Data Analytics (Modular Course)

Course description:

The statistical software R has come into prominence due to its flexibility as an efficient language that builds a bridge between software development and data analysis. For example, one strength of R is the facility to develop and quickly adapt to the different needs coming from the data management and analysis community while at the same time making use of other languages in order to deliver computationally efficient solutions. This course consists of two workshops that can be completed separately or in succession.


This course is a modular Course:

Module 1

Date For Module 1 : From June 22th 2020 to July 3rd 2020

Module 2

Date For Module 2 : From July 6th 2020 to July 10th 2020

Module 3

Date For Module 3 : From July 13th 2020 to July 18th 2020


Tuition Fees:

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Tuition for UNIGE students:

No more places available for UNIGE students.


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*Including 100 CHF non refundable administrative fees


Faculty & Staff:

Program Directors:

  • Prof. Maria-Pia Victoria-Feser, GSEM, University of Geneva
  • Prof. Stephane Guerrier, GSEM, University of Geneva

Instructors:

Prof. Matthew Beckman:

Assistant Research Professor at the Department of Statistics, Penn State University, as well as the Director of Undergraduate Studies. He earned a PhD in Statistics Education from the University of Minnesota where he previously earned his MS in Statistics. Prior to academia, he worked as a Senior Statistician & Senior Biostatistician in the medical device industry for 8 years. His current research interests include statistics education, educational assessment, and industrial statistics.

Prof. Si Konda

Is an assistant professor in Biostatistics at University of Illinois at Chicago (UIC). He has considerable experience in developing and teaching statistical and machine learning courses. He provided multiple two day analytics and machine learning seminars for Society of Actuaries from 2016-2019 and conducted one-day machine learning workshop at Abbott Labs, Chicago, USA in 2019. He is the recent golden apple award winner for excellence in teaching & leadership at UIC. Si Konda was a visiting faculty at University of Waterloo in 2012 and University of California at Santa Barbara from 2013 to 2015. Si Konda has a Ph.D. in Statistics from the Case Western Reserve University in Cleveland, USA.

Prof. Roberto Molinari:

Obtained a Master degree in International Affairs at the LUISS Guido Carli University in Rome, which brought to experiences in the UNECE, ECD and Ernst & Young. He then obtained a PhD in Statistics (University of Geneva) to become Visiting Professor in statistics at the University of California, Santa Barbara (USA) where he taught introductory Statistics and supervised projects in actuarial sciences. After a year as a consultant for international organizations in West Africa, he returned to academia as Lindsay Assistant Professor at Penn State University (USA) where he continues his research and develops courses in non-parametric statistics and time series analysis. His research interests are in robust estimation for time series models, spatial statistics and model selection as well as applied statistics in the fields of economics, finance and medicine.

Olga, Switzerland, R-programming for Data Science Summer School 2019

"Having a management background, I didn’t have any previous knowledge of programming and the Summer School in R-Programming for Data Science at the Université de Genève represented an enriching experience.

The professor was able to introduce the class very well to this statistical software and at the end of the week, with the precious help of the teaching assistants, I was able to solve some real-life problems, coming from the field of statistics and financeThe interdisciplinarity was actually one of the main strengths of the course, showing how R can be tailored to different usages. For me, the presentation of RMarkdown was extremely useful, allowing to create and use data in an easy and quick way, and I have appreciated a lot the introduction to Shiny Web Applications.

In addition, the background of the class was extremely varied, from business analytics to biology, and this represented another remarkable aspect, along with the international environment of both the city and the university. Taking part in it required for sure an academic effort but it was absolutely worth it and gave me the willingness to deepen what I learnt!"