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

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.




Celebrating our 100th R exercise set

Yesterday we published our 100th set of exercises on R-exercises. Kudos and many thanks to Avi, Maria Elisa, Euthymios, Francisco, Imtiaz, John, Karolis, Mary Anne, Matteo, Miodrag, Paritosh, Sammy, Siva, Vasileios, and Walter for contributing so much great material to practice R programming! Even more thanks to Onno, who is working (largely) behind the scenes to get everything working smoothly.

I thought perhaps this would be a good time to share some thoughts on the ideas behind the site, and how to proceed from this point onward. The main idea is pretty simple: it helps to practice if you want to learn R programming.

The two problems we’re trying to solve

Although the idea itself is simple, for many people, and perhaps you as well, following up on this idea is a challenge. For example, practicing R programming requires a certain task that has to be completed, a solution to an analytical problem that has to be found, or broader goal definition. Without this, we would just be typing random R syntax, or copy-paste code we found somewhere on the web, which will contribute little to improving our R skills. The main problem R-exercises is trying to solve is how to specify these tasks, problems and goals in a useful, creative and structured way. The exercise sets are our (current) solution to this problem.

But there’s a second challenge for those who want to practice: Staying focused. Live throws many distractions at us and while you perhaps found some interesting problems to practice your R skills, sooner or later practicing fades away when more urgent matters pop up. So, the second problem R-exercises is trying to solve is how to practice in a focused, persistent way. Offering new exercises on a daily basis, rather than one-time communication (e.g. a book or course) is our solution to this second problem.

Filling a gap in existing solutions

Is there a need for a site filled with exercises? There is an enormous amount of educational material on R available already. Our Course Finder directory includes 140 R courses, offered on 17 different platforms. Many universities teach R as part of their methods/statistics course programs. There are plenty of books on R. A search for “tutorial” on blog aggregator R-bloggers, reveals 1783 articles. And then there’s Youtube. It seems, with so much material, gaps are unlikely. But are they?

Going back to the two challenges we just described, we think what we’re offering is complementary to courses, books, classes and tutorials. Because the focus of most courses, books, classes and tutorials is on explaining/demonstrating things instead of practicing (the first challenge). And their focus is temporary, not necessarily persistent (the second challenge). It’s gone after you completed the course, read the book or watched the video tutorial.

In their excellent book “Make it stick”, Roediger and McDaniel explain that many of our intuitive approaches to learning (e.g. rereading a text) are unproductive. Instead they advise: “One of the best habits a learner can instill in herself is regular self-quizzing to recalibrate her understanding of what she does and does not know.” From this perspective, R-exercises can help you to recalibrate your understanding of what you know and don’t know about R.

The next 100 sets

We’re committed to keep expanding R-exercises, and adding more exercise sets. A while ago we started to differentiate sets in terms of difficulty (beginner, intermediate and advanced), an idea that many readers seemed to like when we proposed it. Recently we started to include information about online courses directly related to the exercises in a set, so for those who want to learn more, it’s easy to find a relevant course quickly.

Another idea we have is to offer premium (paid) memberships, with access to more extensive learning materials related to each exercise set. We’d actually love to hear your suggestions on how we can improve and expand R-exercises. What would you like to see on the site in 2017?




R Course Finder December update!

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 22 courses to the Course Finder. Currently we are at 140 courses on 14 different online platforms, and 2 offline Learning Institutes.

This month we added two new platforms:

Other then adding these platforms we also kept expanding the content on platforms already available in the Course Finder. There were some new courses added this month we we’re excited about and wanted to highlight:

Highlighted Courses

Foundation of Strategic Business Analytics
This course offered by Coursera is part of the ‘Strategic Business Analytics’ specialization. Business analytics is one of the hottest places to work in these days and this course, together with the entire specialization, lays out in great detail the skills you need to enter this field. It also raises the question when we are going to merge business analytics and Data Science into one, Data analytics anyone?

Regression Machine Learning with R
This is an Udemy course that seems to me (and I’ve been working on this database for a while), is one of the most complete courses on Machine Learning so far available. It also has a good pace that connects to those of us who have a solid statistical background and know how to work with R, but want to focus on this concept in more detail.

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.




New Expansion of the R Course Finder!

eye-15699__180

On the 1st of september 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.

Over the past month we have further expanded the courses available in the Course Finder. Currently we are at 118 courses on 12 different platforms, and 2 offline Learning Institutes.

