M.S. in Data Science & Analytics

2 Years On Campus Masters Program

Georgetown University

Program Overview

The Master of Science in Data Science & Analytics (MS DSAN) at Georgetown University is designed to equip students with the technical, analytical, and problem-solving skills needed to succeed in the rapidly growing data science industry. The program combines statistical modeling, programming, machine learning, artificial intelligence, and big data technologies, allowing students to specialize in areas such as AI, Natural Language Processing, Financial Analytics, and Data Visualization.

Curriculum Structure

First Year: Students develop a strong foundation in data science through core courses covering statistical methods, programming, data analysis, and visualization. They study Data Science and Analytics (DSAN 5000), Probabilistic Modeling and Statistical Computing (DSAN 5100), and Advanced Data Visualization (DSAN 5200) to learn how to collect, process, interpret, and communicate complex datasets. Students also explore Statistical Learning (DSAN 5300) to understand predictive modeling, supervised and unsupervised learning, and machine learning techniques.

Second Year: Students advance their technical expertise through Big Data and Cloud Computing (DSAN 6000) and specialized electives aligned with their selected concentration. They can explore subjects such as Neural Nets and Deep Learning (DSAN 6600), Reinforcement Learning (DSAN 6650), and Computational Linguistics (DSAN 5400) while developing practical skills through real-world datasets and research opportunities. Students complete the remaining elective credits and can participate in internships, faculty-led research, and applied data science projects.

Focus Areas: Artificial Intelligence, Natural Language Processing, Data Visualization and Communication, Financial Analytics, Generalist Data Science, Machine Learning, Deep Learning, Big Data, Cloud Computing, Statistical Modeling, Data Ethics and Policy.

Learning Outcomes: Develop advanced programming and statistical analysis skills, apply machine learning and artificial intelligence techniques, build predictive models, process and interpret large datasets, create effective data visualizations, understand cloud computing technologies, and communicate data-driven insights to solve real-world business and research challenges.

Professional Alignment (Accreditation): The program is offered through Georgetown University's Graduate School of Arts and Sciences and provides a STEM-designated curriculum in Computational Science (CIP code 30.3001). Its interdisciplinary coursework, practical projects, research opportunities, and optional internships prepare students for professional careers across technology, finance, consulting, healthcare, and public policy. International graduates may be eligible for the 24-month STEM OPT extension, subject to applicable immigration requirements.

Reputation (Employability Rankings): Georgetown University provides strong industry exposure through its location in Washington, D.C., faculty connections, research opportunities, and engagement with technology organizations. The university reports that Data Science & Analytics graduates have secured positions at leading organizations, including Amazon, Google, IBM, Deloitte, MITRE, and Sony Pictures. Graduates pursue career opportunities as Data Scientists, Machine Learning Engineers, Software Engineers, Data Analysts, Consultants, and Developers

Experiential Learning (Research, Projects, Internships etc.)

At Georgetown University, the M.S. in Data Science & Analytics program is designed to provide students with hands-on experience that translates theoretical knowledge into practical skills. The program emphasizes experiential learning through various opportunities, including collaborative projects, internships, and access to cutting-edge technology and facilities. Students engage in real-world data challenges, allowing them to apply their learning in meaningful ways while building a robust portfolio.

Here are some key aspects of the experiential learning opportunities available in the program:

- Collaborative Projects: Students work in teams on data-driven projects, simulating real-world scenarios and enhancing their teamwork and problem-solving skills.
- Internships: The program encourages internships with industry partners, providing students with invaluable experience and networking opportunities in the field of data science.
- Access to Software Tools: Students gain proficiency in essential data science tools and programming languages, including Python, R, SQL, and Tableau, which are integral to data analysis and visualization.
- Research Laboratories: Georgetown offers dedicated research labs equipped with advanced technology, allowing students to conduct experiments and analyze data in a supportive environment.
- Data Science Institute: The university's Data Science Institute fosters collaboration between students and faculty, promoting innovative research and practical applications of data science.
- Field Trips: Students have opportunities to visit local tech companies and organizations, gaining insights into industry practices and trends.
- Libraries and Resources: The university's libraries provide access to a wealth of academic resources, databases, and research materials that support students' learning and projects.

Progression & Future Opportunities

Georgetown University's M.S. in Data Science & Analytics equips graduates with the skills and knowledge to excel in a rapidly evolving field. Alumni have successfully transitioned into roles such as Data Scientist, Business Intelligence Analyst, and Machine Learning Engineer. The program not only prepares you for immediate employment but also lays a strong foundation for long-term career growth:

- Career Services: Georgetown offers dedicated career services, including resume workshops, interview preparation, and networking events tailored specifically for data science students.
- Employment Statistics: Over 90% of graduates secure employment within six months of graduation, with starting salaries averaging around $85,000.
- University–Industry Partnerships: The program has established partnerships with leading companies like Deloitte, Amazon, and Booz Allen Hamilton, providing students with internship opportunities and real-world project experience.
- Accreditation Value: The program is accredited by the Middle States Commission on Higher Education, ensuring that your degree holds significant value in the job market.
- Graduation Outcomes: Graduates have gone on to work at top-tier firms and have reported high job satisfaction and career advancement opportunities.

Further Academic Progression: After completing the M.S. in Data Science & Analytics, you may choose to pursue a Ph.D. in a related field, such as Computer Science or Information Systems, which can open doors to academic positions or advanced research roles. Additionally, you could consider specialized certifications in areas like machine learning or artificial intelligence to further enhance your expertise and marketability.