Pick from top data science courses to unlock career opportunities
There is a massive shortage of data scientists in the U.S. as companies compete for the talent necessary to unlock the benefits of big data. The University of Illinois and University of Michigan’s data science degrees provide their students with the tools necessary to take advantage of these lucrative opportunities.
Despite growing interest in data science courses across campuses nationwide, the data science pipeline is still too small to fill industries’ needs. While this is an issue for companies, it’s very clearly an opportunity for aspiring data scientists.
“There are as many as 250,000 jobs in the data sciences that will need to be filled by 2024.”
“There are as many as 250,000 jobs in the data sciences that will need to be filled by 2024,” says Professor John Hart, Director of Online and Professional Programs in the Computer Science Department at the University of Illinois. “Our Master of Computer Science in Data Science degree unlocks these career opportunities.”
Thomas A. Finholt, the dean of the School of Information at the University of Michigan, sees his role as preparing students for both the immediate next step and all those that follow. “Whether their goal is professional development in a current position or a gateway to a career in this high-demand field, students will gain real-world, practical knowledge from top-ranked faculty and a degree from one of the world’s most respected educational institutions.”
To take advantage of the increase in data science jobs requires a data science degree that goes beyond quick tricks. A degree program must teach the underlying fundamentals that help students pursue a long-term career, no matter how their field changes over the years. Coursera co-founder Andrew Ng, an early pioneer and an influential member of the data science community, says Coursera degree program partners establish a high bar and set their graduates up for meaningful and durable careers.
That’s what sets the University of Michigan Master of Applied Data Science (MADS) and the University of Illinois Master of Computer Science in Data Science (MCS-DS) programs apart. The multitude of available boot camps and short courses often teach toolkits and languages that will be out of date in the short term. “We are trying to future-proof the students we are training so they can work in the way the world is right now, but also in the way the world will be in the next five to ten years,” says Professor Robert Brunner, the key driver of the effort to integrate data science across curricula at the University of Illinois.
Both Michigan and Illinois start with a strong cross-disciplinary approach, because data science by nature touches nearly all aspects of a business. It requires a T-shaped skill profile, in which you have general knowledge of a lot of fields and then specialize based on the specific applications needed for your job. “We give learners a broad understanding of data science approaches, and use this to understand modern techniques, as well as develop the computational skills to apply these techniques to real-world problems,” says Professor Chris Brooks, in the School of Information at the University of Michigan. “[The degree] helps students situate these new skills in the areas of work or study that are important to them.”
In addition to learning how to use data skills in the context of their profession, both Illinois and Michigan students also benefit from the diversity of peers with whom they interact. “We have to work with so many classmates from so many places—from China, from Thailand, from Canada, from here,” says Gitika Jain, a MCS-DS graduate. “Everyone has their own perspectives and we get to learn from each other. That’s really unique.”
“Everyone has their own perspectives and we get to learn from each other. That’s really unique.”
To develop such a skillset, it is key that learners receive instruction from experts in each of the disciplines. With the University of Illinois online MCS-DS, for example, data mining is taught by Professor Jiawei Han, a Michael Aiken Endowed Chair, who is a well-recognized authority in data mining and an author of the well-known textbook “Data Mining: Concepts and Techniques.”
At Michigan, too, the program is taught by core professors and is no different than what students would take on-campus.
“The curriculum was developed by our own outstanding, educators with extensive experience in designing and teaching critically acclaimed online data science courses that have been taken by hundreds of thousands of students around the world,” says Dean Finholt.
Perhaps the most important way to set students up for a durable career, however, is to provide the opportunity to apply theories and fundamentals to the real-world problems and datasets of companies. This is a focus at both Michigan and Illinois. “The main thing we learn from our MCS-DS students is that they value practice,” says Hart. “These students demand more than just fundamentals and theories. They want to see how they apply to the real world.”
Bruno Ferreira, an employee of the Brazilian government who took classes with the University of Michigan through Coursera, says the practical nature of Michigan’s data science classes is what initially attracted him when he was searching for the right machine learning course. “In Brazil, we have many theoretical courses but very few with practical application,” he says. “At Michigan, each course was related to solving real problems.”
Ferreira took what he learned through Coursera and built a machine learning model to catch fraud in the Brazilian government, winning an award for his efforts and impressing his superiors so thoroughly that they funded the Coursera-facilitated education of another 10 employees. “Thanks to Michigan, I gained a data scientist toolbox, and more importantly, I think as a data scientist now,” says Ferreira.
Vinod Bakthavachalam, a senior data scientist at Coursera, says the ability to point at specific projects is key when applying for a job. “You have to demonstrate that you can apply the knowledge you’ve learned, and if you have some projects where you’ve done that before, that’s golden,” he says.
Michigan will accomplish this through its portfolio-based curriculum. “With three capstone projects and two domain application courses, [the MADS degree] enables learners to demonstrate their knowledge of data science to others, such as potential employers or university programs,” says Brooks.
The MADS program at Michigan is taught through one of the nation’s top-ranked Information Sciences schools, and one that features a 99 percent success rate in employment for grads. The program boasts one of the world’s largest and proudest alumni networks, which is helpful to new graduates’ employment prospects. With an alumni network of 500,000 strong and growing, a student is sure to find a Michigan grad to network with, regardless of industry or location.
Illinois’ MCS-DS also offers the opportunity to tap into a sprawling global network. Illinois features a computer science program that is ranked top-five in the nation, with highly regarded faculty teaching online degree seekers from all over the world.
Illinois MCS-DS students receive a thorough grounding in the tenets of machine learning, data visualization, data mining, and cloud computing. While applicants don’t need to be computer scientists already, they should be familiar with an object-oriented computer programming language (such as C++ or Java), data structures, and algorithms, and college-level calculus and statistics.
Both programs, however, welcome students from a diversity of academic and professional worlds. The goal is to provide everyone an opportunity to pursue a top-level data science degree, and to do so in a way that fits around their schedule and life. “After this course, I changed my mindset. I am now a professional that learns and extracts knowledge in order to solve real problems,” says Ferreira. “It was the turning point of my career.”