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Choose a plan and master interview patterns at your own pace.
Choose a plan and master interview patterns at your own pace.
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A guided technical-interview platform for software engineering, data science, machine learning, and applied AI roles.
Yes. Learn each concept, apply it to progressively harder problems, then practise explaining and repairing code in interview-style exercises.
Yes. Algorithms follow a dependency-ordered topic path. Data and ML content progresses from Python and probability to experiments, modeling, deployment, RAG, and LLM evaluation.
Use the thought process and explained solution for an Algorithm problem, or reveal staged hints and a reference repair in the Interview Lab.
No. Learner code is not published. CodeBaobab provides reviewed solutions and alternative approaches where they add value.
No. Courses, the Python and JavaScript IDE, editable project files, and interview exercise tests run in your browser.
Run checks the examples you can see. Submit checks additional edge and scale cases before marking an Algorithm problem solved. Interview Lab exercises run their project tests.
Completed courses and accepted Algorithm problems sync to your account. Interview Lab progress is saved in your browser.
Not yet. Repository-style pair-coding exercises and interview drills are available, but live mock interviews and timed assessments are not.
Yes. Big O, Arrays, Strings, 10 progressive Algorithm problems, Python for Data Work, and the Game of Life interview exercise are free.
There is no fixed schedule. New material is added when it strengthens the learning path and passes content, solution, and test reviews.
Email support@codebaobab.com with the problem URL, language, and what you expected versus what happened.