Data Science and Analytics, M.S.A.

12 Months On Campus Masters Program

Georgia State University

Program Overview

The Master of Science in Analytics (M.S.A.) in Data Science and Analytics at Georgia State University's Robinson College of Business prepares students to use data, artificial intelligence, and advanced analytical techniques to solve complex business and organisational problems. The programme offers two learning tracks, Data Scientist and Citizen Data Scientist, combining programming, statistical analysis, machine learning, deep learning, and generative AI with practical business applications.

Curriculum Structure

The programme follows a cohort-based structure with eight required courses and three electives, supported by practical boot camps and industry-based Insight Sprints. Students can pursue either the Data Scientist track, which focuses on building analytical and machine learning solutions, or the Citizen Data Scientist track, which emphasises interpreting data and communicating insights to business decision-makers.

Data Scientist Track

Students develop technical skills through courses such as Data Programming for Analytics, Data Management for Analytics, and Statistical Foundations for Analytics. Advanced courses include Machine Learning for Analytics, Predictive Analytics, Deep Learning and Generative AI, and Building Generative AI Business Solutions.

Citizen Data Scientist Track

This track builds analytical and business communication skills through courses such as Business Statistics for Analytics, Programming for Business, and Data Management for Analytics. Students also study Scalable Data Analytics, Machine Learning for Business, Predictive Analytics, and Deep Learning and Generative AI.

Electives and Practical Learning

Students complete three elective courses and can pursue a concentration in Data Science or Legal Analytics. The Legal Analytics concentration includes Legal Analytics and Text Analytics, along with two courses at Georgia State's College of Law. Students also participate in Insight Sprints, where they work in teams with faculty and industry partners on real-world data challenges over a six-to-ten-week period.

Focus Areas

Data Science, Data Analytics, Artificial Intelligence, Generative AI, Machine Learning, Deep Learning, Statistical Analysis, Predictive Analytics, Data Programming, Data Management, Big Data Analytics, Data Visualisation, Business Intelligence, Data Storytelling, Legal Analytics, Text Analytics, Data Engineering, Business Analytics, Decision Science, Data-Driven Business Strategy.

Learning Outcomes

Students develop the ability to collect, organise, process, and analyse complex datasets to support business and organisational decisions. They learn to apply Python programming, statistical methods, machine learning, deep learning, and generative AI techniques to real-world problems. The programme also strengthens their ability to evaluate analytical models, interpret results, communicate insights, and collaborate with business and technology professionals. Through practical Insight Sprints and optional internship opportunities, students gain experience working with industry data and developing actionable solutions.

Professional Alignment (Accreditation)

Both the Data Scientist and Citizen Data Scientist tracks are STEM-designated, making eligible international graduates potentially qualified for the 24-month STEM Optional Practical Training extension after their initial OPT period, subject to U.S. immigration requirements. The official programme page does not identify a separate professional accreditation specifically for this degree.

Reputation (Employability Rankings)

Georgia State University's Robinson College of Business reports the following programme rankings:

No. 1 in the Southeast and No. 10 in the United States – TFE Times, 2026.
No. 22 among public universities and No. 39 nationally – U.S. News & World Report, 2026.
No. 13 among public universities and No. 18 nationally – Fortune, 2025.

The university also reports 2025 graduate outcomes, including an average top-quartile salary of $116,376 and an average salary increase of 52%. These figures are university-reported outcomes and should not be interpreted as guaranteed individual salaries.

Experiential Learning (Research, Projects, Internships etc.)

At Georgia State University, the Data Science and Analytics MS program is designed to provide students with hands-on experience that is crucial for success in the rapidly evolving field of data science. Students engage in practical learning through various projects, internships, and access to state-of-the-art facilities and tools. This experiential learning approach ensures that you not only understand theoretical concepts but also apply them in real-world scenarios, preparing you for a successful career.

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

- Collaborative Projects: Work on team-based projects that simulate real-world data challenges, allowing you to collaborate with peers and apply your skills in a practical setting.

- Internship Opportunities: Gain valuable industry experience through internships with leading companies in Atlanta, a hub for technology and innovation.

- Advanced Software Tools: Utilize industry-standard software such as Python, R, SQL, and Tableau, equipping you with the technical skills employers are looking for.

- Research Laboratories: Access dedicated research labs where you can engage in cutting-edge data analysis and machine learning projects under the guidance of faculty experts.

- Data Science Institute: Benefit from the resources and networking opportunities provided by the Georgia State Data Science Institute, which connects students with industry professionals and research initiatives.

- Field Trips and Workshops: Participate in field trips to local tech companies and workshops led by industry leaders, enhancing your understanding of the data science landscape.

- Library Resources: Take advantage of extensive library resources, including access to databases and journals that are essential for your research and studies.

These experiential learning opportunities are designed to enrich your educational journey and prepare you for a successful career in data science and analytics.

Embarking on this program will not only enhance your knowledge but also provide you with the practical skills and experiences that employers value. I encourage you to apply and take the next step toward your future in data science!

Progression & Future Opportunities

The Data Science and Analytics MS program at Georgia State University equips graduates with the skills and knowledge needed to thrive in a rapidly evolving job market. Alumni of this program often find themselves in high-demand roles such as Data Analyst, Data Scientist, Business Intelligence Analyst, and Machine Learning Engineer. With a strong foundation in data-driven decision-making, graduates are well-prepared to tackle complex challenges across various industries.

Here’s how Georgia State supports your journey toward a successful career:

- Career Services: The university offers dedicated career counseling, resume workshops, and interview preparation to help you stand out in the job market.
- Employment Stats: Graduates from the Data Science and Analytics program have an impressive employment rate, with many securing positions within six months of graduation. The average starting salary for graduates is around $85,000, reflecting the high demand for skilled professionals in this field.
- University–Industry Partnerships: Georgia State has established partnerships with leading companies such as Delta Air Lines, Coca-Cola, and AT&T, providing students with internship opportunities and real-world projects that enhance their learning experience.
- Long-term Accreditation Value: The program is accredited by the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC), ensuring that your degree holds value in the job market for years to come.
- Graduation Outcomes: The program boasts a strong track record of graduates who not only find employment but also advance quickly in their careers, often moving into leadership roles within a few years.

Further Academic Progression: After completing the Data Science and Analytics MS, you may choose to further your studies by pursuing a Ph.D. in Data Science, Analytics, or a related field. This advanced degree can open doors to academic positions, research opportunities, and higher-level roles in industry, allowing you to contribute to the evolving landscape of data science and analytics. Additionally, you might consider specialized certifications in areas like machine learning or artificial intelligence to enhance your expertise and marketability.

Choosing Georgia State University for your graduate studies in Data Science and Analytics is a step toward a rewarding and impactful career.