BloomTech Blog

SQL, short for Structured Query Language, is a standard programming language used since the 1970s to design, create, and manage relational databases, and it's been a top data science language for over 50 years.

Developers, analysts, and data scientists alike use Python not only to “automate the boring stuff,” but also to clean, query, and analyze data, create web applications, and integrate systems more effectively.

Python is a versatile, high-level programming language that’s used for web development (server side), software development, mathematics, and data science.

Data science is a complex, challenging field of work that has practical applications in nearly every part of our lives, and you can start learning the basics without paying a dime.

The demand for data scientists in 2020 has increased by an average of 50% across healthcare, telecommunications, entertainment, and the banking, financial Services, and insurance sectors, among others. So what's next for data science in 2021?

Applicants for our data science program often ask us whether they need a background in math to be successful at data science. The answer is: not necessarily – but it certainly helps.

A data scientist practices the art of data science. They solve complex data problems with their expertise in mathematics, statistics, computer science, programming, and other scientific disciplines.

So, you want to learn how to become a data scientist. Good choice! Data science is one of the buzziest and most lucrative fields to emerge in the past decade, and for good reason.

Dubbed the “sexiest job of the 21st century” by Harvard Business Review, there’s no doubt data science a hot career – but is it the right path for you?

How can you, a job seeker who may not meet all of the listed educational or technical requirements, get hired? Follow these three rules: Be flexible, be realistic, and use your network.

Understanding the skills data scientists need is your first step toward this rewarding career. BloomTech can help you get started.