cz/education/rozvrhy-ng.B191/public/html/predmety/47/02/p4702306.html|Class schedule]].
  * [[http://www.fel.cvut.cz/cz/education/bk/predmety/47/02/p4702306.html|Course syllabus]].
  * [[https://cw.felk.cvut.cz/brute/teacher/course/1021|Upload system]].


==== Recommended resources ====

  * [[http://www-bcf.usc.edu/~gareth/ISL/|An Introduction to Statistical Learning - the Book]] with [[https://www.r-bloggers.com/in-depth-introduction-to-machine-learning-in-15-hours-of-expert-videos/|related slides and videos]],
  * the references in the individual lectures,
  * [[https://www.datacamp.com|Data scientist with R]].