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Big Data ManageR
Provider: Faculty of Health and Medical Sciences

Activity no.: 3331-18-00-00 
Enrollment deadline: 10/04/2018
Date and time15.05.2018, at: 10:00 - 18.05.2018, at: 17:00
Regular seats50
Course fee2,280.00 kr.
LecturersThomas Gerds
ECTS credits2.80
Contact personSusanne Kragskov Laupstad    E-mail address: skl@sund.ku.dk
Enrolment Handling/Course OrganiserPhD administration     E-mail address: phdkursus@sund.ku.dk

Aim and content
This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not enroled as a PhD student at the Graduate School, you will be placed on the waiting list until enrolment deadline. After the enrolment deadline, available seats will be allocated to applicants on the waiting list.

The course is free of charge for PhD students at Danish universities (except Copenhagen Business School). All other participants must pay the course fee

Learning objectives
A student who has met the objectives of the course will be able to:

1. have insight into statistical methods for big data
2. use multiple cores for parallelized computing
3. setup a project in R studio and organize a reproducible analysis
4. organize and merge data from multiple sources using data.table
5. visualize data using ggplot2

Content

The course has the following two objectives and each of the four course days will accordingly be divided into 3 hour lectures by an invited lecturer and 3 hour practicals using R.

1. International experts are giving lectures about recent developments in statistical
methods for big data analysis.
- the actual topics covered will be selected from the active research of the invited lecturers
and will deal with big data including omics and data from Danish registers.
- the lecturers are ask to discuss how these methods can be implemented, preferably using R.

2. Participants learn data management with R ...
- A general theme is working with data from different sources.
- How to move a messy and narrow 1-room project to a functional multiroom laboratory.
- Certain rules of behaviour towards reproducible research results.
- Parallel computing
- data.table
- ggplot2


Participants

Participants should have basic knowledge of the statistical software R.

Relevance to graduate programmes
The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:

All graduate programmes

Language
English

Form
Lectures on statistical methods for big data analysis and computer exercises using the statistical software R.

Course director
Thomas Alexander Gerds, Prof. Dr., Section of Biostatistics Department of Public Health University of Copenhagen, tag@biostat.ku.dk

Teachers
Benoit Liquet, University of Pau and Pays de l'Adour, France
Klaus K. Holst, Mærsk, Denmark
Marc Chadeau-Hyam, Faculty of Medicine, School of Public Health, Imperial College London
Christian Torp-Pedersen,Unit of Epidemiology and Biostatistics, Aalborg University Hospital, Aalborg, Denmark
Helene C Rytgaard, Section of Biostatistics, Copenhagen University, Denmark
Thomas A. Gerds, Section of Biostatistics, Copenhagen University, Denmark

Dates
Tuesday 15, 16, 17 and 18 May 2018

Course location
CSS, University of Copenhagen

Registration
Please register before 10 April 2018

Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.
Applications from other participants will be considered after the last day of enrolment.

Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor

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