Math Department’s New Data Science Program Prepares Graduates for High-Demand Careers in Science, Business and More

The Mathematics Department at Borough of Manhattan Community College (BMCC/CUNY) now offers an Associate of Science (A.S.) in Data Science degree program.

The effort to develop the new degree program was led by Mathematics Professor Annie Yi Han and started with a National Science Foundation (NSF)-funded curriculum project, “Creating Data Science Pathway for STEM Students Success.”

“The creation of the Data Science associate degree program at BMCC is an excellent example of the high-quality academic product a faculty team can produce together,” says Professor Han, who served as Principal Investigator (PI) of the NSF grant alongside four Co-PIs and one key personnel member.

The Co-PIs followed by their area of focus in the project included Mathematics Professors Glenn Miller (curriculum development), Elisabeth Jaffe (recruitment), Oleg Muzician (OER Lab), Jorgé Florez (student success) and Stephen Featherstongaugh (online homework).

Curriculum project reimagines existing mathematics courses and creates data science courses

The curriculum development project funded by the National Science Foundation (NSF) was led by Mathematics Professor Glenn Miller.

“What we did in the curriculum development phase of the project was to redesign and infuse data science concepts into five existing mathematics courses, as well as create four new data science courses,” says Dr. Han.

He adds that graduates of the A.S. in Data Science program will be prepared for a seamless transfer to the Data Science track in the Bachelor of Science (B.S.) program in Applied Mathematics at John Jay College of Criminal Justice, CUNY.

“In addition, we are also pursuing an agreement with New York City College of Technology, CUNY,” he says, and addsthat career options for those holding a degree in data science “are varied and lucrative.”

Career opportunities for graduates with Data Science degrees are dramatically expanding

“Because of the dramatic growth in data used in science, business, government and other fields, employers are in great need of applicants who possess a combination of skills,” says Dr. Miller.

These skills include programming ability, as well as the analytical skills to sort through “mountains of data to find relationships between variables and to ultimately contribute to industry-changing, data-driven decisions.”

He gives an example. “The rise of artificial intelligence presents one application of large data sets. They can be used to develop systems that will drive decision-making and solve problems dynamically and analytically.”

According to the U.S. Bureau of Labor Statistics, the demand for jobs involving data science will increase by 33% over the next three years, better than for most other careers.

The work of data scientists to prepare data for analysis is constantly evolving to accommodate an expanding scope of applications.

Some examples include detecting bias in loan application approvals, detecting credit card fraud, measuring climate change in order to drive legislative efforts, and much more.

Graduates with advanced degrees in data science are prepared for careers as an analyst in the areas of data, business or finance. They become machine learning engineers, data engineers, data architects and more.

Innovative pedagogy fuels open-source online homework system, Data Science Open Lab and student research projects  

The four new courses developed for the A.S. in Data Science program in the Mathematics department are Probability and Statistics for Data Science (MAT 409), Linear Algebra for Data Science (MAT 415), Introduction to Machine Learning (MAT 420) and Python Programming (CSC 203).

In addition to Professor Glenn Miller, Mathematics professors who participated in curriculum development for the new degree program include David Allen, Elizabeth Jaffe, Karl Levy, Adam Li, Jaewoo Li and Micah Miller.

Pedagogical innovations that are part of the new curriculum include an open-source online homework system developed by Professor Stephen Featherstonhaugh. “As an OER developer, I play an important role in reducing costs and increasing accessibility for Data Science majors.”

The Data Science Open Lab project was led by Professor Oleg Muzician, who created Data Science Python lab projects for calculus course and Linear Algebra for Data Science with tutorial videos for the instructors.

A framework for student research projects was developed by Jorgé Florez.

“As a Student Success Coordinator,” he says, “I am committed to engaging our students in internship and research activities in Data Science in order to prepare them for a wide range of future careers in the data science fields.”

Guided pathway supports student success in this high-demand STEM discipline  

According to project materials, the Data Science pathway will support undergraduate STEM education by expanding equity and inclusion in the field of Data Science.

To achieve this goal, BMCC will help students successfully transition from lower-division to upper-division coursework in data science and encourage the participation of groups traditionally underrepresented in a wide range of STEM-related disciplines.

By following a guided pathway model, the Data Science degree program “provides a curriculum which is highly structured and meshes with the program at the four-year college curriculum with which we have articulation,” says Dr. Miller.

He explains that following a guided pathway also ensures pedagogical consistency in the online homework part of the program, as well as with applications used in lab sessions, and with student participation in faculty-led research projects.

The guided data Science pathway starts with a student recruitment activity led by Co-PI and Professor Elisabeth Jaffe.

“In my role, I will be recruiting students into the data science major and working with them to foster and understand the value of a ‘growth mindset,’” a belief that with the right supports and opportunities in place, every student can learn and achieve their academic goals.

“By majoring in data science, students will be able to enter the workforce in a diverse range of careers for which the national demand is very rapidly increasing,” says Dr. Jaffe. “By having a growth mindset, students will be well prepared for any challenge they face in their pursuit of this degree.”

As Dr. Han points out, “In the end, this guided pathway approach is intended to guide our students successfully through the program. It’s a unique approach in this particular STEM discipline of data science, in that it aims to improve the success of students from diverse backgrounds who have struggled in such fields in the past.”

For more information on the Data Science program in the BMCC Mathematics Department, visit here, stop by Room N-599 at 199 Chambers Street between 9 a.m. and 9 p.m., Monday through Friday, call (212) 220-1335 or email ascruz@bmcc.cuny.edu.