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Notebook Challenge

Overview​

Notebook Challenges allow candidates to work within a fully integrated Jupyter Notebook environment. These are ideal for evaluating complex data analysis, engineering, and machine learning workflows.

Configuration Process​

Creating a Notebook challenge follows a guided workflow to define the analytical environment and evaluation parameters.

Step 1: Basic Details & Data Environment​

Configure the metadata and optional data resources:

  • Challenge Metadata: Provide the Name, Description, Difficulty, Duration, and Tags.
  • Database Selection (Optional): You can link a pre-configured Database that will be directly accessible within the notebook for data retrieval and analysis tasks.

Basic Details and Database

Step 2: Technology Selection​

Choose the notebook execution environment. Currently, Jupyter Notebook is the supported technology, providing a robust platform for Python-based data science.

Technology Selection

Step 3: Runtime Review​

Review the technical configuration and runtime details for the Jupyter Notebook environment to ensure all necessary system resources are correctly allocated.

Runtime Review

Post-Creation: Environment & Content Setup​

Once the challenge is created, navigate to the Code tab from the Challenge General Details Page to finalize the technical content.

Code Tab Overview

Preparing the Notebook​

The Edit Code interface provides a full Jupyter environment where you can:

  • Initialize Cells: Pre-populate the notebook with markdown cells for task instructions and code cells with helping commands (e.g., library imports or data loading) to help candidates get started.
  • Data Access: If a database was linked during Step 2, candidates can use the Database tab in the right-hand panel to browse the schema and execute test queries while building their models.

Notebook IDE Interface Candidate View with Instructions

Using the Right Panel​

The right panel provides essential tools for the candidate:

  • Challenge Instructions: A dedicated space to review the problem statement and requirements without switching away from the notebook.
  • Database Helper: A utility to execute SQL queries and view results, facilitating data-driven notebooks.

Database Tab and Query Execution

Ensure you click Save Changes once your notebook content, boilerplate cells, and instructions are finalized.

Next steps​