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Data science: R basics coding

20 hour(s)

2 x 2 hours per week or duration to agree with the learners

Objectives

In this course of R-basic coding, you will learn the basic building blocks of R.You will learn to use general programming features like "if-else", and "for loop" commands to write your own functions to perform various operations on datasets.

In practical, you will learn:

  • how to read, extract, and create datasets in R
  • how to perform a variety of operations and analyses on datasets using R
  • how to write your own functions/sub-routines in R

Content

Section 1: R Basics, Functions, and Data Types

You will get started with R and learn about R's functions and data types.

Section 2: Vectors and Sorting

You will learn to operate on vectors and advanced functions such as sorting.

Section 3: Indexing, Data Manipulation, and Plots

You will learn to wrangle, analyze and visualize data.

Section 4: Programming Basics

Target group

Who is the course aimed at?

  • Students and Recent Graduates
  • Early- and Mid-Career Professionals
  • Marketing and Project Management Professionals

 
Prerequisites

R studio software is recommended but not mandatory to enable programming directly in a software-based interface.

Assessment

Certficate, diploma

In order to earn a Certificate of Completion, participants must thoughtfully complete all 4 modules.

Additional information

About the Professor

Dr Hichem Omrani (Research Scientist, full ADR / Habilitation-HDR)
Dr. Hichem Omrani is currently a research scientist (R3) at the Luxembourg Institute of Socio-Economic Research (LISER). his research group is hosted at the Urban development and Mobility department. He received his Ph.D. in Computer Science in 2007, from the Technology University of Compiegne (UTC-France). Dr. Omrani is also an Adjunct Associate Professor at the University of Concordia (Canada). He conducts research in the framework of several competitive projects supported mainly by the FNR. His research focuses on data science, applied statistics, machine learning, complex system modelling applied in a wide range of applications (environment, mobility, policy evaluation, and individual exposure to the environments, and public heath). He supervised several master/PhD students, young researchers and act as a reviewer for several international journals. During his lastest scientific leave (2016-2017), he served as Senior Visiting Researcher at Purdue University (USA), working jointly with Dr. Bryan Pijanowski, an internationally recognized specialist in the field of environmental science and soundscape. Dr. Omrani is (co-) author of 45+ scientific articles on peer-reviewed international journals, 100+ papers in conferences proceedings, and 2 book chapters in volumes with ISBN. His publications have been cited, so far, 1500 times (source: Google scholar). My Google scholar H-index is 17 (i10-index: 26). To date, he has attracted around €4.25m in grants mainly from the EU, FNR and industry.

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Responsibility for the content of this training description lies solely with its author, the training provider Centre Avicenne Luxembourg.

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