Artificial intelligence and big data are disruptive forces reshaping industries, redefining roles, and raising the stakes in the public and private sectors. As these technologies spread, so does the demand for professionals with the specialized skills to manage complex data systems and extract meaning from information.
To meet these needs, the Woods College of Advancing Studies at Boston College (BC) continually updates its Master of Science in Applied Analytics (MSAA) and Master of Science in Applied Economics (MSAE) programs. These degrees evolve in response to market changes, emerging technologies, and shifting career demands, ensuring that students are prepared not only for today’s jobs but also for future opportunities.
Associate Dean for Strategy, Innovation, & Technology and Director of the MSAA and MSAE programs Aleksander (Sasha) Tomic, explains the programs’ approach this way: “We cannot fully prepare you for future careers, but we can give you a very solid foundation and teach you how to learn— both from us and on your own—so you’re prepared for the ever-changing nature of work. And we do that very well.”
Learn to Solve Complex Problems With Data
Turn Data Into Impact With a Master’s From BC
Solve Real-World Problems
Students in the MSAA and MSAE programs extend academic learning through in-class activities, assignments, and project-based courses designed to mirror real-world problems. Whether working with raw, unstructured data or tackling open-ended problems, students focus on developing skills that translate directly to the workplace, where data doesn’t come pre-cleaned and questions don’t always have obvious answers.
“[We] prepare students for future careers by providing them the applied skills necessary to address the real-world problems of industry, no matter what industry it is,” says Lawrence Fulton, a professor in the MSAA program. This philosophy is reflected across courses where students have numerous opportunities to apply their analytical and problem-solving skills.
For example, in the MSAA program’s Applied Analytics Project course, students complete an end-to-end AI project. Rather than just focusing on the technical aspects, they also build project management, advisory, presentation, and communication skills, gaining hands-on experience in developing analytical solutions to business or policy problems.
Students in the MSAE elective course Applied Stress Testing for Economics delve into financial regulations, including the Comprehensive Capital Analysis and Review (CCAR). They build “bottom-up” and “top-down” stress-testing models that incorporate real economic scenarios and, for the final project, present their work to experienced banking professionals. These exercises build real-world experience in financial modeling and business communication.
The Data Analysis course, which both MSAA and MSAE students take early in their programs, introduces students to the foundations of statistical and data analysis in a hands-on format. Using the statistical software Stata, students learn to conduct empirical analyses that reflect the kind of work they will encounter in professional settings. They acquire hands-on experience using their analytical and problem-solving skills. They also participate in case competitions, sharpening their skills among peers in an engaging and friendly setting.
These courses and projects adapt over time. As technologies evolve and industries shift, so does the curriculum. Assignments, areas of focus, and tools that students engage with change to align with the latest trends and the real-world demands of data-driven roles across sectors.
Gain Practical Experience
Experiential learning is a cornerstone of both the MSAA and MSAE programs. Many required and elective courses offer hands-on experience in programming and modeling, helping students refine their ability to solve real-world problems through applied techniques.
In the MSAA program, students gain practical experience through courses such as:
- AI/ML Software Tools and Platforms, which equips students with the data engineering knowledge needed for data science research projects and industry products
- Predictive Analytics/Forecasting, which introduces students to common forecasting techniques used in industry
- Computer Vision, which covers computer vision concepts and techniques and teaches students how to perform classification, detection, and recognition tasks
In the MSAE program, students apply analytical tools to economic data and theory through courses such as:
- Econometrics, which focuses on the use of statistical methods to estimate economic relationships
- Big Data Econometrics, which explores the integration of economic data analysis and applied econometric tools with machine learning techniques
- Software Tools for Data Analysis, which introduces students to widely used software packages for data exploration, analysis, and visualization
These courses develop technical competencies and build essential interpersonal skills. Students gain experience with statistical software and programming languages like R and Python to conduct data analysis. But just as importantly, they learn how to communicate their findings clearly and effectively.
As Assistant Professor of the Practice in Applied Economics Arvind Sharma explains: “We try to holistically build different skill sets, both the hard skills and the soft skills, so that [students] become effective analysts and can deliver their results to the stakeholders and convince the people that this is the analysis that should be implemented.”
Dive Into Pressing Issues
Research opportunities are central to both graduate programs, providing students with chances to write papers and present their work to peers and industry professionals. Student Trevor Petran shares, “It was great to have heads of AI from different companies see our work, not just to see what we did but to help us understand how to improve on future projects.”
