Georgia residents: $39,000
Non-Georgia residents: $45,000
Nonrefundable seat deposit: $250
Tuition is subject to change. Master of Science in Data Science and Analytics students may be required to complete prerequisite courses for an additional fee.
Where can I take classes?
Buckhead Center (200 Tower Place)
Application Deadlines View Admissions Requirements
The Robinson College of Business reviews applications by admissions rounds. The online application and all additional required materials must be submitted by the deadline to be considered for that round. Each admissions round has a decision release date. Find out when a decision is expected to be released for your program.
Students can enter the program in the fall.
Graduate Admissions
rcbgradadmissions@gsu.edu
Attend virtual office hours with one of our recruiters to get your questions answered.
Whether you are a math whiz or possess a liberal arts degree, this program will prepare you for a job in the data science field. After reviewing your application, the admissions committee will enroll you in a pathway that makes sense based on your background. Both tracks—data scientist and citizen data scientist—are STEM-designated as well as comprehensive, rigorous, and fast-paced. Through both courses of study, you will become comfortable with machine learning, deep learning, Python, and big data, and have the option to attend boot camps covering topics like SAS, Amazon Web Services, and Microsoft Azure. Both tracks also include the option to pursue a concentration in either data science or legal analytics.
| Data Scientist Learn to apply statistics and build algorithms using machine and deep learning behind-the-scenes. |
Citizen Data Scientist Learn to understand data, use visualization tools, and communicate insights to decision makers. |
|
| Curriculum | •Advanced calculus •Statistics •Artificial intelligence •Machine learning for analytics •Deep learning for analytics •Predictive analytics |
•Intro to data programming for business •Business statistics •Artificial intelligence •Machine learning for business •Deep learning for business •Predictive analytics |
| STEM-designated | Yes | Yes |
| Prospective student background | •Bachelor's degrees: STEM - science, technology, engineering, math •Knowledge in calculus I & II, multivariate calculus, statistics, linear algebra •Coding knowledge/experience preferred but not required •A minimum of 18 months’ full-time work experience recommended but not required |
•Bachelor's degrees: business, psychology, health services, political science, communications •Statistics and/or business knowledge preferred but not required •Strong communication skills are crucial, as you will be primarily communicating analytical techniques and insights. •A minimum of 18 months’ full-time work experience recommended but not required |
| Co-curriculars | •Hands-on learning with real company data in Insight Sprint projects •Boot camps to enhance technical knowledge (e.g., advanced R, blockchain, Amazon Web Services) |
•Hands-on learning with real company data in Insight Sprint projects •Boot camps to enhance technical knowledge (e.g., advanced R, blockchain, Amazon Web Services) |
| Skills you will acquire | •Data pre-processing including preparation and manipulation •Model selection and testing •Data visualization, evaluation and interpretation •Innovative solution ideation for business executives |
•Ability to bridge the gap between IT professionals and business stakeholders •Expertise in various data science tools and terminology in order to automate data preparation •Data visualization, evaluation and interpretation •Confidently leverage "data storytelling" to derive innovative solutions |
| Typical career path | Data Scientist --> Sr. Data Scientist --> Data Science Manager
Data Analyst --> Analytics Innovation Lead --> Executive Business Analyst --> Data Analytics Associate --> Senior Consultant |
Business Intelligence Analyst --> Data Science Manager --> Executive
E-Commerce Analytics Manager --> Director of Strategic Analytics --> Executive Business Analyst --> Sales Manager --> Executive |
| How to pursue this track | Admitted students will be placed in the track that best aligns with their background and goals.
If a student requests to enroll in this track, math and/or programming prerequisites may be required. |
Admitted students will be placed in the track that best aligns with their background and goals. |
Application Requirements
Learn more about the application process and what you will need to apply.
The M.S. in Data Science and Analytics program comprises three semesters in a lock-step, cohort format. However, working professionals can complete the program on a part-time basis, extend the length of the program and take courses in the summer. Full-time students also have the option of completing the program in 12 months by taking their electives in the summer.
Besides the eight required and three elective courses, students will participate in boot camps covering topics such as linear algebra, R programming, data visualization, Tableau, advanced R, big data programming and SAS.
Students will also complete Insight Sprints throughout the program.
Pre-requisite Requirements
Academic knowledge of Calculus I, II and III (Multivariate), Linear Algebra and Basic Programming are required. These courses must be completed at an accredited college or university. Coursera, Code Academy or other online, non-accredited courses do not qualify.
MSA 8010 – Data Programming for Analytics (3 hours) | View a sample syllabus
MSA 8040 – Data Management for Analytics (3 hours) | View a sample syllabus
MSA 8020 – Data Visualization (1.5 hours) | View a sample syllabus
MSA 8190 – Statistical Foundations for Analytics (3 hours) | View a sample syllabus
MSA 8050 – Scalable Data Analytics (3 hours) |View a sample syllabus
MSA 8150 – Machine Learning for Analytics (3 hours) | View a sample syllabus
MSA 8200 – Predictive Analytics (3 hours) | View a sample syllabus
MSA 8600 – Deep Learning Analytics (1.5 hours) | View a sample syllabus
Internship (optional)
Elective 1
Elective 2
Elective 3
Pre-requisite Requirements
Academic knowledge of Calculus I, II and III (Multivariate), Linear Algebra and Basic Programming are required. These courses must be completed at an accredited college or university. Coursera, Code Academy or other online, non-accredited courses do not qualify.
