Table of Contents
- Introduction
- Software Engineering
- Data Science
- Summary
- References
Introduction
Although data science job descriptions require a range of various skillsets, there are concrete prerequisites that can help you to become a successful data scientist. Some of those skills include, but are not limited to: communication, statistics, organization, and lastly, programming. Programming can be quite vague, for example, some companies in an interview could ask for a data scientist to code in Python a common pandas’ functions, while other companies can require a complete take on software engineering with classes.
As I have been apart of several positions and a wide array of various companies, I have encountered data scientists and software engineers, and therefore have developed a good sense of what is required to become a successful data scientist. Below, I will outline software engineering and data science, and answer the question: “Is Software Engineering a Prerequisite for Data Science?”.
Software Engineering
Just like data science, this field within computer science can include several different skills. However, most of these roles will require you to be proficient in at least one programming language, as well as know the software development lifecycle. The programming and coding languages often used by software engineers are [2]:
Java
Python
C#/.Net
Ruby
#machine-learning #data-science #towards-data-science #programming #software-engineering
