Test your knowledge

To help you remember what you just learned, try answering the following questions. Try to answer the questions without looking back at the answers in the chapter at first. The answer key is included in the GitHub repository for this book (https://github.com/PacktPublishing/Practical-Data-Science-with-Python).

1. What are the top three data science programming languages, in order, according to the 2020 Kaggle data science and machine learning survey?
2. What is the trade-off between using a GUI versus using a programming language for data science? What are some of the GUIs for data science that we mentioned?
3. What are the top three cloud providers for data science and machine learning according to the Kaggle 2020 survey?
4. What percentage of time do data scientists spend cleaning and preparing data?
5. What specializations in and around data science did we discuss?
6. What data science project management strategies did we discuss, and which one is the most recent? What are their acronyms and what do the acronyms stand for?
7. What are the steps in the two data science project management strategies we discussed? Try to draw the diagrams of the strategies from memory.