CoderPad September Releases
Discover how you can run your data science interviews with Jupyter Notebook, conduct more realistic interviews with multi-file projects, and benefit from AI-generated follow-up questions.
CoderPad Interview Updates
Jupyter Notebooks for data science interviews
Jupyter Notebooks (Minimal, R, TensorFlow, SciPy) are now available in the pad environment! Run awesome, on-the-job data science interviews using:
- Ability to increase processing power to handle large data sets
- A fully-functional Jupyter Notebook environment
- Ability to import and utilize any package or library
- Plot data and run individual cells in the notebook
- Access to the server, shell and console
CoderPad multi-file projects offer a highly realistic and flexible environment, where you can add more files, write and run unit tests, install packages from the shell, and more.
CoderPad Screen Updates
Dynamically saving code edits
When a candidate updates code in the Screen code editor, they are now saved automatically. Code can also be saved manually by using CTRL+S keystrokes.
Follow-up questions for cheating prevention – Beta
Are you concerned that candidates will paste code from ChatGPT and give an inaccurate view of their coding skills?
While many developers use these tools to be more efficient, the problem is when people blindly copy and paste code they don’t truly understand.
CoderPad Screen is introducing a feature to address this issue. You’ll have the option to activate AI-generated follow-up questions for coding exercises, based on the specific code the candidate provides. This will give insight into whether the candidate truly understands the code. If you’d like exclusive early access as a beta tester (in return for feedback), share your email address here or respond to this email.
Custom question page design update
The custom questions page now has the same design and features as the general question bank page. This will make it easy to create a test directly from your created content.