We expanded the Course Finder across nearly all the platforms! Also there were some courses we we’re excited about and wanted to highlight:

Highlighted Courses

  • Advanced R Programming

  • This course offered by Coursera is part of the ‘Mastering Software Development in R Specialization’. When indexing it and reading thru the syllabus it got me excited to follow the complete specialization. We also added the other courses which include one on package building!

  • Statistics with R – Advanced Level

  • This is an udemy course that still starts of somewhat easy with ANOVA and other mean comparison techniques, but the expert level is reflected in the quick pace and fast steps to more advanced material. Furthermore you can also find the beginner level in the Course Finder here

But we want to keep going! If you miss a course or know of a different platform we want to know, so we can keep adding to the most complete directory of R courses available online.

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.




The R-Studio Founder, Debate Language and Who is the most Active Data Scientist?

R news To stay on top of R in the news, we’re sharing some stories related to R published last week.

A great interview with JJ Allaire, creator of RStudio.(Joseph Rickert)

The man who build RStudio now 13 years ago shares some insight on the company and his own motivation. Or was it a company? we are still not sure JJ!

The language of the second presidential debate(Edward Lee)

I do love some text analysis, but Trump is all about that money… When will data scientists start coaching presidential candidates to look good on post-debate word clouds?

The most Active Data-Scientists online (Manish Saraswat)

Hadley Wickham standing proud! But it does look like the R-community can take steps in their online visibility.

Alright that was it for this week, we will keep uploading sets this week and come back with another update as scheduled. To stay on top of the news during the week, visit our R News section.




Big Salaries, Recommendation Systems, and Where We’ll Be 5 Years from Now

R newsTo stay on top of R in the news, we’re sharing some stories related to R published last week.

Why Data Science ‘Rock Stars’ Earn Big Salaries (Dennis McCafferty)

Recent post and slide deck related to the 2016 Data Science Salary Survey (O’Reilly Media), with R mentioned as one of the high-demand programming languages (next to SQL and Python). “Today’s data scientists in the United States are typically members of the six-figure salary club”. Are you a member as well?

Prediction in the Age of Big Data: The Science Behind Recommendation Systems (Devavrat Shah)

Interesting article by MIT professor Devavrat Shah answering the question “How can data scientists extract meaningful insights and accurately predict customers’ preferences in the age of big data?”. Mentions the RecommenderLab R package.

Microsoft and the ubiquity of data intelligence (Andrew Brust)

Short overview of improved R integration in Microsoft Power BI and SQL Server 2016. “with SQL Server R Services, Microsoft has been able to get SQL Server to support the generation of 100 million predictions per second.”

Where Will Data Science Be in Five Years (Anthony Goldbloom / Huffington Post / Quora)

Some thoughts by Kaggle’s co-founder and CEO Anthony Goldbloom on the recent past and (near) future of Data Science. Interesting estimates (1.5-3 million) on the number of data scientists (by his definition “somebody using R or Python”) in the world. Compared to 20 million software engineers. BUT: he believes “data science will be bigger than software engineering in the next decade.” Do you agree?

How do R and Python complement each other in data science? (CrossValidated)

Oh no… Python vs R, not again! But wait: This lively CrossValidated discussion seeks common ground and focuses on the complementarity of both languages. Are you actually using Python as a complement to R?




How can we improve R-exercises?

light-bulb-1002783_960_720Hey there! We’ve been sharing R exercise sets for about a year, and think this is a good moment to reflect and ask for your feedback. So here is your opportunity to have a say in where we take R-exercises next! We’d like to hone in a bit on the degree of difficulty of the exercises, because we’re thinking one size might not fit all of you.

Rather than the current one-size-fits-all approach we’re considering to create exercise sets aimed at specifically beginners, intermediate users and people who’ve been using R for years.

As an example, Dr Kumal said in the comments of examining data exercises that he thought the beginner level of the exercises did not reflect the usual level that visitors are looking for on this website. What do you think? Is there a specific level we should aim for or should we diversify and create beginnner, intermediate and advanced level sets for every topic we have on the site?

In addition to your ideas on this specific issue, we’d also be interested to receive general feedback on the content, format and direction R-exercises is taking. Would you like to see other things than just exercises, such as quizzes, tutorials, news items etc. Which packages/topics should we focus on? Do you have any problems with navigating the site?

Please share with us your ideas in the comments below

Again, this is your chance to have a say in what you’d like to see on R-exercises in the coming months. I promise to read all your feedback rather than feeding it into an R text mining script. And if you have so much feedback that it does not fit in the comment section below, I also encourage you to email me directly at onno@researchfordecisions.com.




