Across industries, data scientists are bringing buzzwords to life: artificial intelligence, machine learning, big data, data visualization. Behind the buzzwords are software skills like Python, R, SQL, and Java. The list goes on and can sound intimidating, but getting started is more approachable than ever and the value of foundational, entry-level data science skills is taking off.
“Today with data science, for a lot of it you don’t have to have a PhD anymore. You don’t have to spend years and years studying something. The runway is a lot shorter this year for data science,” said Joseph Santarcangelo, PhD, IBM data scientist, and instructor for several edX data science courses and programs, from Python to deep learning.
“Even some years ago, if you wanted to perform any kind of data science task, you had to spend a lot of time understanding the concepts, learning the programming languages, but now all you really have to know is Python and have a basic understanding of what’s going on and it’s pretty remarkable where you can go.”
Read on for more excerpts from our interview with Santarcangelo, where he shares insights from working in and teaching data science, along with advice for those considering a data science career path or adding data science skills to another discipline.
What Does it Take to Get Started in Data Science?
Most of what I do is stuff I learned in the beginning. I’ll spend a long time learning a framework. A lot of it’s just going into Python, understanding the language, understanding what does what — and those are the first few things I learned.
The first step is the largest. You’re going to make the biggest jump. You’ll get 70% of the way there in your first few steps. A year of studying data science will get you very far.
The hardest part of anything starting it and Python is the first big step to data science.
Why Is It Important to Start With Python? What Advice Do you Have for Students Starting From Scratch?
I think a lot of the stuff you hear hype about… it’s useful, but not everyone needs it. People shouldn’t be focusing on deep learning and machine learning to start. They should be focused on just learning Python, getting the data, and maybe building a simple model that they can use for prediction. That’s where the real gains are.
According to Stack Overflow data, Python is the fastest-growing major programming language worldwide. Learning Python for data analysis gives you access to a wide, general-purpose language that can be used in a variety of industry, research, and engineering contexts.
I find that in our Analyzing Data with Python and Python Basics for Data Science courses, people are pretty surprised at how easy it is. They’re astonished how easy Python is. When you look at programming, it seems like a pretty abstract, difficult concept. If you make a little mistake, everything is wrong. So people usually get scared. But then they start learning, and realize ‘oh wow that’s it?’ And they get very excited and then I usually see them in the next few courses. That’s the biggest aha moment I see.
What Types of People and Jobs Benefit From Python and Data Science Skills?
I see either people wanting to become data scientists and a lot of developers, but I also see others who want to apply data science to their existing field. All kinds of clustering and applying data science techniques to optimize a given profession.
So for the Python course, for the more basic programming courses, I see that broader audience — people you wouldn’t expect taking these courses, disciplines you wouldn’t expect to be associated with data science. Marketing, for example. Or some people who have a basic understanding of finance and they’ll want to get into it and they’ll see that everything in finance is done in Python. So they’ll start picking up Python. And they pick it up pretty fast, which is the incredible part. For the more advanced courses, like the deep learning courses, I see more advanced students.
According to data from Burning Glass, in 2018 alone, more than 1.7 million job postings asked for data science skills. In addition to the increase in job titles like data scientist, data engineer, and big data architect, other disciplines are seeing high demand. For example, one in eight marketing jobs now demand data skills.
Take the Next Step in Your Data Science Path
Whether you’re seeking an entry-level data scientist role, adding data science skills to another discipline, or taking the next step in your data science career, learn more about online courses and programs to help you get started.