MS Cybersecurity Assurance Courses

MSDS 510 Computer Programming Foundations for Data Science

3 credit hours

Introduction to computer programming for data science using Python, R, and SAS.

• Introduction to Python. Python syntax to write basic computer programs; Using the interpreter; Built-in and user-defined functions; Introduction to object-oriented programming in Python.
• Introduction to R. Simple graphing; R Basics: variables, strings, vectors; Data Structures: arrays, matrices, lists, dataframes; Programming Fundamentals: conditions and loops, functions, objects and classes, debugging.
• Introduction to SAS Programming. The SAS Operating Environment; SAS Programming Essentials: SAS Program Structure, SAS Program Syntax; Getting Data In and Out of SAS; Printing and Displaying Data; Introduction to SAS Graphics.

There are no pre-requisites for this course. Students are expected to have a working familiarity with the discipline of data science and analytics and general knowledge about the impacts of Big Data in businesses and corporations. All students should have a working knowledge of all aspects of Microsoft Office; and it goes without saying that they should be familiar with Internet access and usage.

MSDS 515 Data Consciousness

3 credit hours

Using Excel, JavaScript, Python, SAS, SQL, and R to develop Data Conscientiousness: ability to immediately recognize the issues involved in data organization that will need to be addressed to tackle a specific problem. Developing skills in all of the preprocessing, scrubbing, cleaning tools (“search and rescue” operations), data imputation and handling of missing values, checking for adherence to data standards, and all of the rest of the time-consuming and dirty work of data projects. Linking structured and unstructured data sources and recognizing how to reshape data to get it into a computer-friendly format (i.e., rows and columns) required by analytical and statistical methods. A gentle introduction to statistics to enable understanding of the statistical difference between observations and variables, along with knowledge of the different scales of measurement so as not to end up with nonsensical analytical results.

There are no pre-requisites for this course. Students are expected to have a working familiarity with the discipline of data science and analytics and general knowledge about the impacts of Big Data in businesses and corporations. All students should have a working knowledge of all aspects of Microsoft Office; and it goes without saying that they should be familiar with Internet access and usage.

MSDS 520 Math and Statistical Foundations for Data Science

3 credit hours

Techniques for building and interpreting mathematical models of real-world phenomena in and across multiple disciplines, including linear algebra, discrete mathematics, probability, and calculus, with an emphasis on applications in data science and data engineering. Introduction to statistical methods that are used to solve data problems. Topics include sampling and experimental design, group comparisons, parametric statistical models, multivariate data visualization, multiple linear regression, and classification. Students will obtain hands on experience in implementing a range of commonly used statistical methods on numerous real-world datasets.

MSCA 525 Introduction to Cybersecurity

3 credit hours

This course introduces the fundamental principles and practices of cybersecurity. It covers the key concepts, terminologies, and technologies essential for protecting information systems against various types of cyber threats. Students will be introduced to security policies, risk management, cryptography, and the importance of ethical considerations in cybersecurity.

MSDS 545 Introduction to Computational Software Engineering

3 credit hours

This course provides an introduction to systems development for computational science. Students will learn to design, develop, and deploy a set of software components that produce a scalable, reliable, and reproducible experimental system for scientific investigation. Additionally, students will explore a variety of approaches to software development team organization and learn to select techniques that are appropriate for different circumstances.

MSCA 550 Digital Forensics and Ethical Hacking

3 credit hours

This course provides an in-depth exploration of digital forensics and ethical hacking, equipping students with the knowledge and skills necessary to investigate and respond to cyber incidents. The course covers the legal and ethical implications of cybersecurity, techniques for collecting and analyzing digital evidence, and methods for identifying, exploiting, and mitigating vulnerabilities in computer systems

MSCA 560 Distributed Systems and Network Security

3 credit hours

This course explores the principles, technologies, and practices involved in securing distributed systems and networks. Students will learn about the security challenges inherent in distributed computing environments, including cloud computing, peer-to-peer networks, and large-scale networked systems. The course covers topics such as cryptography, access control, network security protocols, intrusion detection, and emerging threats in distributed systems.

