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A (very) basic introduction to programming with R

Instructor: Srdjan Sarikas
Teaching Assistant: Saren Tasciyan

Description

This course provides a very elementary introduction to programming using R, as one of the most widespread programming languages for data analysis in science, and maintained largely by the practicing researchers. The course will present the core basics in the following domains:

The course consists of 4 regular (obligatory) and one additional catch-up/Q&A session. The sessions will be a mix of lecturing and hands-on exercises, lasting for 3 hours with breaks when needed. More exercises will be expected to completed individually at home, and submitted before the next session, which will begin with explanations and comments on the homework.


Software

The in-session and home exercises will require all participants to have a computer with a working software. You are hence encouraged to download and install R and RStudio before the first session. CRAN website provides the latest R distribution for OSX, Linux and Windows. RStudio offers the appropriate installers on their website.

A brief preparatory meeting will be held in the later afternoon of Tuesday, September 20th, for participants who would like support with the installation of the software or have any preliminary/general questions regarding the programming courses (attendance optional). Details on the time and place will be communicated in due time.


Requirements/Exams

As the name suggests, the course is explicitly targeted towards students with little or no prior programming experiences. Therefore, there are no prerequisites for taking this course.

If you do have previous programming experience, you may not be eligible for ECTS credit, but are of course welcome to attend as an auditor to learn the syntax of R. For example, if you already know how to use the for, if/else, and while statements you are likely too advanced for the course. In case of doubt, discuss your situation with the instructor.


Credits

Upon successful completion of the course students will be granted 1 ETCS credit.


Final Grade

Final grade (fail/pass) will based on completion of homework exercises.

Schedule (subject to change)

Date Time Topic Location Notes
Sep 20, Tue 15:30-16:00 Installation of R and RStudio Mondi 3 Preliminary session (attendance optional)
Sep 21, Wed 9:00-12:00 Session 1 Mondi 2 Variables, expressions, vectors, Conditioning
Sep 23, Fri 9:00-12:00 Session 2 Mondi 2 Matrices, packages
Sep 26, Mon 9:00-12:00 Session 3 Mondi 2 For-loop, lists
Sep 28, Wed 9:00-12:00 Session 4 Mondi 2 Data frames
Sep 30, Fri 9:00-12:00 Session 5 Mondi 2 Custom functions, I/O

Homework

File Due Date Solutions
Homework 1 Sep 22, 18:00  
Homework 2 Sep 25, 18:00  
Homework 3 Sep 27, 18:00 Homework 3 Solutions
Homework 4 Sep 29, 18:00 Homework 4 Solutions
Homework 5 optional  

Additional Downloads

Training Datasets

antibio_res

luminescence.csv

 

luminescence.xls

luminescence.xlsx

luminescence_2.xlsx



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