What should I start with first? Python for beginners or applied data science?
TLDR: No, it is not required for someone with your background to take &quot;Python for everyone&quot; beforehand.
I have taken the &quot;Applied Data Science with Python Specialization&quot; by UofM and it provided a very soft start in terms of Python for Data Science. Also, see the description of the first course of the specialization &quot;Introduction to Data Science in Python&quot;:

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

As they say, the course walks you through the important libraries, such as Numpy and Pandas, and covers some key methods. Moreover, the second course of the specialization &quot;Applied Plotting, Charting &amp; Data Representation in Python&quot; provides an intro to Matplotlib. So this one is covered too.
Finally, if you would like to go for competitions I highly recommend the course &quot;How to Win a Data Science Competition: Learn from Top Kagglers&quot; (as a next step). It is more advanced than the UofM specialization and provides great insights in the mechanics of and approaches for competitions.