MSCS 565 Advanced Computer Systems

3 credit hours

This course offers an in-depth exploration of modern computer systems, focusing on advanced topics in computer architecture, operating systems, networking, and quantum computing. The course begins with a review of foundational computer systems concepts and progresses to advanced pipelining, superscalar architectures, distributed computing, and system-level design. Students will engage with cutting-edge topics such as Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and the principles and challenges of quantum computing. Through a combination of theoretical instruction and practical assignments, students will develop a comprehensive understanding of advanced computer systems and their applications in real-world scenarios.

MSDS 655 AI in Cybersecurity

3 credit hours.

What is artificial intelligence (AI)? What does it mean for cybersecurity? And how AI can be integrated to achieve the goals of cybersecurity? This course designed to answer the above questions. In this course, a mix of key AI technologies will be introduced to support the understanding of the decision-making process when cybersecurity is concerned. The course will address key AI technologies in an attempt to help in understanding their role in cybersecurity. AI deficiently will complement and strengthen the cybersecurity practices and will improve their applications in enhancing our security.

MSCS 575 High Performance Computing

3 credit hours

This course provides a comprehensive introduction to high-performance computing (HPC) and its applications in various fields. Students will explore the fundamental concepts of HPC, including distributed and parallel computing, HPC architecture, and operating systems. The course covers key optimization techniques, libraries and tools essential for developing and managing HPC systems. Additionally, students will gain insights into specialized topics such as system on chip (SoC) design, neuromorphic computing, and CUDA programming. Through hands-on projects and practical exercises, students will learn to harness the power of HPC for solving complex computational problems.

MSDS 575 Ethics in Data Science

3 credit hours

Analysis of ethical issues, algorithmic challenges, and policy decisions (and social implications of these decisions) that arise when addressing real-world problems through the lens of data science, and the choices we make at the different stages of the data analysis pipeline, from data collection and storage to understand feedback loops in analysis.

MSDS 700 Fundamentals of Database Management Systems

3 credit hours.

Introduction to database concepts and the relational database model. Topics include ER Model, Relational Model, Relational Algebra, SQL, normalization, Indexing, Normal Forms, design methodology, DBMS functions, Security, Transaction Management, data-base administration, and other database management approaches such as client/server databases, object-oriented databases, and data warehouses. Strong emphasis on database system design and application development.

MSDS 740 Big Data Privacy and Security

3 credit hours

Security issues related to the safeguarding of sensitive personal and corporate information against inadvertent disclosure; Policy and societal questions concerning the value of security and privacy regulations, the real world effects of data breaches on individuals and businesses, and the balancing of interests among individuals, government, and enterprises; Current and proposed laws and regulations that govern information security and privacy; Private sector regulatory efforts and self-help measures; Emerging technologies that may affect security and privacy concerns; and Issues related to the development of enterprise data security programs, policies, and procedures that take into account the requirements of all relevant constituencies; e.g., technical, business, and legal.

MSDS 590 Capstone

3 credit hours

Comprehensive real-life industry-type capstone, oriented toward the student’s domain of interest. Projects will include: formulation of a question to be answered by the data; collection, cleaning and processing of data; choosing and applying a suitable model and/or analytic method to the problem; and communicating the results to a non-technical audience.