R Course Finder update

eye-15699__180A month 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.

With your help and input we have improved it over the past month. As of today it consists of 93 courses on 12 different platforms on the web, and 1 offline learning institute.

This month we added courses from:

  • Pluralsight
  • NYC Data Science Academy

The NYC Data Science Academy is our first addition of an offline course. If this is something you are interested in and want to see more of, please let us know!

The R Course Finder allows to filter courses based on these filters:

8 Filters

The R Course Finder allows to filter courses based on these filters:

  • Level
  • Content
  • Duration
  • Price
  • Learning tools
  • Institute
  • Platform
  • Online/offline

Clever search box

Perhaps even better is a clever search box, which shows results immediately while you type. Just give it a try!

search

 

But we want to keep going! If you miss a course or know of a different platform we want to know, so we can keep adding to the most complete directory of R courses available online.

How you can help to make R Course Finder better

  • 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.
  • If you miss a course that is not included yet, please post a reminder in the comments and we’ll add it.

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

 




Announcing R Course Finder

eye-15699__180Did you ever feel knowing exactly what you wanted, but couldn’t find it in a mountain of information?
We know how you feel… As the mountain of R courses and tutorials continues to get bigger, we need smart tools to quickly find those that meet our needs best.

So, we built the R Course Finder (link).

It contains as of today 86 online courses from 11 different platforms around the web.

r course finder

7 Filters

Moreover, you can search and use any combination of 7 filters to find exactly what you are looking for:

  • Level
  • Content
  • Duration
  • Price
  • Learning tools
  • Institute
  • Platform

Do you want to search through free courses only?
Do you want to find courses on specific topics, such as machine learning?
Are you looking for that course that focuses on Case Studies?
Perhaps you want to learn about a different tutorial platform you didn’t know exist?

Clever search box

Perhaps even better is a clever search box, which shows results immediately while you type. Just give it a try!

search

How you can help to make R Course Finder better

Although 86 courses is quite a bit, we think we can make R Course Finder even better with your help:

  • 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.
  • If you miss a course that is not included yet, please post a reminder in the comments and we’ll add it.

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

 




Start here to learn R!

start here to learn R

Ready, set, go!

On R-exercises, you will find hundreds of exercises that will help you to learn R. We’ve bundled them into exercise sets, where each set covers a specific concept or function. An exercise set typically contains about 10 exercises, progressing from easy to somewhat more difficult. In order to give you a full picture of all the amazing content on this website, we’ve categorized all sets into broader topics below.

If you’re completely new to R, we suggest you simply start with the first topic, “Vectors”. Once you’ve managed to work through all exercise sets, from top to bottom, you should have a fair amount of knowledge of, and practical experience with, using R. Of course, those of you who are familiar with R already, can jump straight to any of the topics below.

New exercise sets are added on a daily basis. Subscribe to R-exercises to receive daily updates by email.

Note: For future updates to the overview below, please have a look here.

Have fun!

Exercise sets by Topic

Vectors

  1. Vectors
  2. Regular sequences
  3. Logical vectors and operators
  4. Missing Values
  5. Character vector exercises
  6. Index vectors

Object modes and attributes

  1. Mode exercises

Factors

  1. Factor Exercises

Arrays and matrices

  1. Matrix exercises
  2. Array exercises
  3. Bind exercises

Lists and dataframes

  1. List exercises
  2. Data frame exercises
  3. Merging Dataframes Exercises
  4. Accessing Dataframe Objects Exercises

Importing data

  1. Reading delimited data
  2. Scan exercises

Tables

  1. data exploration with table
  2. Complex Tables – Exercises
  3. Cross Tabulation with Xtabs exercises

Data manipulation

  1. Get-your-stuff-in-order-exercises
  2. Summary Statistics With Aggregate()
  3. Data Shape Transformation With Reshape()

Dates/times

  1. As.Date() Exercises

Probability distributions

  1. Lets Begin with something sample

Loops and conditional execution

  1. Conditional execution exercises
  2. Scripting Loops in R

Functions

  1. Functions exercises

Data visualization

  1. Start plotting data!
  2. Customize a scatterplot exercises
  3. Graphics parameters exercises
  4. 3D plotting exercises

Contributed packages

  1. Data Table – Data table exercises: keys and subsetting
  2. Lattice – Lattice exercises – part 1
  3. Lattice – Lattice exercises – part 2
  4. Zoo – zoo time series exercises