Creating a Data Science Question

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 explore 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.
• In the Select Question Type dialog box, under Projects, select Data Science, as shown below. 
• Once you choose the role, you will proceed to the stage where the question can be designed.

Step1: Environment

• In the Environment tab, you can select the Kernel with which you would like to use the Jupyter notebook.
• If you want to know the package information, click on the View Package Info button.
• Click on the Next button to move forward to the next steps.  

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

Step2: Project Setup

• On the Project Setup page, you can choose one option between Upload Zip or Github URL to upload your project.  
• The Project Setup tab will already be initialized with a sample project for Jupyter Framework. You can download this sample file by clicking the Download Sample Project button at the top right corner of the page.   
  • 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. You can edit it only in cases where you want to edit specific default open paths or add automatic scoring programs.
  • For Data Science questions, the validation is completed using default files, and uploading a separate .yml file is unnecessary. You must upload your project and validate it to move on to the next step. 
• You can expand the code editor by clicking on the maximize icon.
• This feature enables you to work with your code on a large screen to have a seamless experience. You can return to the normal view by clicking on the Exit Fullscreen button.
  
• You can also add additional files containing external files, such as data sets and scripts. You can copy the file link using a command and refer to it inside the question notebook.
• Eg: !wget 'https://xxx-abx.amazonaws.com/abcx/abc/test.zip'
• You can upload files upto a total of 500 MB
  
• Each file should not be more than 100MB."

• HackerRank platform supports the use of externally hosted datasets with a maximum total size of 5 GB. When working with these datasets, it's important to keep in mind the underlying machine specifications, which are as follows:

  • CPU: 2 vCPUs
  • Memory: 16 GB RAM
  • Storage: 20 GB Disk size

  

• There are two options to evaluate the Data science questions:
  • Manual: Using this, you can evaluate the candidate's answer independently.  
  • Automatic: HackerRank platform will automatically evaluate the candidate's answer.  
• You can use the Automatic Scoring Enabled toggle switch to switch between the two modes. 
• If you have enabled Automatic Scoring, you must select a Scoring Metric from the dropdown in the Scoring Metric section.
• To perform the automatic scoring, you must upload the candidate submission file on which the scoring metric would be evaluated.
• You can also upload the following:
  • Expected Result File: This contains the actual result, which will be used to generate the score. 
  • Sample Submission File: A sample file that you expect the candidate to submit.
• For more details regarding the scoring, you can visit this page: Setting up automatic scoring for Data Science Questions

• Once you finish uploading your files, click on Validate to check whether your project is valid. 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 set up, then:

  • The scoring command should run successfully
  • The scoring command should produce valid output 
  • The scoring command should produce valid test cases

• Once the validation is successful, you will be notified on the screen, as shown below.  
• You can view the validation steps by clicking on View All Steps under Validation Status.   
• If the validation fails, use the information provided by the validation result to fix the project.
• Once validation succeeds, you can click on the Next button to the next tab. 

Step3: Question Details

• • 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. You can look at How to Attach a File to a Problem Statement for more information.
• You can use the Try Question feature If you want to try out the question you have just created.
• Click on the Save button to save it to your library.

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 create more questions or add Questions to your Tests.