Program Overview
- Location: Charleston, SC
- Length: 2 Years
- Tuition: $24,000
- Website: https://charleston.edu/academics/programs/graduate-studies/data-science-and-analytics.php
The College of Charleston offers a Master of Science in Data Science and Analytics, marking the first program of its kind in South Carolina and representing the nation’s 13th oldest institution. The program is designed for individuals seeking expertise in artificial intelligence, machine learning, business intelligence, and specialized fields including national security, genomics, drug informatics, and biomedical informatics.
Students benefit from an outstanding faculty-to-student ratio ensuring personalized learning and excellent mentorship opportunities. The program operates on-campus with access to cutting-edge research opportunities, world-class faculty, and state-of-the-art research labs.
Program Duration and Credit Requirements
The Master of Science in Data Science and Analytics requires 30 credit hours for completion with two distinct pathways:
- Core requirements: 18 credits covering essential areas including database management, data cleaning and visualization, machine learning and data mining, linear models, and scientific computing
- Practicum Option: 6 credits of hands-on industry experience plus 6 credits of specialized electives
- Thesis Option: 6 credits of traditional research culminating in a comprehensive thesis plus 6 credits of electives
- Admission timing: Fall semester only with priority deadline February 1 and final deadline July 1
- Program duration: Typically 1.5-2 years depending on course load and chosen completion pathway
Prerequisites
Academic Background: Open to students from various fields.
Prerequisite Competencies:
- Statistics, linear algebra, calculus, and programming
- Preferred grade: B- or higher in each area
Application Materials:
- 300–500-word statement of purpose
- Two letters of recommendation
- Official transcripts from all institutions
- Current résumé
Work Experience: Relevant professional experience may substitute for some prerequisites.
Machine Learning Focus and Career Outcomes
The program explicitly emphasizes machine learning through required core coursework including “Machine Learning, Data Mining, and Analytics” (DATA 534) and advanced statistical learning options.
Students develop hands-on expertise in:
- Data modeling and wrangling
- Experimental design and statistics
- Optimization and machine learning
- Data visualization
The program offers elective tracks tailored to specific careers:
- Business Analytics Data Scientist
- Machine Learning Data Scientist
- Modeling & Software Engineering Data Scientist
- Computational Data Scientist
- Scientific Computing Specialist
Industry partnerships with major companies including Boeing, Volvo, Booz Allen Hamilton, and Mercedes-Benz Vans provide unique research and employment connections.
Curriculum
Corse coursework includes these classes:
CSIS 638 Implementation of Database Management Systems (3) – This advanced database course covers query processing algorithms, optimization techniques, physical database design, and transaction management. Students learn concurrency control, backup and recovery methods, distributed database systems, and multidimensional data handling using Datalog for recursive queries. Additional topics include multimedia databases, object-relational systems, data warehousing, and data mining techniques.
DATA 510 Data Cleaning, Organization, and Visualization (3) – Students master essential data preparation skills including cleaning, wrangling, organizing, and querying large datasets and streaming data. The course emphasizes practical strategies for handling big data challenges and creating effective visualizations to communicate insights from complex data sources.
DATA 531 Database Concepts (3) – This foundational course introduces core database principles with emphasis on the relational model. Students explore data models, query languages, relational design using normalization, database programming, and security considerations. Hands-on experience includes working with relational database management systems and SQL programming.
DATA 534 Machine Learning, Data Mining, and Analytics (3) – Students implement and apply cutting-edge machine learning algorithms for knowledge discovery from data. The course covers fundamental concepts and advanced methods in machine learning, analytics, and data mining, providing practical experience with state-of-the-art algorithms used in industry and research.
MATH 550 Linear Models (3) – This theory-focused course provides comprehensive coverage of linear models for data analysis using vector space concepts and projections. Topics include analysis of variance, regression models, Bayesian estimation, hypothesis testing, experimental design, and advanced concepts like variance component estimation and balanced incomplete block designs.
DATA 507 Scientific Computing in Data Science (3) – Students learn to apply scientific methodology to data science challenges including incomplete data handling, temporal analysis, bias correction, and outlier detection. The course covers experimental design, signal processing, time-dependent modeling, ensemble methods, statistical image analysis, and scientific numerical techniques for rigorous data analysis.
MATH 540 Statistical Learning I (3) – This advanced statistics course introduces modern statistical learning approaches including empirical processes, classification algorithms, clustering techniques, and nonparametric methods. Students explore density estimation, regression analysis, model selection procedures, adaptive algorithms, bootstrapping, and cross-validation for robust statistical inference.
In addition there is a wide range of Practicum and Thesis options to choose from.
More curriculum details can be found here: https://catalog.cofc.edu/preview_program.php?catoid=30&poid=6202
Tuition
Estimated total cost for the program is $23,482.50.
Cost Breakdown
Annual Costs (same for in-state and out-of-state):
- Tuition & Fees: $7,920
- Tech & Library Fees: $230
- Books & Supplies: $1,040
- Average Loan Fees: $203
- Total Annual Cost: $9,393
Total Program Cost: Since the program is 30 credit hours and the annual estimate is based on 6 credit hours per semester (12 hours per year), the program would typically take 2.5 years to complete.
Estimated Total Program Cost: $9,393 × 2.5 = $23,482.50
More tuition information here: https://charleston.edu/cost-aid/tuition-fees/index.php
Ideal Candidates
The program specifically targets professionals seeking career advancement in data-driven fields and those interested in contributing to knowledge discovery from data across multiple domains. Students benefit from access to extensive alumni networks, collaborative research opportunities in specialized labs covering cybersecurity, AI, and health informatics, and the program’s strategic location within Charleston’s growing technology sector.