Automatically grading data science and big data courses online in CodeGrade
Guides
June 7, 2021

Webinar: How to automatically grade Data Science Assignments in R and Python

Autograding large Data Science assignments has become way quicker and effective with the release of our latest feature: AutoTest Caching. To celebrate that, CodeGrade's founder and Product Expert Devin Hillenius explains how to set up a basic automatically graded Data Science assignment (in both R and Python) in CodeGrade in our latest webinar (recorded on June 4th 2021 and available on demand now).

Data Science autograding in CodeGrade

Data Science is one of the most popular disciplines at this moment, data science courses are especially popular amongst non Computer Science students. These courses teach basic Python, R and other useful skills for this increasingly data-driven world. As this is often the first coding experience for these students, having instant automatic feedback helps motivate them throughout the beginning of the course and accelerate their first steps of coding.

Furthermore, it is very important to provide many exercises to these beginning students, an autograder like CodeGrade gives you the tools to provide many exercises to your students without extra grading work. Also, the subtasks of these assignments can be conveniently graded by separate tests and rubric categories in CodeGrade, motivating the students by making their progress visible and insightful.

Some of the tools CodeGrade offers for effective data science autograding are:

  • Use hidden data sets and test cases for your students to validate their code and make sure they did not "pattern match" the answers of the open tests. This way, you assess the actual inner workings of their code. Hidden tests are automatically run after the deadline and are explained by Devin in the webinar or in this guide.
  • Upload or download your required data sets easily to AutoTest. Data sets can be uploaded as fixtures or downloaded.
  • AutoTest caching is turned on by default, and will make sure that even for your Data Science assignments with large configurations (e.g. large data sets or installing of new packages or software) will give your students feedback instantly. Find out about all ins- and outs of this new feature in the webinar or in this guide.
Start autograding all your data science assignments now with CodeGrade's powerful autograder!

Python and Jupyter Notebook Data Science assignments

In this webinar we go over how to set up a Data Science assignment using Python or Jupyter Notebooks. For most of these assignments, you will need to install additional packages like Pandas, Tensorflow or Matplotlib. These can be very easily installed in the Global Setup Script by following this guide.

Want to learn more about Python or Jupyter Notebook autograding? Have a look at our previous webinar in which we deep dive into everything you need to know to do just that!

R Data Science assignments

Finally, we discuss how you can best set up your R Data Science assignments in CodeGrade. Luckily, R is one of the many languages that work right out of the box. All you need to do is install the required additional R libraries (or let your students do that themselves). Installing software using both of these methods is explained in this webinar and our previous guide. Everything you need to know about R autograding can also be found in our previous guide which you can read here.

With this webinar and our newest update, we are helping you set up the best possible Data Science autograded assignments. The lessons in this webinar are basic, but should be a great starting point for any R, Python or Jupyter Notebook data science assignment. Would you like to learn more about data science in CodeGrade? Or would you like some more help with your AutoTests? Feel free to email me at support@codegrade.com and I'd be more than happy to help you out!

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