Earning a Master of Science in Computer Science (MSCS) online from Georgia Institute of Technology (Georgia Tech) is a significant step towards advancing your tech career. The program, often referred to as OMSCS, is renowned for its rigor, flexibility, and affordability, making it a top choice for aspiring computer scientists worldwide. A key feature of the Georgia Tech OMSCS program is the opportunity to specialize in a specific area of computer science, allowing you to tailor your education to your interests and career goals.
This guide delves into the diverse specializations offered within the Georgia Tech Online Cs Masters program. Understanding these specializations is crucial for prospective students to make informed decisions about their academic journey and future career paths. Let’s explore the options available to you:
Artificial Intelligence
Alt text: Conceptual image depicting artificial intelligence with glowing lines forming a network, representing the interconnectedness of AI algorithms and data.
The Artificial Intelligence specialization, previously known as Interactive Intelligence, is designed for students eager to explore the fascinating world of intelligent systems. This specialization requires a prerequisite undergraduate course in algorithms or computational thinking, ensuring students have a foundational understanding before diving into advanced AI concepts.
Core Courses (9 hours):
Students must select one course from the Algorithms and Design group and two courses from the core AI courses:
-
Algorithms and Design (Choose one):
- CS 6300 Software Development Process
- CS 6301 Advanced Topics in Software Engineering
- CS 6505 Computability, Algorithms, and Complexity
- CS 6515 Introduction to Graduate Algorithms
- CSE 6140 Computational Science and Engineering Algorithms
-
Core AI Courses (Choose two):
- CS 6601 Artificial Intelligence
- CS 7637 Knowledge-Based AI
- CS 7641 Machine Learning
Electives (6 hours):
Students can further customize their AI specialization by choosing two elective courses from the following categories:
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Interaction: Focuses on the intersection of AI and human interaction.
- CS 6440 Introduction to Health Informatics
- CS 6460 Educational Technology: Conceptual Foundations
- CS 6465 Computational Journalism
- CS 6471 Computational Social Science
- CS 6603 AI, Ethics, and Society
- CS 6750 Human-Computer Interaction
-
AI Methods: Delves into specific AI techniques and applications.
- CS 6476 Computer Vision
- CS 7631 Multi-Robot Systems
- CS 7632 Game AI
- CS 7633 Human-Robot Interaction
- CS 7634 AI Storytelling in Virtual Worlds
- CS 7643 Deep Learning
- CS 7647 Machine Learning with Limited Supervision
- CS 7650 Natural Language
- CS 8803 Special Topics: Advanced Game AI
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Cognition: Explores the cognitive aspects of AI and human-like thinking in machines.
- CS 6795 Introduction to Cognitive Science
- CS 7610 Modeling and Design
- CS 7651 Human and Machine Learning
- CS 8803 Special Topics: Computational Creativity
This specialization is ideal for students aiming for careers in AI research, development of intelligent systems, machine learning engineering, and related fields.
Computational Perception and Robotics
Alt text: Advanced robotics lab at Georgia Tech, showcasing a robotic arm and complex machinery, highlighting research in computational perception and robotics.
The Computational Perception and Robotics specialization focuses on the exciting intersection of computer vision, robotics, and artificial intelligence. Students in this specialization will learn how to develop intelligent robots that can perceive their environment, make decisions, and interact with the world.
Core Courses (6 hours):
-
Algorithms (Choose one): Provides a strong algorithmic foundation necessary for robotics and perception.
- CS 6505 Computability, Algorithms, and Complexity
- CS 6515 Introduction to Graduate Algorithms
- CS 6520 Computational Complexity Theory
- CS 6550 Design and Analysis of Algorithms
- CS 7520 Approximation Algorithms
- CS 7530 Randomized Algorithms
- CSE 6140 Computational Science and Engineering Algorithms
-
AI or Machine Learning (Choose one): Essential for building intelligent and adaptive robotic systems.
- CS 6601 Artificial Intelligence
- CS 7641 Machine Learning
Electives (9 hours):
Students choose three elective courses, with at least one from each of the following areas:
-
Perception: Focuses on computer vision and related sensory data processing.
- CS 6475 Computational Photography
- CS 6476 Computer Vision
- CS 7499 3D Reconstruction
- CS 7636 Computational Perception
- CS 7639 Cyber Physical Design and Analysis
- CS 7644 Machine Learning for Robotics
- CS 7650 Natural Language
-
Robotics: Delves into the control, planning, and intelligence of robots.
- CS 7630 Autonomous Robotics
- CS 7631 Autonomous Multi-Robot Systems
- CS 7633 Human-Robot Interaction
- CS 7638 Artificial Intelligence Techniques for Robotics
- CS 7648 Interactive Robot Learning
- CS 7649 Robot Intelligence: Planning
Graduates with this specialization are well-prepared for careers in robotics engineering, autonomous systems development, computer vision research, and automation industries.
