What is the next step?

Last updated on 2024-12-03 | Edit this page

Overview

Questions

  • “What do I do now?”
  • “What is the next step?”

Objectives

  • “Present suggestions for further reading,”
  • “Tips on problems to work on to practice,”

Where to learn more?

We have other courses in R - and other stuff.

In our calender, you will find all our activities, courses, seminars, datasprints etc.

There is an abundance of online courses in R, and a lot of other subjects.

Some of our favorites include:

A lot of online books also exists:

Where to find something to practice on?

You will only get proficient in R by practicing. If you already have your own data, and something you want to do with it, great! Go ahead.

But if you would like to find some data to play around with, here are some suggestions:

  • Kaggle is an online machinelearning competition site. Doing machinelearning might be a bit premature for you, but they provides acccess to a lot of interesting datasets.
  • The KUB Datalab website has a section on Open Data Sources.
  • Tidy Tuesday is an online event, where R enthusiasts every tuesday hack away on a common dataset. It’s a great way to both discover new and interesting datasets, and find inspiration for what to do with them.

If you want to dive into programming with R, rather than “just” data analysis, we recommend Project Euler, witch is a collection of numerical problems.

But what should I do with that data?

Sometimes the most challenging thing is actually getting an idea for doing something.

Fundamentals of Data Visualization by Claus O. Wilke is a great book about visualizing data. No code unfortunately.

The R Graph Gallery provides both inspiration for visualizations and also the code!

R Screencasts - what it says on the tin. Live data analysis, recorded.

Contact us!

The whole reason for the existence of KUB Datalab is to help and assist students (and teachers and researchers) working with data.

We do not guarantee that we will be able to solve your problems, but we will do our best to help you.

Our website

Our mail:

  • “Practice is important!”
  • “Working on data that YOU find interesting is a really good idea,”
  • “The amount of ressources online is immense.”
  • “KUB Datalab is there for your.”