R – A non-technical introduction to big data techniques, team work and interactive visualization

(spring semester, lecture, block course)

„Much of what characterizes good research is the ability to anticipate, and neutralize with data, potential criticisms of conclusions.”

N. Cliff


Abstract:
Data-driven decision making gets increasingly important in today’s fast-paced business environment. Three aspects are key to succeed in data-driven decision making: handling “big data”, team collaboration and (interactive) visualization.

In detail, this class will show you in an easy and non-technical way how to deal with questions such as:  How to speed up your code? How to use Cloud Computing technology to crunch your data? How to automatically analyze data and summarize the results in an interactive report? What is the best tool to work in teams on code?

This class will apply a non-technical approach by starting every unit with “real-world” problem and providing you solution strategies to tackles those problems. The class is a lecture with integrated exercises. For every session, you are required to bring your laptop with the latest R version installed. No statistical models (besides mean and standard deviation) will be discussed in this class. The skills learned in this class are not only useful for a job in the data science industry but also for your master thesis.

Instructors:
Dr. Markus Meierer
Patrick Bachmann

Type:
Block Course

Target audience:
Master students, assigned to “Wahlpflichtbereich BWL 4”.

Frequency:
Each spring semester.

APS/ECTS-points:
3

Work load statement:

Part Workload Total Time
Course attendance 5 sessions à 7h, 1 week 35h
Course preparation 25h 25h
Online exercises 30h 30h
Total   90h

Maximum number of students:
-

Content:

  • big data techniques in R
  • interactive visualization in R
  • team collaboration with R

Language:
English

Resources:

- Crawley, M. J. (2015). The R Book. Chichester, Wiley
- The lecture will be complemented by online exercises on the e-learning platform provided by datacamp.com.
- Further details are available on the OLAT course platform.

Datacamp logo

Prerequisites:
Bring a laptop with R & RStudio installed (latest version).
Solid R programming skills. The required skills are on par with the contents of e.g. the following online classes: coursera and datamind as well as codeschool.

Access:
Join our courses and make up your mind if you want to participate. Then officially register using the “Buchungstool” at the University of Zurich.

Grading:
Individual evaluation based on contribution in class, multiple-choice tests (every days, starting Tuesday) and exercises.

Dates: Block course, 03-07 February, 2020, 9:00 - 17:00h

Location: AND-3-02/06  andSee https://www.vorlesungen.unizh.ch

Registration:
Don’t forget to officially register yourself using the registration tools at the University of Zurich.

Note:
The information in the syllabus supports the official information in the electronic university calendar (VVZ – Vorlesungsverzeichnis). In case of doubt, the official information at the VVZ is valid.