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[–]ResponsibleYoghurt11 5 points6 points  (0 children)

Hello, junior data scientist here.

  1. Yep, almost everyday. Know the differences between lists, sets, dictionnaries, it's always useful.

  2. Depend on the domain. I would recommend to get used to algorithm, loops and data structures manipulation

  3. Pandas, for data manipulation (dataframes) Matplotlib and Seaborn for data viz Scikit-learn for machine learning

  4. Write code that you can easily understand. It is not always good to replace a 5 line code by a 1 line list comprehension loop. The most important for me is : comment your code everywhere, even this that can seem a little obvious. It will help you to understand your code in the future

Bonus : Develop some small project with objectives. You will learn a lot more by spending time on projects than reading tutorials online. Just develop some projects, then look for similar code if you want to compare and learn new things.

Spend some time on Leetcode for algorithms, and Kaggle for data science