In short, understanding Python is one of the valuable skills needed for a data science career. Though it hasn't always been, Python is the programming language of choice for data science. Here's a brief history: In 2016, it overtook R on Kaggle, the premier platform for data science competitions.
When you Google for the math requirements for data science, the three topics that consistently come up are calculus, linear algebra, and statistics. The good news is that — for most data science positions — the only kind of math you need to become intimately familiar with is statistics.
(Structured Query Language) is used for performing various operations on the data stored in the databases like updating records, deleting records, creating and modifying tables, views, etc. SQL is also the standard for the current big data platforms that use SQL as their key API for their relational databases.
(in python*)Knowledge of algorithms and data structures is useful for data scientists because our solutions are inevitably written in code. As such, it is important to understand the structure of our data and how to think in terms of algorithms.