Syllabus
Title
2197 Data Analytics
Instructors
PD Dr. Ronald Hochreiter
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
11/07/16 to 11/21/16
Registration via LPIS
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
Dates
| Day | Date | Time | Room |
|---|---|---|---|
| Thursday | 11/24/16 | 02:00 PM - 05:30 PM | D2.0.038 |
| Tuesday | 11/29/16 | 02:00 PM - 05:30 PM | D4.0.133 |
| Thursday | 12/01/16 | 01:30 PM - 05:00 PM | TC.3.06 |
| Wednesday | 12/07/16 | 02:00 PM - 06:00 PM | EA.5.034 |
| Wednesday | 12/14/16 | 09:00 AM - 01:00 PM | D5.0.002 |
| Wednesday | 12/21/16 | 02:00 PM - 06:00 PM | EA.5.034 |
One core element of modern Data Science are computational methodologies from the field of Machine Learning as well as Statistical Learning. The main methods will be discussed to allow for handling Classification, Clustering as well as Association Analysis and Collaborative Filtering tasks. Real-life examples and data sets will be used. The statistical programming language R will be used to solve problems numerically.
Students are able to identify a data science problem and choose the appropriate technology to solve the problem. Furthermore, the students are able to implement the respective algorithms using the statistical programming language R by selecting useful extension packages. Upon completion of the course participants will be able to:
1. Analyze data science problems structurally and find the appropriate method to solve the respective problem.
2. Solve data science problems using R.
1. Analyze data science problems structurally and find the appropriate method to solve the respective problem.
2. Solve data science problems using R.
At the beginning theoretical foundations of Machine Learning technologies will be presented. Furthermore, an introduction to R for Data Science will be given. Over the course of the lecture student presentations will be a central part.
Successful conclusion of the course 1 of SBWL Data Science.
Please be aware that for all courses in this SBWL registration is only possibly for students who successfully have completed the entry course (Einstieg in die SBWL: Data Science).
Note that for courses within the SBWL "Data Science" we can only accept students enrolled in one of WU's bachelor programmes who qualify for starting an SBWL; particularly, we cannot accept students from other courses and programmes enrolled at WU as 'Mitbeleger' only.
Last edited: 2016-10-03
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