We spoke with Dr. Dave Dimas to learn more about the online Certificate in Data Science at UC Irvine. Continue reading to learn what sets successful students apart, the importance of continuing education for data scientists, and what to look for when choosing between a certificate and master’s degree program.
Dave Dimas, Ph.D is a lecturer in the Department of Mechanical and Aerospace Engineering, as well as the Director of Engineering, Sciences and Information Technology Programs for UC Irvine Extension. He is responsible for overseeing the development of current curriculum and evaluating the need for new courses and certificate programs.
Dr. Dimas received Bachelor’s degrees in Biological Science and Mechanical Engineering, a Master’s in Engineering Mechanics, and a Ph.D. in Civil Engineering, all from UC Irvine.
The students who really thrive are not necessarily computer science majors. In fact, some of our strongest students have come from non-computer science, non-math backgrounds, such as history, language and lots of other backgrounds. All it takes is a little penchant for science and math. Students who aren’t afraid of computers or math tend to do really well in these programs.
This is absolutely key. More and more mid-sized companies are beginning to realize the significant impact of collecting and analyzing data. Larger companies have been doing this for a while. Now we’re seeing it in mid-sized companies, too. Between the large and the mid-sized companies, there’s a tremendous demand for people who are trained in data science.
Secondly, there’s a limited supply of people with these skills. These are fairly new undergraduate and graduate degrees, so the number of people who have completed these programs is still relatively low. Accordingly, there is a significant gap in the market as far as demand and supply are concerned. The demand is way, way higher than the supply. That’s awesome for data science professionals.
The biggest piece of advice is to get out and connect. Go to industry and professional association meetings. There are also larger conferences. Some conferences are more industry focused, such as Predictive Analytics World. Other conferences and societies, such as the Digital Analytics Association, offer more local events. Go to these meetings and talk with the people there. Make a point to meet 5 or 10 new people in the industry. This is important for two reasons. First, it gives you some ideas on how you might be applying data science and predictive analytics in your future career. Second, it connects you with people who can provide invaluable insights to help guide your career as well as helping you with future job opportunities.
This is a really good way to start the transition back into the classroom and get introduced to the material. It also allows students to make much more informed decisions as to their long-term goals. In fact, that’s the typical progression we see from students. It starts with a commitment to an individual course, then perhaps a commitment to a larger certificate, and then possibly a commitment to the master’s.