Buckhead, USA
DURATION
12 up to 24 Months
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
Request application deadline *
EARLIEST START DATE
Request earliest startdate
TUITION FEES
USD 48,150 **
STUDY FORMAT
On-Campus
* round 3 | round 4: May 6,2024 | round 5: rolling
** out-of-country residents I non-georgia residents: $47,250 | georgia residents: $39,975 | non-refundable seat deposit: $250
Key Summary
Introduction
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.
Each track prepares you with the necessary skills to succeed.
Data Scientist Track - Learn to apply statistics and build algorithms using machine and deep learning behind the scenes.
- Data pre-processing including preparation and manipulation
- Model selection and testing
- Data visualization, evaluation, and interpretation
- Innovative solution ideation for business executives
Citizen Data Scientist Track - Learn to understand data, use visualization tools, and communicate insights to decision-makers.
- 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
- Confidence to leverage “data storytelling” to derive innovative solutions
How long will it take?
- Full-time format: 12 months (3 semesters). Offers a fast track into the workforce. Classes up to four days a week: Monday-Thursday, 2 p.m. and 6 p.m. sessions.
- Part-time format: 24 months (6 semesters). Allows working professionals to advance their current careers. Classes up to two evenings a week: Monday-Thursday, 6 p.m.
Admissions
Scholarships and Funding
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
Graduate research assistantships are available to offset program costs.
Loans
- Federal Direct Loans and online FAFSA application for Federal Student Aid
- Private Education Loans
Curriculum
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.
- Industry partners provide real problems with data for insights and solutions.
- Student teams work with faculty from across the entire university as well as corporate participants.
- Students get feedback during weekly meetings over a 6- to 10-week period.
- Students engage in the practical application of machine learning and predictive analytics.
Data Scientist: Full-time
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.
Fall 1
- MSA 8010 – Data Programming for Analytics
- MSA 8040 – Data Management for Analytics
- MSA 8030 – Communicating with Data
- MSA 8190 – Statistical Foundations for Analytics
Spring
- MSA 8050 – Scalable Data Analytics
- MSA 8150 – Machine Learning for Analytics
- MSA 8200 – Predictive Analytics
- MSA 8600 – Deep Learning and Generative AI
Summer
- Internship (optional)
Fall 2
- Elective 1
- Elective 2
- Elective 3
Data Scientist: Part-time
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.
Fall 1
- MSA 8010 – Data Programming for Analytics
- MSA 8040 – Data Management for Analytics
Spring 1
- MSA 8050 – Scalable Data Analytics
- Elective
Summer
- Internship (Optional)
- Elective
Fall 2
- MSA 8190 – Statistical Foundations for Analytics
- MSA 8030 – Communicating with Data
- Elective
Spring 2
- MSA 8150 – Machine Learning for Analytics
- MSA 8200 – Predictive Analytics
- MSA 8600 – Deep Learning and Generative AI
Citizen Data Scientist: Full-time
Fall 1
- IFI 8110 – Business Statistics for Analytics
- MSA 8040 – Data Management for Analytics
- IFI 8410 – Introduction to Programming & Predictive Analytics for Business
- MSA 8030 – Communicating with Data
Spring
- IFI 8450 – Scalable Data Analytics
- IFI 8420 – Machine Learning and Deep Learning for Business
- MSA 8200 – Predictive Analytics
- MSA 8600 – Deep Learning and Generative AI
Summer
- Internship (optional)
Fall 2
- Elective 1
- Elective 2
- Elective 3
Citizen Data Scientist: Part-time
Fall 1
- IFI 8410 – Introduction to Programming & Predictive Analytics for Business
- MSA 8040 – Data Management for Analytics
Spring 1
- IFI 8450 – Scalable Data Analytics
- Elective
Summer
- Internship (Optional)
- Elective
Fall 2
- IFI 8110 – Business Statistics for Analytics
- MSA 8030 – Communicating with Data
- Elective
Spring 2
- IFI 8420 – Machine Learning and Deep Learning for Business
- MSA 8200 – Predictive Analytics (3 hours) | View a sample syllabus
- MSA 8600 – Deep Learning and Generative AI (1.5 hours) | View a sample syllabus
Legal Analytics Concentration
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.
Program Outcome
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.
Program Tuition Fee
Career Opportunities
Data Scientist Career Paths
- Data Scientist –> Sr. Data Scientist –> Data Science Manager
- Data Analyst –> Analytics Innovation Lead –> Executive
- Business Analyst –> Data Analytics Associate –> Senior Consultant
Citizen Data Scientist Career Paths
- Business Intelligence Analyst –> Data Science Manager –> Executive
- E-Commerce Analytics Manager –> Director of Strategic Analytics –> Executive
- Business Analyst –> Sales Manager –> Executive