Potential Research projects

Build on your classroom experience with hands-on research projects where you can address an industry-like problem. Possible projects include:

• Resilient Smart City Sensor Network Security Architecture
• Insider Threat Detection Through User Behavior Analytics
• Blockchain-Based Identity Management System
• AI-Driven Malware and Ransomware Detection and Analysis
• Privacy-Preserving Data Collection in IoT Healthcare Devices
• AI for Predictive Cybersecurity
• Differential Privacy and Federated Learning
• Post-Quantum Cryptography

Career opportunities with an M.S. in Cybersecurity Assurance

Our program will help prepare you for a career in cybersecurity, a field that the U.S. Bureau of Labor Statistics forecasts will see a 32 percent increase in jobs from 2022 to 2032. Potential future roles include:

• Cybersecurity analysts
• Cybersecurity engineer
• Cybersecurity Director
• Digital Forensics Investigator
• Information Security Manager
• Network security engineers
• Security Architect

All other applicants should meet the following requirements:

• Educational equivalent of at least a bachelor’s degree from a regionally accredited university in the U.S.
• Students are expected to have a working familiarity with the discipline of data science and analytics and general knowledge about the impacts of big data in businesses and corporations. All students should have a working knowledge of all aspects of Microsoft Office; and should be familiar with Internet access and usage.
• Grade Point Average (GPA) of 2.75 on undergraduate work with a minimum of a “B” (GPA of 3.00) in undergraduate Calculus, Elementary Statistics, or their equivalents.

If you meet one of the above requirements, you may begin the admissions process.

Application timeline

Applicants can apply to begin our programs in the Fall Semester, starting in August. While we accept students on a rolling basis, the following dates serve as application deadlines the semester. Please contact the Office of Enrollment Management about applying after these deadlines.

Fall 2026 priority application deadline

May 30, 2026: Priority deadline for application. All materials outlined in Step 2 of the applicant process are due by June 13, 2026.

Each applicant must complete the following:

Step 1

Complete an application.

That application will include the following:

• Two references: one professional and one academic (or both academic if prospective student has no employment experience).
• Personal statement: The School of Applied Computational Sciences (SACS) wants to know (1) your personal and career goals, and (2) how the graduate program will contribute to the achievement of your goals via the personal statement form.

Step 2

• Official transcripts: Please ask your institution to send official transcripts directly to the Office of Enrollment Management. We prefer to receive an electronic transcript and the institution can email it to sacsenrollment@mmc.edu.If the institution prefers to mail transcripts, please use this address:
  Office of Enrollment Management, School of Applied Computational Sciences,
  Meharry Medical College,
  3401 West End Avenue
  Suite 260
  Nashville, TN 37203(Must have an undergraduate degree with at least a GPA of 2.75 or better for full admission. Applicants with a GPA of less than 3.00 in calculus and elementary statistics, including linear algebra, may be admitted conditionally and must obtain a minimum of 3.00 GPA by the end of the first 3 courses or 9 credit hours.)
• CV: Submit an electronic CV to sacsenrollment@mmc.edu.
• Applicants must submit documentation verifying coursework or demonstrated competency in data science or computing and technology concepts and terminology, statistics, data management, and computer programming.
• GRE test scores are not required at this time.

Step 3

On-campus (or virtual) interview with the School’s Admissions Committee.

Additional Requirements for International Applicants

International applicants must hold a degree comparable to a regionally accredited US baccalaureate or master’s degree. Applicants submitting transcripts from international colleges and universities are required to have them verified for US degree program equivalency before being considered for admission. Verification from the following organizations is acceptable:

• International Education Services (IES)
• World Education Services (WES)
• Global Credential Evaluators (GCE)
• Educational Credential Evaluators (ECE)

The decision of the verifying organization must be transmitted directly to Meharry Medical College in electronic form.

English proficiency

Adequate proficiency of spoken and written English is essential to success in graduate study, and medical residency training at Meharry Medical College.

Please review Meharry’s  F-1 English Language Policy and the College’s English proficiency requirements policy.

Get Prepared

Are you interested in this program but need to improve your programming, or statistics other skills? Contact us at sacsadmissions@mmc.edu or complete the request information form to learn about courses you can take to prepare you for either program.

Program Contact

Jayla Stallworth, PHR
Student Recruitment and Admissions Specialist
jayla.stallworth@mmc.edu