January Update R Course Finder: Shiny, Quantitative Trading, and Much More

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eye-15699__180A few months ago we launched R Course Finder, an online directory that helps you to find the right R course quickly. With so many R courses available online, we thought it was a good idea to offer a tool that helps people to compare these courses, before they decide where to spend their valuable time and (sometimes) money.

If you haven’t looked at it yet, go to the R Course Finder now by clicking here.

Last month we added 9 courses to the Course Finder. Currently we are at 149 courses on 14 different online platforms, and 2 offline Learning Institutes.

Highlighted Courses


R Shiny Interactive Web Apps – Next Level Data Visualization

Are you a business analyst, data scientist, entrepeneur, or student, looking for modern data visualization tools? Then you have to check out the Shiny package! This is the first course in our directory that teaches how to create Shiny apps. It starts with creating the basic structure of a Shiny app, adding interactive input controls and widgets, and styling. After this, you’ll learn more advanced functionality, such as embedding videos, tables, and multi-page apps. Finally, it offers a real-world project, where you’ll build a financial app.

Quantitative Trading Analysis with R

Finance professionals, DIY investors and students who want to learn about quantitative trading analysis, should check out Quantitative Trading Analysis with R. In 53 lectures (7 hrs) you learn how to use R to analyse mean-reversion and trend-following trading strategies, calculate risk management and trading statistics such as the Kelly criterion, simulate historical returns, and use walk-forward testing (cross-validation) to avoid over-optimization.

Reproducible Research

This is a 4-week course, part of Coursera’s Data Science Specialization, where you’ll learn about concepts and tools behind reporting modern data analyses in a reproducible manner (including Markdown and knitr).

Besides these courses, we also added these other 6 courses:

R Machine Learning solutions
R for Data Science Solutions
Mastering R Programming
Building R Packages
The Data Scientist’s Toolbox
Statistical Inference

How you can help to make R Course Finder better

  • If you miss a course that is not included yet, please post a reminder in the comments and we’ll add it.
  • If you miss an important filter or search functionality, please let us know in the comments below.
  • If you already took one of the courses, please let all of us know about your experiences in the review section, an example is available here.

And, last but not least: If you like R Course Finder, please share this announcement with friends and colleagues using the buttons below.

To leave a comment for the author, please follow the link and comment on their blog: R-exercises.

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