by:

This is the Public Data Science Test. Any serious candidate should answer all questions. This test shall be performed on-site.

The candidate should be familiar with:

1. Git and github code repositories -- cloning the exam.
2. Python programming for Data Science (basic: numpy, pandas and matplotlib).
3. Theoretical background. Key machine learning concepts. Mathematics, probability and statistics. Be able to translate theory into practice (code) from scratch.
4. Jupyter Notebooks.
5. Recursion (from functional programming).

• Clone the exam form terminal using git clone.
• Choose 3 problems.
• Answer each question following the instructions in the jupyter notebook. The order is irrelevant.
• You may ask questions if needed. Part of the evaluation consists on seeing how you handle problems.
• You can test your solution with not-so-good code practices. Following the best-practices is encourage.
• Use of apply, lambda functions, maps (or list comprehension) over for/while loops is preferred.
• After completing the test, change the name of the jupyter to 'FirstAttempt_MyName' replacing your name in 'MyName' (as 'MartinOdersky').
• Download your answers as an HTML file and send the .ipynb and .html to [email protected] with the headline '[Data Science Test] MyName'.

Happy coding! May the knowledge be with you!