Universität Wien

040212 UK Data Science Praxisbeispiele mit SAS (2022S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 09.03. 16:45 - 20:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 16.03. 16:45 - 20:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 23.03. 16:45 - 20:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 25.03. 11:30 - 14:45 Hörsaal 13 Oskar-Morgenstern-Platz 1 2.Stock
  • Wednesday 30.03. 16:45 - 20:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 06.04. 16:45 - 20:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 27.04. 16:45 - 20:00 Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock

Information

Aims, contents and method of the course

SAS software is used by many companies and organizations and SAS knowledge is also mentioned as a requirement in numerous job advertisements. This course gives an introduction to the programming language SAS and selected visual interfaces. Based on data science use cases, you will learn how SAS can be used for data preparation and data analysis.

The course consists of 2 main areas:
Learn the basics of SAS programming for statistical analysis and data management. Here we build on the ebook and the SAS course "SAS Programming for R Users" and work out the most important properties of SAS with small practical examples and hands-on tasks.
The application of statistical methods and data science for technical questions with the SAS system. Here we use selected (real) data sets and create analyzes and evaluations both in the SAS programming language and in a visual interface (NoCode/LowCode). With regard to the use cases, we choose from examples such as "New Product Forecasting", "Employee Retention Analysis", the water level analysis at Lake Neusiedl, or the simulation of the Monopoly or DKT board game.

We are also running a small hackathon where the goal is to build an accurate predictive model for customer behavior.
In the courses we mainly work with the user front end "SAS Studio" and learn how to use SAS to read in the data for analysis, how to process this data and evaluate it graphically and with descriptive statistics, and how to carry out complex data science analyses. The SAS modules SAS Base, SAS STAT, SAS Graph and SAS Visual Analytics are mainly used.
The course is held in blocks of 8 units.
The use of SAS Certified Young Professionals (SCYP) in the SAS Cloud is recommended for the course. Detailed information and tips for registration will be announced on Moodle.

Assessment and permitted materials

- Attendance in the 8 LV units
- Submission of programming examples (details will be discussed at the beginning of the course)
- Completion Quiz
Permitted resources: use of the SAS software, course materials, SAS online documentation, Internet research

Minimum requirements and assessment criteria

- At least 50% of the achievable points when submitting the programming examples
- At least 50% of the achievable points when completing the quiz
- Attendance in at least 6 course units

Examination topics

Will be discussed at the beginning of the course.

Reading list

- SAS Programming for R Users, Jordan Bakermann 2019, Download: https://support.sas.com/content/dam/SAS/support/en/books/free-books/sas-programming-for-r-users.pdf
- Courseware from SAS SAS Certified Young Professionals
- Gerhard Svolba: Applying Data Science - Business Case Studies Using SAS, SAS Press 2017 (http://support.sas.com/svolba )
- Gerhard Svolba: Data Preparation for Analytics Using SAS, SAS Press 2007
- Shreve J, Holland D: SAS Certification Prep Guide - Statistical Business Analysis Using SAS9, SAS press 2018
- Webinar on Data Science Case Studies and Data Preparation for Data Science on Youtube

Association in the course directory

Last modified: Th 28.04.2022 09:07