MSA 8010 – Data Programming for Analytics (3 hours) | View a sample syllabus
MSA 8040 – Data Management for Analytics (3 hours) | View a sample syllabus
MSA 8050 – Scalable Data Analytics (3 hours) |View a sample syllabus
Elective
Internship (Optional)
Elective
MSA 8190 – Statistical Foundations for Analytics (3 hours) | View a sample syllabus
MSA 8020 – Data Visualization (1.5 hours) | View a sample syllabus
Elective
MSA 8150 – Machine Learning for Analytics (3 hours) | View a sample syllabus
MSA 8200 – Predictive Analytics (3 hours) | View a sample syllabus
MSA 8600 – Deep Learning Analytics (1.5 hours) | View a sample syllabus
IFI 8110 – Business Statistics for Analytics (3 hours)
MSA 8040 – Data Management for Analytics (3 hours) | View a sample syllabus
IFI 8410 – Introduction to Programming & Predictive Analytics for Business (3 hours) | View a sample syllabus
MSA 8020 – Data Visualization (1.5 hours) | View a sample syllabus
IFI 8450 – Scalable Data Analytics (3 hours)
IFI 8420 – Machine Learning and Deep Learning for Business (3 hours) | View a sample syllabus
MSA 8200 – Predictive Analytics (3 hours) | View a sample syllabus
MSA 8600 – Deep Learning Analytics (1.5 hours) | View a sample syllabus
Internship (optional)
Elective 1
Elective 2
Elective 3
IFI 8410 – Introduction to Programming & Predictive Analytics for Business (3 hours) | View a sample syllabus
MSA 8040 – Data Management for Analytics (3 hours) | View a sample syllabus
IFI 8450 – Scalable Data Analytics (3 hours)
Elective
Internship (Optional)
Elective
IFI 8110 – Business Statistics for Analytics (3 hours)
MSA 8020 – Data Visualization (1.5 hours) | View a sample syllabus
Elective
IFI 8420 – Machine Learning and Deep Learning for Business (3 hours) | View a sample syllabus
MSA 8200 – Predictive Analytics (3 hours) | View a sample syllabus
MSA 8600 – Deep Learning Analytics (1.5 hours) | View a sample syllabus
As part of the legal analytics concentration, you can pursue either the data scientist or citizen data scientist track. Instead of Predictive Analytics (MSA 8200), you will take Legal Analytics (MSA 8350). For your electives, you will take Text Analytics (MSA 8770) as well as two courses at Georgia State’s College of Law.
Georgia residents: $39,000
Non-Georgia residents: $45,000
Nonrefundable seat deposit: $250
Tuition is subject to change.
Master of Science in Data Science and Analytics students may be required to complete prerequisite courses for an additional fee. Students will be informed if this is the case by the admissions committee.
Contact Graduate Student Financial Services
We are here to help you understand the cost of your program, the payment schedule and financing opportunities.
rcbfinancialaid@gsu.edu
404-413-7086
Robinson Scholarships
Robinson offers several scholarships through the Office of the Dean as well as the individual academic departments.
Search Georgia State’s Database
Georgia State offers a robust searchable database containing scholarships offered through the university as well as external websites.
Graduate research assistantships are available to offset program costs.
You will be paired with a Graduate Student Experience professional who stays on top of the extracurricular programming that will enhance your academic journey and propel your career. Activities include boot camps on topics that are relevant to your field, professional workshops, networking events, recruiting fairs, and meet-and-greets intended to create camaraderie with your peers.
The mission of the M.S. in Data Science and Analytics program is to educate students on how to acquire, organize, and model data sets in order to formulate the questions that guide decision-making in corporate and non-corporate settings.
Grace Bendinger is senior manager of clinical services and operations at Emory Healthcare. In her field, creativity and innovation have become just as important as science and technology.
Through the Innovation Studio, Bendinger built the prototype for an app that connects the components of the healthcare system. Currently, those components are fragmented and complex: making an appointment, negotiating with insurance, filling a prescription. Bendinger’s app removes those silos. The platform also helps users navigate a new diagnosis with a checklist of prioritized steps.
Bendinger is more tech savvy than the average nurse but felt apprehensive about developing an app. The class is designed to snowball concepts week by week, and makes it possible for people of all backgrounds to achieve technical competence.
Our 2021 graduates reported a 82% average salary increase, enabling them to pay back their investment in graduate school in less than one year.
Fortune Ranks Georgia State’s M.S. in Data Science and Analytics Among Top 20 U.S. Programs
Data Analytics Students Create Dashboard to Support Food Banks
Four Robinson College Specialized Master’s Among Nation’s Best in Newly Released RankingsAttend virtual office hours with one of our recruiters to get your questions answered.
Graduate Admissions
rcbgradadmissions@gsu.edu
35 Broad St NW
Atlanta, GA 30303
