VIKMB42 Tools and Methods of Data Analytics

Faculty of Arts
Autumn 2018
Extent and Intensity
1/1/0. 4 credit(s). Type of Completion: k (colloquium).
Teacher(s)
Mgr. Jan Mayer (lecturer)
Mgr. Pavel Klammert (lecturer)
Jan Kudělka (lecturer)
Guaranteed by
PhDr. Petr Škyřík, Ph.D.
Division of Information and Library Studies – Department of Czech Literature – Faculty of Arts
Contact Person: Mgr. Sabina Kubisová
Supplier department: Division of Information and Library Studies – Department of Czech Literature – Faculty of Arts
Timetable
Mon 18:00–19:40 L11
Prerequisites
There’s no technical prerequisites for this course. Basic computer skills are completely enough. Also, there’s no need for a special software.
Course Enrolment Limitations
The course is offered to students of any study field.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
Course objectives
The main goal of this course is to introduce the most common methods of data munging to the students.
Syllabus
  • What is data? Why do we care?
  • The basic data formats (binary, text)
  • Introduction to the internet technologies (API)
  • Basic types of databases (SQL, NoSQL)
  • Common tools for work with data (regular expressions)
  • Introduction to the R language
  • Big data
  • Open data
  • Data in big companies
  • Data and legal issues
  • Statistics basics
  • Data mining and scraping basics
  • Introduction to the machine learning
Literature
  • Big data :understanding how data powers big business. Edited by Bill Schmarzo. 1 online r. ISBN 9781118740033. info
  • MAYER-SCHÖNBERGER, Viktor and Kenneth CUKIER. Big data : a revolution that will transform how we live, work, and think. 1st pub. in pbk. London: John Murray. 242 s. ISBN 9781848547926. 2013. info
  • Big data, big analyticsemerging business intelligence and analytic trends for today's businesses. Edited by Michael Minelli - Michele Chambers - Ambiga Dhiraj. Hoboken, N.J.: John Wiley & Sons, Inc. xxiii, 187. ISBN 9781118225837. 2013. info
  • Big data for dummies. Edited by Judith Hurwitz. 1st ed. Indianapolis, Ind.: John Wiley & Sons. xxii, 311. ISBN 1118504224. 2013. info
  • SIEGEL, Eric. Predictive analytics : the power to predict who will click, buy, lie, or die. Hoboken, N.J.: John Wiley & Sons. xvii, 302. ISBN 9781118596470. 2013. info
Teaching methods
Weekly lectures. Course is available for distance students.
Assessment methods
For successful termination of the course students must a) solve homeworks and study literature b) sucessfully elaborate and defend the final project.
Language of instruction
Czech
Further Comments
Study Materials
The course is also listed under the following terms Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017.
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