Data Science

The Master of Science in Data Science at Emory University is a comprehensive and innovative program designed to equip students with the essential skills and knowledge necessary to excel in the rapidly evolving field of data science. This interdisciplinary degree combines coursework in statistics, computer science, and domain-specific applications, offering a rigorous curriculum that emphasizes both theoretical foundations and practical skills. Students will learn to collect, analyze, and interpret complex data sets, develop predictive models, and utilize cutting-edge tools and techniques to solve real-world problems across various sectors such as healthcare, business, government, and technology.

Throughout the program, students are exposed to a variety of topics including machine learning, data visualization, database management, programming languages such as Python and R, and ethical considerations in data science. The curriculum encourages experiential learning through hands-on projects, collaboration with industry partners, and research opportunities, enabling students to apply their knowledge to challenges faced by organizations today. Emory University also provides access to state-of-the-art laboratories and computing resources, fostering an environment of innovation and scholarly inquiry.

Additionally, the program is designed to prepare graduates for diverse career paths, including data analyst, data engineer, machine learning engineer, and research scientist. Emory’s strong connections with the Atlanta business community and beyond facilitate internships and networking opportunities, helping students to build professional relationships and gain practical experience. The program emphasizes not only technical competence but also ethical responsibility in data handling, ensuring graduates are well-rounded professionals committed to integrity and societal impact in data science. Whether students aim to advance their careers or pursue further academic research, the Emory Master of Science in Data Science provides a solid foundation for success in the dynamic and expanding field of data science.

Students are required to take the following 4 core courses:

• CS 526: Algorithms
• CS 534: Machine Learning
• CS 551: Systems Programming
• CS 554: Database Systems

In addition, students are required to take at least 3 concentration electives from:

• CS 557: Artificial Intelligence
• CS 562: Advanced Computer Systems
• CS 563: Digital Image Processing
• CS 570: Data Mining
• CS 571: Natural Language Processing
• CS 572: Information Retrieval
• CS 573: Data Privacy and Security
• BIOS 506: Statistical Methods (4)
• BIOS 510: Probability Theory (4)

Students are required to choose one of the following options:

• Thesis:
  An acceptable masters thesis and oral defense (9 credit hours).
• Project:Completion of one approved elective course, and a faculty supervised project, formally taken by registering for CS598 (for up to 6 credit hours).  The project may be external as long as it is approved and co-advised by the faculty advisor. The project result may be in the form of a report or documented software.  Satisfactory completion of the project requires approval by the faculty advisor.
• Coursework:
  Completion of 9 additional electives hours.  Courses outside the department (e.g., from the sciences, schools of medicine and public health, or the business schools) may be taken if they coincide with the degree objective of the student.  Approval of electives will be by the Computer Science Committee.

Students may substitute at most one of the above electives with a relevant course from Mathematics, Computer Science, Biology, Chemistry, Physics, Biomedical Informatics, the Rollins School of Public Health, School of Medicine, and appropriate schools at Georgia Tech.  When substituting courses, a student must obtain prior written approval from the thesis advisor and CSI/BMI DGS/program director(s). Students must complete their core courses with a grade of B or higher and complete all coursework by year two with a GPA of 3.0 or higher.

• Transcripts: We will need copies of transcripts from each post-secondary institution you have attended, including your current one. They must be in English. and issued by the registrar's at your university. We do not  require official transcripts (issued by the registrar's at your university) as part of the application process, only if and when you are offered and accept admission.
• GRE scores: We will need your official GRE general exam score to be sent to us (institution code 5187). 
• Statement of purpose: Write candidly about why you want to pursue a Ph.D. in computer science and informatics, what kind of questions you have worked on in the past, what you intend to focus on in your studies and how you plan to use the research experience in your longer-term plan. 
• Curriculum Vitae: Provide a document listing relevant experiences and accomplishments, such as internships, awards and research experiences, that you believe will strengthen your application.
• Recommendation letters; We require three professionals with knowledge about your academic performance to write letters that evaluate your research potential and your teaching experience. Your application cannot be processed before we have received these letters.
• Application fee: The application fee is waived ($0) before October 31 (midnight PST). Starting November 1, the application fee is $75. 
• International applicants whose native language is not English must also complete the Test of English as a Foreign Language (TOEFL).

Scholarships

In the M.S. programs, partial tuition scholarships are available on a competitive basis. There are no teaching assistantships available for those programs. 

The Data Science program at Emory University is designed to prepare students for careers in analyzing and interpreting complex data to inform decision-making across various sectors. The curriculum combines coursework in computer science, statistics, and domain-specific knowledge to equip students with the essential skills in data collection, analysis, visualization, and reporting. Emory's program emphasizes practical experience through projects, internships, and collaboration with industry partners, allowing students to apply theoretical concepts to real-world challenges. The program often includes training in programming languages such as Python and R, data management techniques, machine learning algorithms, and ethical considerations in data usage. Students benefit from access to state-of-the-art laboratories, computing resources, and a faculty renowned for research in data science and related fields. The program aims to produce graduates who are proficient in handling large datasets, developing predictive models, and communicating insights effectively to stakeholders. Emory University also fosters interdisciplinary learning by integrating data science with health sciences, business, and social sciences, reflecting the university's broad research interests and industry needs. Graduates of the program are well-prepared for careers in technology, healthcare, finance, consulting, and academia. The degree may be offered at the undergraduate, master's, or doctoral level, providing entry points for diverse student backgrounds and career paths. Emory continuously updates its curriculum to include emerging trends and technologies in data science, ensuring that students are well-versed in current best practices and innovative techniques. The program may also offer opportunities for study abroad, research assistantships, and participation in conferences and seminars. Overall, Emory's Data Science program aims to produce highly capable professionals who can leverage data to solve complex problems and contribute meaningfully to their fields.