How to choose a bachelor's in data science
Earning a bachelor's in data science degree can position you for a job working with one of the fastest-growing assets in the world — data. As this degree is highly technical, choosing an optimal program for your desired career path can be critical to your success in the industry.
Learn about what factors to consider when choosing a bachelor's in data science program so you can find one that aligns with your career goals.
Guide to choosing a bachelor's degree in data science
When choosing where to pursue your bachelor's degree in data science, there are several key factors worth analyzing before making a decision. Here are some considerations to keep in mind:
DASCA accreditation (optional)
While finding a school with Data Science Council of America (DASCA) accreditation is not a requirement, it does show a school's willingness to offer a superior product to students. DASCA accreditation demonstrates that a school has had its curriculum and program offerings assessed and evaluated by the council.
The criteria used to determine eligibility relate to a program's “all-round capabilities of designing, delivering and managing high-quality data science education." DASCA accreditation follows the Baldridge Excellence Framework, a highly-regarded system designed to help organizations improve performance.
Available specialization and concentrations
Depending on the school you choose, you may have opportunities to concentrate your studies in a particular area of data science, such as business intelligence, machine learning, and data visualization. By doing this, you can earn skills that are more applicable to the job you want post-graduation.
Additionally, this adds to your résumé and helps to set you apart from other job candidates. Keep in mind that these specializations are not offered with every program.
University resources
Data science is a resource-intensive program that relies heavily on access to the latest programs and technologies. Look for a school that prioritizes staying on the cutting edge of technology with the resources they make available to students.
In data science, this may include technologies supporting deep learning, deep reinforcement learning (DRL), edge artificial intelligence (AI), and generative artificial intelligence (GAI). Often, schools that conduct published research in the field of data science tend to lead in this area.
Student-to-teacher ratio
Due to the highly technical nature of data science, finding a degree program that offers a lower student-to-teacher ratio may foster an environment that is more conducive to learning. This ratio is generally less important in lower-level general elective courses, but often becomes increasingly important as you get later into your core coursework and electives.
Another helpful tip is to look for schools where professors conduct office hours when you can come in to get extra help.
Staff credentials
When pursuing your bachelor's in data science degree, who you learn from may be just as important as what you learn. As this industry changes fast, look for a program that has professors who actively stay on top of the latest trends and continuing education.
This information may be tougher to find, but you can look in staff bios and popular industry publications to find helpful information.
Explore bachelor's degrees in data science
Are you ready to journey into the ever-expanding world of data science? Then check out edX's courses and programs in data science and get started today.