Computer Graphics
Alt text: Detailed computer graphics rendering of a complex scene, showcasing advanced techniques in lighting, textures, and 3D modeling, representing computer graphics specialization.
The Computer Graphics specialization is tailored for students passionate about visual computing, including image synthesis, animation, and interactive graphics. This specialization provides a strong foundation in the principles and techniques behind creating compelling visual experiences.
Core Courses (6 hours):
-
Graphics Fundamentals (Choose one): Introduces core concepts in computer graphics.
- CS 6491 Foundations of Computer Graphics
- CS 6457 Video Game Design
- CS 7496 Computer Animation
-
Algorithms (Choose one): Provides algorithmic tools necessary for graphics computations.
- CS 6505 Computability, Algorithms, and Complexity
- CS 6515 Introduction to Graduate Algorithms
Electives (9 hours):
Students select three elective courses to further specialize in areas within computer graphics:
- Graphics Applications and Advanced Topics:
- CS 6457 Video Game Design and Programming
- CS 6475 Computational Photography
- CS 6476 Computer Vision
- CS 6491 Foundations of Computer Graphics
- CS 6492 Shape Grammars
- CS 6730 Data Visualization Principles
- CS 7450 Information Visualization
- CS 7496 Computer Animation
This specialization opens doors to careers in the gaming industry, visual effects, animation studios, virtual and augmented reality development, and scientific visualization.
Computing Systems
Alt text: Interior of a large data center with rows of servers and blinking lights, illustrating the scale and complexity of modern computing systems, relevant to the Computing Systems specialization.
The Computing Systems specialization is designed for students interested in the underlying infrastructure that powers modern computing. This specialization covers a broad range of topics, from operating systems and computer architecture to networking and distributed systems.
Core Courses (9 hours):
-
Algorithms (Choose one):
- CS 6505 Computability, Algorithms, and Complexity
- CS 6515 Introduction to Graduate Algorithms
-
Systems Core (Choose two): In-depth study of key computing systems areas.
- CS 6210 Advanced Operating Systems
- CS 6241 Compiler Design
- CS 6250 Computer Networks
- CS 6290 High-Performance Computer Architecture
- CS 6300 Software Development Process OR CS 6301 Advanced Topics in Software Engineering
- CS 6390 Programming Languages
- CS 6400 Database Systems Concepts and Designs
- Any Core Courses in excess of the 9-hour requirement can be used as Computing Systems Electives.
Electives (9 hours):
Students choose three elective courses from a vast list, allowing for deep dives into specific systems areas:
- Systems Electives:
- CS 6035 Introduction to Information Security
- CS 6200 Graduate Introduction to Operating Systems
- CS 6220 Big Data Systems and Analytics
- CS 6235 Real Time Systems
- CS 6238 Secure Computer Systems
- CS 6260 Applied Cryptography
- CS 6262 Network Security
- CS 6263 Intro to Cyber Physical Systems Security
- CS 6291 Embedded Software Optimization
- CS 6310 Software Architecture and Design
- CS 6340 Software Analysis and Testing
- CS 6365 Introduction to Enterprise Computing
- CS 6422 Database System Implementation
- CS 6550 Design and Analysis of Algorithms
- CS 6675 Advanced Internet Computing Systems and Applications
- CS 7210 Distributed Computing
- CS 7260 Internetworking Architectures and Protocols
- CS 7270 Networked Applications and Services
- CS 7280 Network Science
- CS 7290 Advanced Topics in Microarchitecture
- CS 7292 Reliability and Security in Computer Architecture
- CS 7560 Theory of Cryptography
- CS 8803 FPL Special Topics: Foundations of Programming Languages
- CSE 6220 High Performance Computing
- Any Special Topics (CS 8803) course taught by a School of Computer Science faculty member can count as a Computing Systems elective. Check the School of Computer Science website for faculty listings.
Graduates from this specialization are highly sought after for roles in systems administration, network engineering, cloud computing, cybersecurity, and software engineering focused on infrastructure.
High Performance Computing
Alt text: A section of a supercomputer, showing intricate wiring and cooling systems, representing the advanced technology in high-performance computing.
The High Performance Computing (HPC) specialization focuses on the techniques and technologies used to solve computationally intensive problems. Students learn about parallel algorithms, high-performance architectures, and software tools for maximizing computational performance.