Fulton emphasizes the importance of these experiences: “One of the things that we focus on is providing students opportunities such as research with faculty members, opportunities to present at symposia, and opportunities to conduct real-world applied research.” Fulton notes that students and faculty collaborate on research in areas such as natural language processing, computer vision, predictive analytics, and statistical modeling.
Faculty research continues to advance the field and shape program curricula. Drawing on the resources of a nationally ranked research university, Woods faculty—active practitioners with decades of relevant experience—bring cutting-edge research and practical insights to the classroom. Their ongoing work ensures that the programs evolve in tandem with rapidly changing industry demands.
Learn from Industry Professionals
In addition to full-time faculty, the MSAA and MSAE programs feature an adjunct faculty of highly accomplished industry professionals who bring firsthand experience in growing fields like AI, machine learning, and data analytics. Their contributions enrich student learning by bringing in real-world insights and up-to-date industry practices. They also help ensure the curriculum stays in step with the latest trends and what employers are looking for.
Advisory boards, comprised of BC professors, faculty from other institutions, and thought leaders, further contribute by shaping course offerings and ensuring the programs stay ahead of the curve. Together, these close industry ties keep the programs fresh, practical, and aligned with the needs of today’s employers.
Tomic shared one example of how faculty draw on their expertise to inform the classroom experience: “We have a faculty member who leads AI efforts at a major international consulting company and works across various industries. [He created] a technical generative AI course to help students build on their underlying abilities in areas like analytics and coding, so that they can better understand, interact with, and even contribute to the gen AI revolution.”
Petran appreciates learning from industry veterans, explaining: “Being able to work with people who have been in the industry and who are not just succeeding but thriving is very valuable.”
Develop into an Ethical Professional
Another key factor that sets the MSAA and MSAE programs apart predates AI or even computers: a strong emphasis on ethics. Rooted in BC’s Jesuit values, both programs prioritize not only how people use data and AI but why. This means teaching students to consider the broader impact of their work: who it affects, what values it reflects, and how to approach complex problems with integrity and accountability.
This values-driven approach was a major draw for student Gina Accapinti. “It’s not just about learning the different concepts, but focusing on ethics and learning what is the right thing to do. It’s about being good stewards of data and good decision-makers in our careers.”
These principles are threaded throughout the curriculum, ensuring that graduates master technical tools while appreciating the responsibility that comes with using them. As ethical concerns around data use and generative AI continue to dominate headlines, BC’s emphasis on teaching students to “do the right thing” positions them to make a meaningful, positive impact now and in the years to come. By centering conversations around responsible data use, these programs equip students to respond to today’s challenges and lead with integrity as they help shape the future of the field.
Prepare for Your Future at BC Woods
The MSAA and MSAE programs at BC Woods prepare students for today’s workforce and the rapidly evolving future. With a curriculum that continually adapts to industry trends, students gain hands-on experience alongside foundational knowledge, ensuring they graduate ready to contribute and adapt to new challenges.
As Sharma explains, “It’s not just talking about AI, it’s actually doing AI. And that, I think, is our distinct advantage and helps students be prepared for the world outside that is changing at a very rapid pace.” Fulton agrees, highlighting the programs’ applied focus: “These BC Woods College programs prepare students for the AI workforce by the term in its title: Applied. Students will apply the skill sets in nearly every non-foundational class, from natural language processing to computer vision to predictive analytics to generative AI. We take it seriously when we say ‘applied.'”
Students in the MSAA and MSAE programs build a strong foundation and acquire the tools for success in a rapidly changing landscape. Each program targets a distinct focus and application:
- MSAA: This STEM-designated program equips students with skills in data analysis, machine learning, and AI to solve real-world problems. Graduates apply advanced analytical techniques across diverse industries.
- MSAE: This program emphasizes the quantitative skills and knowledge required to analyze and interpret data across various fields. Graduates contextualize data, communicate findings effectively, and make data-driven recommendations.
Next Steps: Learn More About BC Woods Programs
Whether you’re just starting your career or looking to advance or broaden your expertise, BC Woods offers flexible degree options designed to meet your goals. Both the M.S. in Applied Analytics and the M.S. in Applied Economics provide the skills and experiences needed to succeed in today’s dynamic job market. To learn more about which program is the better fit for you—or to explore the possibility of earning both with the dual-degree option—connect with an enrollment advisor, or, if you’re ready, start your application today.