Dispelling misconceptions about data science

Data Science is not just statistics

Data science is a field of study that uses mathematics, computer programming, statistics, and scientific methods to analyze data. There are many different types of data science, including machine learning, artificial intelligence, natural language processing, computational linguistics, and predictive analytics.

Data scientists don’t need a degree in math

A bachelor’s degree in mathematics is often assumed to be necessary for entry-level jobs in data science. However, data science does not require any formal training in mathematics. Many people who have worked in data science do not have degrees in math.

Data scientists aren’t necessarily good at coding

While some data scientists may know how to code, they are not necessarily good at it. In fact, many data scientists are programmers first and foremost.

Data scientists don’t work alone

Many data scientists work alongside statisticians, engineers, and business analysts. These professionals help data scientists understand their data and provide context for what they are doing.

Data scientists don’t always use big data

Some data scientists use small datasets, while others use large ones. A data scientist might use a single dataset or hundreds of them.

Data scientists don’t spend their days crunching numbers

Data scientists use statistical techniques to solve problems and make predictions. While they may use computers to crunch numbers, they don’t spend their time doing so.

Data scientists don’t write algorithms

Algorithms are mathematical formulas that describe how to perform tasks. Algorithms are written in programming languages like Python, R, C++, Java, and JavaScript.