Core Courses (6 hours):
- CSE 6140 Computational Science and Engineering Algorithms
- CSE 6220 High Performance Computing
Electives (9 hours):
Students choose three electives to deepen their knowledge in specific HPC areas:
- HPC Electives:
- CSE 6221 Multicore Computing: Concurrency and Parallelism on the Desktop
- CS/CSE 6230 High-Performance Parallel Computing: Tools and Applications
- CS 6241 Compiler Design
- CS 6290 High-Performance Computer Architecture
- CS/CSE 8803 Special Topics: Parallel Numerical Algorithms
- CSE 6236 Parallel and Distributed Simulation
- CSE 8803 Special Topics: Hot Topics in Parallel Computing
This specialization prepares graduates for careers in scientific computing, data analytics, simulation and modeling, and industries requiring massive computational power such as finance and research.
Human Centered Computing (For PhD Students in HCC)
(Note: This specialization is exclusively for PhD students in HCC seeking an MSCS degree.)
The Human Centered Computing (HCC) specialization, specifically for HCC PhD students, focuses on the design, development, and evaluation of computing systems that are usable, effective, and enjoyable for people.
Core Courses (9 hours):
- CS 6451 Intro to HCC
- CS 6452 Prototyping Interactive Systems
- CS 7455 Issues in HCC
Electives (6 hours):
Students choose two electives from a broad selection related to human-computer interaction and cognitive science:
- HCC Electives:
- CS 6455 User Interface Design and Evaluation
- CS 6456 User Interface Software
- CS 6460 Educational Technology: Conceptual Foundations
- CS 6465 Computational Journalism
- CS 6470 Design of Online Communities
- CS 6471 Computational Social Science
- CS 6474 Social Computing
- CS 6476 Computer Vision
- CS 6601 Artificial Intelligence
- CS 6730 Data Visualization: Principles & Applications
- CS 6750 Human-Computer Interaction
- CS 6795 Introduction to Cognitive Science
- CS 7450 Information Visualization
- CS 7451 Human-Centered Data Analysis
- CS 7460 Collaborative Computing
- CS 7470 Mobile and Ubiquitous Computing
- CS 7476 Advanced Computer Vision
- CS 7610 Modeling and Design
- CS 7632 Game AI
- CS 7633 Human Robot Interaction
- CS 7637 Knowledge-Based AI
- CS 7620 Case-based Reasoning
- CS 7641 Machine Learning
- CS 7650 Natural Language
- CS 7695 Philosophy of Cognition
- CS 7697 Cognitive Models of Science and Technology
- CS 7790 Cognitive Modeling
- CS 8803 Computational Creativity
- CS 8803 Expressive AI
- CS 8803 Computers, Communications & International Development
This specialization is designed to enhance the research and academic careers of HCC PhD students, providing them with a strong MSCS foundation within their doctoral studies.
Human-Computer Interaction
Alt text: Wireframe mockup of a user interface on a tablet, surrounded by sketches and design tools, representing the iterative process of user interface design in Human-Computer Interaction.
The Human-Computer Interaction (HCI) specialization focuses on the crucial relationship between humans and computers. Students learn to design, evaluate, and implement interactive computing systems that are user-friendly, efficient, and meet human needs.
Core Courses (6 hours):
- Core HCI Concepts (Choose one):
- CS 6456 Principles of User Interface Software OR CS 7470 Mobile and Ubiquitous Computing
- CS 6750 Human-Computer Interaction
Electives (9 hours):
Students choose three electives, with at least one from each of the sub-areas below:
-
Sub-area: Design and evaluation concepts: Focuses on the theoretical and methodological foundations of HCI design.
- CS 6010 Principles of Design
- CS 6320 Software Requirements Analysis and Specification
- CS 6435 Digital Health Equity
- CS 6455 User Interface Design and Evaluation
- CS 6457 Video Game Design
- CS 6460 Educational Technology: Conceptual Foundations
- CS 6465 Computational Journalism
- CS 6470 Design of Online Communities
- CS 6795 Introduction to Cognitive Science
- CS 7465 Educational Technology: Design and Evaluation
- CS 7467 Computer-Supported Collaborative Learning
- CS 7790 Cognitive Modeling
-
Sub-area: Interactive technology: Focuses on the technical implementation and application of interactive systems.
- CS 6440 Introduction to Health Informatics
- CS 6730 Data Visualization: Principles & Applications
- CS 6763 Design of Design Environments
- CS 6770 Mixed Reality Experience Design
- CS 7450 Information Visualization
- CS 7451 Human-Centered Data Analysis
- CS 7460 Collaborative Computing
- CS 7470 Mobile and Ubiquitous Computing
- CS 7632 Game AI
Graduates with an HCI specialization are in high demand for roles such as UX designers, UI developers, usability engineers, interaction designers, and HCI researchers across various industries.
Machine Learning
Alt text: Abstract visualization of a machine learning algorithm processing data, with nodes and connections illustrating neural network operations, representing the Machine Learning specialization.
