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Creating a Data Science Question

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Overview

HackerRank Projects for Data Science allows you to create project-based real-world questions to assess Data Scientists. It helps better identify candidates with strong data science skills and comes with a host of options, from using our predefined Data Science assessments that assess candidate skills in Data wrangling, Data modeling, Data visualization, and Machine learning to creating your own Data Science questions. 

Read our blog to learn more about 'HackerRank Projects for Data Science'. 

This article will dive into how you can create your own Data Science Question on HackerRank Projects.

Steps to Create a Data Science Question 

  • Click on the Library tab on the home page and click on the Create Question button.Create_Question.png
  • In the Select Question Type dialog box, under Projects, select Data Science as shown below. 
  • Once you choose the role, you will be proceeding to the stage where the question can be designed. Select_question_type.png

Select Environment

  • In the Select Environment tab, select Jupyter Framework and hit Proceed. 
  • In the Select Environment tab, select the Kernel with which you would like to use the Jupyter notebook. Click on More to view all the pre-installed libraries and packages. Hit Proceed to proceed to the next step.mceclip0.png

Note: The existing questions will be supported on the older version of the platform for the candidates. Recommended versions of the platform are available for creating questions.

  • The Setup Project tab will already be initialized with a sample project for Jupyter Framework. . mceclip1.png
    • The sample project has the necessary files for a candidate to attempt and solve a Data Science question.
    • You can explore the sample project files and create your project to assess candidates.
    • The hackerrank.yml config file (also present in the sample project) is a platform-required configuration file required for configuring necessary project parameters. This file is present by default for Data Science questions in the root directory, and you can choose to edit it only in cases where you might want to edit specific default open paths or to add automatic scoring programs.
    • For Data Science questions, the validation is completed using default files, and uploading a separate .yml file is not necessary. You simply need to upload your project and validate it to move on to the next step. 

Setup Project 

  • You can import your project from a public git URL or upload a zip.Importing_project.png
  • Add evaluation files and actual output files in the third section. To understand how to set up automatic scoring for Data Science questions, read our article: Setting up automatic scoring for Data Science Questions

  • Successful validation of your uploaded project entails the following:

    • It should be a valid project
    • The project size should be less than 5MB
    • hackerrank.yml should be present in the root directory
    • hackerrank.yml should be valid

    If automatic scoring is setup, then:

    • The scoring command should run successfully
    • The scoring command should produce valid output 
    • The scoring command should produce valid test cases
  • If the validation fails, use the information provided by the validation result to fix the project.Uploading_Zip.png
  • Once validation succeeds, you can click on the Save & proceed button to the next tab. 

Define Question

    • Problem Name
      Ensure that the problem name does not hint at the solution to the problem. 
    • Score
      While you can assign any score you want for the questions you create, we use specific standards for assigning scores to the questions we create that you might find helpful.
      Score Question Type
      50 points For a straightforward question that can be solved in 15 minutes
      75 points For a medium question that can be solved in 30 minutes
      100 points For a hard question that can be solved in 45 to 60 minutes
    • Tags 
      Tags are words or phrases that help in searching and organizing questions. You can add existing tags or create new tags. Alternatively, associate custom Tags to identify your Question by its complexity or levels. When you view your Questions in the Library, the associated tags will be indicated for every Question. You can use these Tags to generate candidate reports and performance graphs. Refer to Associating the Tags for Questions for more information.
    • Problem Description
      While describing the problem statement, ensure that the question is clear and detailed. You can also use tables, graphs, or attachments to enhance clarity.
    • Interviewer Guidelines
      Interviewer Guidelines are for later reference. You can include a rubric about scoring the questions or write solutions to the problems in this section. These can be used by your team while evaluating the test. Everything the hiring manager would need to evaluate the question is ideally present here, including the solution Jupyter Notebook, the evaluation script, etc. They are only visible to your team and you; however, candidates cannot view these notes.
    • You can support your problem statement and interview guidelines by attaching a relevant reference file in these sections. Refer to How to Attach a File to a Problem Statement for more information.
  • Click on the Save & Proceed button. define_question.png

The Questions you create are stored in the HackerRank Library under the “My Company questions” section. The Question type and the associated tags are indicated below every Question title.

While in the Library, you can proceed to create more questions or add Questions to your Tests.

 

 

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