By Paula Aven Gladych for Galvanize
Data science isn’t necessarily for everyone. There are a ton of opportunities in data science and it is a very popular career choice, but there are certain prerequisites people need before taking on the challenge of data science.
Neophytes can become data scientists, but they need to meet the following criteria.
First, you need to be generally curious and like to solve problems, says Jack Bennetto, head of Galvanize’s data science immersive bootcamp.
Second, you need to be self-critical.
“There have been a lot of people who have come into [our data science program] from the humanities, and although it takes them a little more work, they are able to get through the program and get a job in data science.”
Jack Bennetto, head of Galvanize’s data science immersive bootcamp.
“A lot of being a data scientist is just being a scientist, being able to look at your ideas, criticize them, and try to fix them instead of holding onto what you believed before,” Bennetto says.
Third, you need to have a growth mindset, he says. You need an attitude that you are always willing to learn new things and accept new challenges along the way.
As far as prerequisites are concerned, Bennetto says that interested people should be reasonably good at math – a little calculus, statistics, and linear algebra – and programming.
“Some of this stuff people can learn on their own,” he says. “Having more math is better but it’s not necessary for you to have a Ph.D. in mathematics to succeed as a data scientist.”
He encourages interested parties to search the internet for free courses.
“There’s a lot of free material out there and you can make a fair amount of progress on your own,” Bennetto says.
Python is the best programming language for data scientists to learn because it is a general-purpose language and is easy to integrate with other applications.
Galvanize offers prerequisite courses in math and Python. It offers a free basic prep course that anyone can take, which is mostly online but provides an opportunity to ask questions.
Once learners have the prerequisites down, they can enroll in either Galvanize’s data science immersive bootcamp or Galvanize’s remote data science immersive class.
Bennetto encourages prospective data scientists to take a data science immersive bootcamp because it will give them the opportunity to work with and learn from other people.
“You can get pretty far learning on your own at Coursera or wherever else, but at some point, it becomes difficult and frustrating if you don’t have anyone else to do that with,” he says.

Students in the data science bootcamp also get help from experienced instructors who have industry experience and can answer questions much more quickly, he adds.
“Many of our students have technical backgrounds. Some come in with advanced degrees in science, but some of them don’t. They still need to be reasonably good at math and reasonably good at programming or be able to figure it out. There have been a lot of people who have come into it from the humanities and although it takes them a little more work, they are able to get through the program and get a job in data science,” says Bennetto.
Students who enter the field via the humanities usually have a skill that many engineers and scientists lack, which is the ability to write and communicate well.
With software engineering, people work very closely with other software engineers. But in data science, people interact with many people who don’t have technical backgrounds.
They may need to explain to others in the company what the problem is and what the fix is in terms that make sense to someone who isn’t a scientist or engineer.
Ready to jump into data science? Start learning with Galvanize’s free data science prep course or apply for our Immersive data science Bootcamp.

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