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Practice mode arrives on mobile!

Today, we’re bringing DataCamp’s practice mode to mobile.
May 2018  · 3 min read

Make your breaks and commutes even more productive by solving practice exercises for the courses you’ve taken on desktop or mobile. We’re launching with practice mode for 9 courses, and we’ll be adding exercises for many more in the coming weeks! Download the app for iOS and Android.

Practice mode

Now that the mobile app has four courses in the app (Intro to R, Python, SQL and Intermediate Python) and one in development (Introduction to Tidyverse), we thought it was time to allow learners of these and the other (desktop) courses to practice.

As on desktop, practice mode for Mobile presents you with a series of random exercises on the course-topics you want to practice. For each course that has practice available (see the full list below), we’ve developed tons of new exercises that cover the course content from a different perspective, helping you learn the subject matter at a deeper level. Doing practice on mobile has one big advantage: you can practice anytime, anywhere, even when you’re offline!

“the mobile version has one big advantage: you can practice anytime, anywhere, even when you’re offline!”

Today’s release is another step towards our end goal of building a ‘personal trainer’. This trainer tracks how well you understand each of the concepts you’ve learned about, and figures out which exercises to give you based on that. In the near future, you can expect a steady increase of the practice library size, to ultimately have practice for each of the 100+ DataCamp courses. Meanwhile, we’re focussing on increasing the quality of the exercises and improving the user experience of the app. Attentive practicers might also notice some initial experiments with exercise personalization :)

Here is a list of all courses with a mobile practice mode:

  • Introduction to R
  • Introduction to Python
  • Intermediate R
  • Intermediate Python
  • Data Manipulation in R with dplyr
  • Joining Data in R with dplyr
  • Cleaning Data in R
  • Cleaning Data in Python
  • Data Types for Data Science
  • [SOON] Cleaning Data in Python
  • [SOON] Intro to SQL for Data Science
  • [SOON] Python Data Science Toolbox (Part 1)
  • [SOON] Python Data Science Toolbox (Part 2)
  • [SOON] Writing Functions in R
  • [SOON] Pandas Foundations
  • [SOON] Manipulating DataFrames with pandas
  • [SOON] Merging DataFrames with pandas
  • [SOON] Exploratory Data Analysis in R: Case Study

Many more to come in the next months!

Happy practicing!

(Would you like to help out building this future? Join our team! We’re looking for content developers, software engineers, and many other roles:

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