Master of Science (M.S.) in Data Science

In an era when data-driven decisions and systems influence every sector of business and society, talented professionals who bring an ethical framework to data science are more in demand than ever. The online m. S. In data science program empowers you to apply technical methods, employ an ethical lens, and utilize relevant management skills to address the needs of organizations and communities, preparing both experienced professionals and recent college graduates for rewarding careers in one of the world’s fastest-growing fields. 

About the program
Our program

• Our online M.S. in Data Science program provides interactive programming by offering small class sizes that incorporate discussions, group projects, and case studies.

Free Python Programming Boot Camp for M.S. Data Science Students

• This self-paced boot camp provides approximately 35 hours of comprehensive instruction and engaging assignments, priming you with essential Python programming skills to be successful in your degree program. For those without Python experience, it is recommended that you complete the optional boot camp before commencing your program.

Ethical Data Science

• The field of data science is rapidly expanding and requires professionals who can take a distinctive and empathetic approach to it. The online M.S. in Data Science program emphasizes the importance of ethical and responsible handling of data. Our program underscores the significance of prioritizing people and society in all analytical and decision-making processes. Upon completion of this program, you will be equipped with the knowledge and skills to transform data science for the betterment of society.

In this program, we draw from the rich strengths of Boston College's Jesuit background to integrate a focus on ethics into every aspect of what we do, and into every single one of our courses. Some examples of what this looks like include:

• Our Fall 2024 speaker, Microsoft Partner Research danah boyd's, talk on "The Challenges of Pursuing Responsible AI"
• Weekly ethical goals in "Programming for Data Science"
• Modules on model explainability and model fairness in "General Linear Modeling"
• Class discussions on ethical considerations in "Applied Math for Data Science"
• Modules on formal frameworks for ethical reasoning from the philosophical tradition in "Introduction to Human-Centered Data Science"

Case studies on:

• Bias and accountability in facial recognition
• Bayes' rule & ethics in medical testing
• Ethical considerations in constrained optimization with Lagrange multipliers
• Quasi-identifiers, re-identification risks, privacy breaches, and Responsibility in the OKCupid study
• Ethical considerations in using race as a predictor in algorithmic college advising
• Facebook's "emotional contagion" study, consent, externalities, and foreseeable harms

You'll engage with this human-centered approach and our core value of ethics throughout our program in a number of ways, including: 

• Hearing from, and asking questions to, the speakers in our speaker series
• Sharpening each others' thinking on our course discussion boards
• Lively case study explorations in our synchronous sessions
• Making thoughtful choices and taking ownership of them with real-world data in your course final projects
• Carrying out responsible, transparent, and reproducible work for a client in your capstone projects

Learning Outcomes
This program will enable you to:

• Approach data science with a human-centered mindset by centering ethics, bias, and security and privacy issues that can influence findings and subsequent decision-making.
• Apply ethical problem-framing and problem-solving methods to evaluate organizational and project needs, identify potential issues, and understand production-level solutions within a team focused on meeting their organization’s or client’s strategic goals.
• Develop appropriate formalizations of project goals and apply statistical, mathematical, and data processing approaches to complex data analytic problems.
• Develop data engineering and applied database management skills while considering ethics, accountability, and data privacy and standards.
• Code in industry-standard programming languages for data science, machine learning, and statistical computing to solve a wide range of data mining and data science problems. 
• Apply their experience with statistical analysis, machine learning, and deep learning tools to real-world scenarios to uncover critical insights in data projects for improved decision-making.
• Interpret data and represent findings visually, orally, and in writing through visualizations, reports, and evidence-based storytelling techniques that ask the right questions and provide persuasive narratives to build consensus and improve outcomes.

At a Glance

• How many courses?- The program consists of 12 courses (36 credits). 
• How long will it take?- Students will spend 2 years pursuing the online program on a part-time basis.
• When can I start?- Students begin the program in the fall semester.
• How much does it cost?- To estimate your total program cost, multiply the number of credits required in your program by the tuition cost per credit.