The College of Charleston M.S. in Data Science and Analytics is a strong fit for this directory because machine learning is built directly into the degree. The 30-credit program combines computer science, mathematics, statistics, data management, and applied analytics. The university specifically identifies artificial intelligence and machine learning among the areas students can study.
Students complete required work in machine learning and data mining while building broader skills in data cleaning, visualization, scientific computing, databases, and statistical modeling. The program is offered in Charleston, South Carolina, and provides both applied and research-oriented ways to complete the degree.
College of Charleston Data Science Program Overview
| Degree | M.S. in Data Science and Analytics |
| Credits | 30 |
| Format | Campus-based |
| Location | Charleston, South Carolina |
| Machine learning | Required coursework |
| Completion options | Practicum or thesis |
| Admission | Fall entry |
The College of Charleston describes the program as preparation for data-intensive work in areas such as business intelligence, national security, genomics, drug informatics, and biomedical informatics. Students also have access to research opportunities and connections with Charleston-area employers.
View the official M.S. in Data Science and Analytics program page.
Machine Learning and AI Focus
This degree has a clear machine learning component rather than treating AI as a small elective topic. DATA 534 Machine Learning, Data Mining, and Analytics is part of the curriculum. Students learn methods for extracting useful information from data and applying machine learning and data mining techniques to analytical problems.
The wider curriculum supports that work with training in programming, databases, statistical modeling, data preparation, visualization, and scientific computing. This mix can be useful for students who want machine learning skills but also want the broader data science foundation needed to prepare data, evaluate models, and communicate results.
Curriculum
The M.S. requires 30 graduate credits. Core and related coursework includes subjects such as:
- Machine Learning, Data Mining, and Analytics
- Data Cleaning, Organization, and Visualization
- Scientific Computing in Data Science
- Linear Models
- Database and computing coursework
- Statistical learning options
Students can finish the degree through a practicum or a research thesis. The practicum route gives students a more applied experience, while the thesis route is better suited to students who want to complete a larger research project or may be considering doctoral study.
Review the College of Charleston graduate catalog for current course and degree requirements.
Admissions
The program accepts applicants from different academic backgrounds, but students need quantitative and programming preparation. College of Charleston lists competency in statistics, linear algebra, calculus, and computer programming among its admission criteria. Relevant prerequisite coursework should generally have a grade of B- or better.
The current program page lists February 1 as the priority deadline and July 1 as the final deadline for fall admission. The university states that new students enter this program in the fall.
Applicants should verify deadlines and required materials directly with the university before applying because graduate admission requirements can change.
Tuition and Cost
College of Charleston lists 2026-27 graduate tuition of $7,920 for an academic year based on 12 credits, or an implied base tuition rate of about $660 per credit. At that rate, 30 credits would equal approximately $19,800 in base tuition before required fees, books, supplies, and other expenses.
The university currently lists the same graduate tuition amount for resident and nonresident students in its published cost-of-attendance figures. Actual program cost depends on enrollment pattern and future tuition rates.
See current College of Charleston graduate tuition and fees.
Career Preparation
The degree can support careers in data science, machine learning, analytics, data engineering, and related technical fields. College of Charleston highlights industry relationships with employers including Boeing, Volvo, Booz Allen Hamilton, and Mercedes-Benz Vans.
The program also has evidence of current AI-focused student work. A 2026 graduate profiled by the university used his graduate studies to work on data systems, automation, artificial intelligence, and machine learning systems. That type of applied work reinforces the program’s relevance for students interested in modern AI and data science careers.
Who Is This Program Best For?
College of Charleston is worth considering if you want a data science master’s with a meaningful machine learning component and prefer an interdisciplinary curriculum instead of a narrowly focused AI degree. It may be especially appealing to students who want to combine computing and statistics with an applied practicum or research thesis.
Applicants without a strong quantitative background should pay close attention to the prerequisite expectations. Students who already have experience with programming, calculus, linear algebra, and statistics should be better positioned for the graduate curriculum.