At Emmanuel College—located in the heart of Boston’s innovation and tech hub—the Data Science major prepares students to lead in a world defined by information.
Every click, swipe, and sensor generates data—but only those with the skills to interpret it can truly lead in today’s information-driven world. Data science is the engine behind decision-making in fields from healthcare to business to environmental sustainability. It’s how we understand patterns, predict outcomes, and solve complex problems at scale.
Why Study Data Science at Emmanuel?
At Emmanuel, data science takes you beyond algorithms and analytics to applying technical skill with purpose. Through interdisciplinary coursework in math, computer science, ethics, and statistics, students build a powerful toolkit for tackling real-world challenges. With personalized support, a built-in internship component, and the unmatched opportunity of being in the heart of Boston, you will study the science of data, but also work with it, question it, and use it to make an impact. Whether you pair it with another major or pursue it on its own, Data Science at Emmanuel prepares you for a future at the forefront of innovation.
Outcomes & Outlook
36%
4
$138K
The Curriculum
Core curriculum
- COMP1101 Introduction to Programming (QA) (QR)
- COMP2102 Programming II and Introduction to Computer Science
- MATH2101 Linear Algebra (QA) (QR)
- MATH2113 Statistics with R (QA) (QR)
- COMP2201 Data Analytics
- PHIL2205 Ethics and Technology (ER)
- MATH3XXX Databases
- MATH4XXX Advanced Statistics
Internship (Complete one of the following):
- MATH3XXX Internship in Data Science
- MATH4194 Research Internship I
Depth elective: (Choose one of the following):
- MATH3103 Probability
- COMP3104 Algorithms
General electives: (Choose 3 of the following):
- MATH2103 Calculus III (QA) (QR)
- MATH2109 Introduction to Proofs (QA) (QR) (WI)
- MATH2111 Mathematical Modeling for Social Justice (QA) (QR) (SJ)
- MATH2115 Modeling and Simulation with MATLAB (QA) (QR)
- MATH3XXX Statistical Analysis in SAS
- COMP2103 Data Structures
- COMP2132 Practical Machine Learning
- COMP2121 Software Development
- MGMT2310 Business Analytics
- MKTG3112 Marketing Analytics
- MKTG3110 Marketing Research: An Applied Approach
- ART2132 Data Visualization (VCI)
- Demonstrate robust understanding of the theory, application, interpretation, and limitations of statistical data analysis techniques
- Create well-designed code for data retrieval and analysis in multiple programming languages (e.g. R, SQL, Python, SAS, Javascript)
- Effectively meet the challenges of dealing with real-world datasets, including data mining, data cleaning, and interfacing with databases
- Communicate findings from data analysis to a variety of audiences
- Demonstrate understanding of the ethical challenges and social responsibilities in handling real-world data
- Demonstrate advanced proficiency in either: The probabilistic basis of statistical theory (if taking MATH 3103), or Design and analysis of computationally efficient algorithms (if taking COMP 3104)
What can I do with a degree in data science?
- Data Scientist - Use statistical modeling, machine learning, and programming to analyze complex data and provide strategic insights for businesses, healthcare organizations, tech companies, and more.
- Data Analyst - Examine datasets to identify trends, create reports, and support decision-making across industries like finance, marketing, education, and public policy.
- Machine Learning Engineer - Design and build intelligent systems that learn from data—powering everything from recommendation engines to self-driving cars.
- Data Engineer - Develop the infrastructure and tools that collect, store, and process large-scale data, making it usable for analysis and decision-making.
- Business Intelligence Analyst - Translate data into dashboards and visual reports to help organizations monitor performance and identify growth opportunities.
- Marketing Analyst - Use data to track consumer behavior, evaluate campaign effectiveness, and optimize marketing strategies.
- Healthcare Data Analyst - Work with hospitals, clinics, or public health agencies to analyze patient outcomes, optimize operations, or track disease trends.
- Quantitative Researcher - Apply mathematical and statistical techniques to develop models and forecasts in finance, economics, and other research-intensive fields.
- Ethics & Policy Advisor for Data Use - Help organizations develop responsible, equitable, and compliant practices for collecting and using data, especially in fields like AI, privacy, and social justice.
- Statistical Analysis - Understanding how to interpret data patterns, test hypotheses, and draw meaningful conclusions using statistical methods.
- Programming Languages - Writing efficient code in languages like Python, R, SQL, SAS, and JavaScript to collect, clean, and analyze data.
- Machine Learning & AI - Designing algorithms that can learn from data and make predictions—essential for roles in tech, finance, and healthcare.
- Data Visualization - Turning complex data into compelling charts, dashboards, and interactive visuals that help others understand the story behind the numbers.
- Database Management - Organizing and managing large datasets using tools like SQL and database systems, making information accessible and secure.
- Communication Skills - Explaining your data findings clearly to both technical and non-technical audiences—because insight is only powerful if people understand it.
- Ethical Reasoning - Navigating questions about privacy, bias, and fairness in data collection and analysis—especially important in today’s AI-driven world.
- Critical Thinking - Asking the right questions, challenging assumptions, and applying logic to solve complex, real-world problems.
Where Essential Values and Skills Meet the Real World
Along with areas of knowledge and major requirements, you will cultivate essential values in the classroom and complete two courses in each area:
- Social Justice (SJ): Develop knowledge, skills, values and motivation to participate beneficially in activities of personal and public concern.
- Diversity & Multiculturalism (DM): Understand the complexity of identity the historical truths of different cultural perspectives to address bias and examine contemporary social issues.

One hundred percent of Emmanuel students complete an internship as part of the core curriculum. In a city as dynamic as Boston, your options are bound only by the limits of your curiosity.
As a Data Science major at Emmanuel, you'll complete a professional internship that puts your skills to the test—and sets you up for success after graduation. Whether you're analyzing patient outcomes at a healthcare startup, building dashboards for a marketing agency, supporting data strategy at a nonprofit, or working on predictive models at a tech company, Boston’s innovation ecosystem offers countless opportunities to get hands-on with data. You'll sharpen your technical and professional skills, explore your career interests, and build a portfolio-worthy project that makes your resume stand out.

In all majors, the Capstone Experience involves completing a significant piece of work that requires the integration and application of learning from multiple courses.
In your final semester, you’ll take on a capstone course in advanced statistics—where you’ll explore real-world data and put your skills to the test. You’ll learn how to use R (a leading tool in data science) to analyze patterns and relationships in data using methods like regression, comparison testing, and other advanced techniques. Then, you’ll choose your own dataset, conduct a full analysis, and share your findings through a professional-style paper and presentation. It’s a hands-on, high-level project that helps you prove what you’ve learned—and show the world what you can do.

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