Education
Master of Science in Computer Science (Online)
Georgia Institute of Technology
Anticipated Graduation: December 2026
Specialization: Machine Learning
Official Program Link: Online Master of Science in Computer Science
Bachelor of Science in Computer Science
Wayne State University, Detroit, MI
Graduation: December 2024
GPA: 3.6: View Unofficial Transcript PDF
Relevant Coursework
Completed Courses:
- Calc 1, 2, 3: Calculus Series
- Elementary Linear Algebra: Introduction to Linear Algebra
- Physics 1 & 2: Introductory Physics
- Intro to C and UNIX: Foundations in C Programming and UNIX; Memory allocation, file and directory concepts
- Problem Solving and Programming: Problem solving with algorithms, and their realization as computer programs using a structured, general-purpose programming language; data types, operators, expressions, assignment, input and output, selection and repetition control structures
- Fundamental Structures in Computer Science: Introduction to fundamental control and data structures in computer science such as algorithms and complexity; recursive algorithms; program correctness using the predicate calculus; reasoning about algorithms using mathematical induction; divide and conquer algorithms; recurrence relations; set properties and their computation; and computing with relations.
- Computer Science 1: Rigorous introduction to fundamental object-oriented concepts and techniques of computer programming using an object-oriented language. Introduction to data abstraction; design of abstract data types. Introduction to recursion; programming with generic data types; inheritance; polymorphism; and exception handlers.
- Introduction to Programming and Computation: Python: Basic control structures (sequence, selection, repetition) and all core data types using objects.
- Computer Science 2: Design and implementation of fundamental abstract data types of computer science (such as stacks, queues, trees, lists, hashing, and graphs), using an object-oriented language. Programming requirements include the implementation of abstract data types using arrays and dynamic links; recursion; sorting and searching; hashing; and string processing. Introduction to algorithm analysis.
- System Administration: Deployment and maintenance of modern computer systems in an operational environment.
- Web Technology: E-mail, FTP, Telnet, Gopher, Archie, Newsgroups, WWW, HTML, CGI and PHP scripting, and how to create an active web site. Laboratory exercises required.
- JAVA Programming: Object-oriented programming, classes, constructors, flow control statements, data types, methods, inheritance, data hiding, abstraction, exceptions, file I/O, Java GUI, and Java packages.
- Computer Operating Systems: Introduction to operating system concepts such as process management, memory management, file systems, and I/O systems.
- Introduction to Theoretical Computer Science: Study of formal languages, automata theory, computability, and complexity.
- Computer Architecture and Organization: Topics include digital logic and digital systems; machine-level representation of data and programs; assembly-level machine organization and programming; register-level description of computer execution and the functional organization of a computer; role and function of programming languages, libraries, and operating systems; performance evaluation; systems programming.
- Introduction to Database Management Systems: Database concepts, ER modeling, schemas and constraints, SQL and relational algebra, web-based database applications, triggers and views, physical organization and indexing, query processing, query optimization, NoSQL databases.
- Algorithm Design and Analysis: Formal techniques to support design and analysis of algorithms: underlying mathematical theory and practical considerations of efficiency.
- Software Engineering: Software life cycle; software requirement analysis; software system design; software implementation and testing; software maintenance; team programming; ethics and programmers.
- Ethics in Computer Science: Learn the responsibilities of computer professionals and how to make appropriate decisions when faced with legal and ethical issues in computing.
- Senior Capstone Project: Culminating project integrating knowledge and skills from the undergraduate program.
- Secure Machine Learning: Study of security and privacy issues in machine learning, including adversarial attacks and defenses.
- Computer Vision: Introduction to computer vision, including image processing, feature detection, object recognition, and deep learning techniques.