Artificial intelligence is no longer just the stuff of dystopian sci-fi novels—it’s a vital aspect of business technology throughout every industry. It may not look like the exotic future we pictured, and in fact, sometimes we barely notice its ubiquity. Personal assistants like Siri and Cortana are more obvious examples, but we’re also served by smart recommendations (think Netflix or Amazon), spam filtering, predictive customer service, voice to text, and smart devices that adjust to human behavior over time. That’s just scratching the surface of what’s already out there.
Even with everything that’s already available to us, the field of AI is still in its infancy, and its growth shows no signs of slowing. If anything, the demand for skilled workers is greater every day, offering lucrative and challenging careers with job security and opportunities for world-changing innovation. This is especially true for data scientists with a specialty in machine learning.
An Employment Boom for Data Scientists
Employment growth in artificial intelligence, according to a LinkedIn emerging jobs report, shows 74% growth over the past four years. Data science jobs, including machine learning, have increased 37% over three years. According to a Dice.com article about data science and machine learning, these combined skillsets were the most-sought by developers looking to keep up with the cutting edge of their field, with 45% seeking professional development at that intersection.
It also shows an average salary of $19k more for mid-level data scientists working in machine learning over a traditional data science path. Tools that allow developers to build and explore are becoming cheaper and more accessible, and machine learning skills open doors to projects that drive change and offer opportunities for career advancement and professional achievement.
What Does Data Science Have to Do With Machine Learning?
To understand the role of data science in artificial intelligence, we first need to take a step back and understand the difference between machine learning and artificial intelligence. Although they sound similar, they’re not interchangeable. Artificial intelligence is a broad term that refers to a computer that is able to imitate human thought or behave in ways that humans do. Machine learning is a subset of AI that allows computers to learn to solve problems in ways that previously seemed impossible.
The way that it does this is through complex algorithms that are able to predict outputs based on statistical data, and that can update outputs as new data is added, without additional programming. These predictions are extremely accurate, and become increasingly sophisticated over time.
Data science dovetails with machine learning because machine learning models can take the huge datasets built by data scientists and learn to process them—and to do so with remarkable speed and accuracy. The field of data science covers the whole of data processing and involves a wide range of aptitudes, with machine learning being one discipline among many.
The field of AI needs data scientists versed in machine learning because machine learning requires experts who understand the mathematics and predictive models required for it. It requires detailed statistical analysis to be able to determine what algorithms to use, and to be able to test a prototype. Data scientists don’t necessarily need to be experts in the software used to put those prototypes into production, instead working in partnership with machine learning engineers to bring their models to life.
Loyola’s Data Science Program: At the Cutting Edge of Your Future Career
Loyola is committed to ensuring that all of our students learn up-to-the-minute skills that prepare them to be at the forefront of their chosen field, and the Data Science Program is no exception. With offerings for both undergraduate and graduate students, we’re here to take you every step of the way to your career in data science.
All Data Science students learn Python and R, two of the most common programming languages for data scientists as well as machine learning professionals. At the undergraduate level, you’ll have the option to study artificial intelligence. At the graduate level, our Technical Specialization includes required coursework in machine learning that will put you in the ranks of highly-desired qualified candidates for jobs at the crossroads of data science and machine learning.
Of course, your studies will also include examination of the ethics of data science—an essential part of your learning path, as machine learning in business processes and monetizes often highly-personal information about millions of consumers. The field of artificial intelligence will need data scientists who are steeped in Loyola’s Jesuit values and strong desire to create ethical business leaders working toward the greater good.
Take The Next Step
If you’re a prospective student considering Loyola’s Data Science Program for your undergraduate or graduate school work, or a current student intrigued by the career potential found in a machine learning specialty, request more information or attend one of our virtual information sessions. With a degree in data science specializing in machine learning from Loyola, you’ll enjoy a lucrative, secure career while you’re driving innovation and changing the face of business worldwide.