interactive-coding-challenges

You can practice coding interview challenges by opening interactive Jupyter notebooks that provide problem statements, code skeletons, unit tests, and Big-O analysis. Each notebook includes reference solutions, allowing you to implement algorithms and immediately verify correctness against built-in tests.

The interview prep challenges cover arrays, linked lists, graphs, dynamic programming, and system design. They span multiple difficulty levels, providing structured learning workflows that take you from problem statement through implementation to verification.

Yes, you need Python and Jupyter installed to run these coding challenges, either locally or in a cloud environment. The notebooks are self-contained, requiring no additional dependencies beyond the standard Jupyter setup to execute the code and run unit tests.

You verify algorithm solutions by running the unit tests built into each Jupyter notebook. After implementing your code in the provided skeleton, execute the notebook cells to automatically check your solution against the test cases and compare it with the reference solution.

The notebooks suit developers and students across multiple difficulty levels, from foundational data structures to advanced system design. Beginners can use the skeletons and solutions for learning, while advanced developers can leverage the challenges for targeted interview fluency practice.

You can use these notebooks for both algorithm problems and system design interview practice. The 120+ challenges include system design topics alongside data structures and algorithms, providing comprehensive coverage with solutions and Big-O complexity verification.