R Course for VTT Technical Research Center of Finland

Dear data-savvy colleagues, you have landed on the homepage of R programming language course, given by me (Ouz). Everything you will need for this course will appear (somewhat on-the-go) under this repository. This course is aimed for anyone who has anything to do with any kind of data. It is composed of online, real-time lectures & some exercises for post-lecture fun (exercises are optional, fun is definitely optional). Lectures will be hands-on and practical (still accompanied by short lecture notes).

I will try to adjust the implementation (content, pace, requirements etc.) according to your needs and will try to add some homour and games whenever possible. Please feel free to contact me anytime for questions, comments and/or feedback.

Contents of the Course

Basics of R & RStudio ✔️
- What exactly is R?
- What about this RStudio thingy?
- When to use / avoid R?
- Basic data types, functions
- Reading & writing data
- Debugging
Data frames ✔️
- Data frame paradigm and why it is cool
Data munging & wrangling ✔️
- melt, reshape, cast, aggregate etc.
- plyr & dplyr packages
- applys
Reading and writing data ✔️
Visualization & plotting ✔️
- base
- lattice
- ggplot2
Statistics for researchers ✔️
- Answering the question: Conference deadline is in 1 week, so which one of this is the p-value?
- Useful statistical tests
Markdown & reporting ✔️
- Reproducible research
- knitr
- Interactive plots
What to do with missing data? ✔️
Signal processing ✔️
- Filter design
- Frequency domain analysis
Machine learning ✔️
- Some cool stuff
- More cool stuff
Profiling your code ✔️
- Answering the question: I already had lunch and 2 coffee breaks, when will I get my results?
- Tips for speeding up the code
Interacting with other languages and environments (tentative)
- python, SQL, MATLAB, LATEX, mongodb etc.
Applications (some of the below, suggestions are welcome) ✔️
- Text mining
- Mining PubMed
- Mining Wikipedia hits
- Time series forecasting
- Network analysis
- Survival analysis
- Anomaly/outlier detection
Parallel processing ✔️
- Running your code on multiple cores
Shiny app (tentative)

Schedule

All lectures are at 14:00 - 16:00 (EEST). A link for attending the lectures will be provided to each one of you via email.

Lecture	Date
Lecture 1	Wednesday 27.04.2016	✔️
Lecture 2	Tuesday 03.05.2016	✔️
Lecture 3	Wednesday 04.05.2016	✔️
Lecture 4	Wednesday 11.05.2016	✔️

Getting Ready

For this course, we will be needing R (the actual programming language) and RStudio (the IDE for R as we don't want to kill ourselves while getting things done in R).

Go to R homepage and click the download R link.
Choose a mirror (doesn't really matter) and afterwards your operating system.
- If you are on Windows, click on "Install R for the first time" and "Download R 3.2.x for Windows" (x is 5 as of 25.04.2016).
- If you are on Mac, click on the file containing the latest version of R under Files (R-3.2.4.pkg as of 25.04.2016).
Follow the regular installation steps (if asked choose 64 bit R).

Go to RStudio download page
Under Installers for Supported Platforms choose your own OS. (RStudio 0.99.896 as of 25.04.2016)
Follow the regular installation steps

Required packages/libraries for the course are listed in required_packages.txt

Lectures

Exercises

There will be exercises related to the lectures almost as if you are not spending enough time in front of your computer day and night. These exercises are not mandatory at all. I will try to to gamify these as much as possible and hopefully provide some options to choose from as well. All exercises have the same deadline: 31.05.2016

To-do

This part is basically for myself.

License

MIT license.

Contact

Oguzhan (Ouz) Gencoglu, oguzhan.gencoglu@tut.fi

ogencoglu/R_for_VTT