The Machine Learning specialization is one of the most popular within the Georgia Tech Online CS Masters program. It provides students with a comprehensive understanding of machine learning algorithms, techniques, and their applications in various domains.
Core Courses (6 hours):
-
Algorithms (Choose one): Provides necessary algorithmic background for machine learning.
- CS 6505 Computability, Algorithms, and Complexity
- CS 6515 Introduction to Graduate Algorithms
- CS 6520 Computational Complexity Theory
- CS 6550 Design and Analysis of Algorithms
- CS 7510 Graph Algorithms
- CS 7520 Approximation Algorithms
- CS 7530 Randomized Algorithms
- CSE 6140 Computational Science and Engineering Algorithms
-
Core ML Courses (Choose one): Fundamental machine learning coursework.
- CS 7641 Machine Learning
- CSE 6740 Computational Data Analysis: Learning, Mining, and Computation
Electives (9 hours):
Elective ML courses must have at least one-third of their graded content based on Machine Learning. Students select three courses from a wide array of specialized ML topics:
- Machine Learning Electives:
- CS 6220 Big Data Systems & Analysis
- CS 6476 Computer Vision
- CS 6603 AI, Ethics, and Society
- CS 7280 Network Science
- CS 7535 Markov Chain Monte Carlo
- CS 7540 Spectral Algorithms
- CS 7545 Machine Learning Theory
- CS 7616 Pattern Recognition
- CS 7626 Behavioral Imaging
- CS 7642 Reinforcement Learning and Decision Making
- CS 7643 Deep Learning
- CS 7644 Machine Learning for Robotics
- CS 7646 Machine Learning for Trading
- CS 7650 Natural Language
- CS 8803 Special Topics: Probabilistic Graph Models
- CSE 6240 Web Search and Text Mining
- CSE 6242 Data and Visual Analytics
- CSE 6250 Big Data for Health
- ISYE 6416 Computational Statistics
- ISYE 6420 Bayesian Methods
- ISYE 6664 Stochastic Optimization
- Approved Substitutions
Graduates with a Machine Learning specialization are highly sought after in data science, AI engineering, research positions, and various industries leveraging machine learning for innovation.
Modeling and Simulations
Alt text: Dynamic visualization of a complex simulation, showing data points and flow lines, representing the application of modeling and simulation techniques.
The Modeling and Simulations specialization focuses on the principles and techniques for creating and analyzing computational models of real-world systems. Students learn to use simulation tools and methodologies for understanding complex phenomena and making predictions.
Core Courses (6 hours):
- CSE 6730 Modeling and Simulation: Foundations and Implementation
- Choose one from:
- CSE 6220 High Performance Computing
- ISYE 6644 Simulation
- MATH 6640 Introduction to Numerical Methods for Partial Differential Equations
Electives (9 hours):
Students select three electives to further specialize in modeling and simulation techniques and applications:
- Modeling and Simulation Electives:
- CSE 6220 High Performance Computing
- CSE 6236 Parallel and Distributed Simulation
- CSE/CHEM 8803 Special Topics: Quantum Information, Computation, and Simulation
- CS 7280 Network Science
- INTA 6742 Modeling, Simulation and Military Gaming
- ISYE 6644 Simulation
- MATH 6640 Introduction to Numerical Methods for Partial Differential Equations
This specialization prepares graduates for careers in simulation engineering, computational modeling, data analysis, and industries that rely on simulation for design, analysis, and decision-making.
Scientific Computing
Alt text: Scientific visualization of complex data, showing volumetric rendering and color gradients, demonstrating the power of scientific computing for data analysis and interpretation.
The Scientific Computing specialization is tailored for students interested in applying computational techniques to solve problems in science and engineering. This specialization focuses on numerical methods, algorithms, and software tools used in scientific simulations and data analysis.
Core Courses (6 hours):
- CSE/MATH 6643 Numerical Linear Algebra
- Choose one from:
- CSE/MATH 6644 Iterative Methods for Systems of Equations
- MATH 6640 Introduction to Numerical Methods for Partial Differential Equations
Electives (9 hours):
Students choose three electives to deepen their expertise in scientific computing:
- Scientific Computing Electives:
- CS/CSE 6230 High-Performance Parallel Computing: Tools and Applications
- CS/CSE 8803 Special Topics: Parallel Numerical Algorithms
- CSE 6140 Computational Science and Engineering Algorithms
- CSE 6220 High Performance Computing
- CSE/MATH 6644 Iterative Methods for Systems of Equations
- CSE 8803 Special Topics: Algorithms for Medical Imaging and Inverse Problems
- CSE 8803/CHEM 6485 Computational Chemistry
- MATH 6640 Introduction to Numerical Methods for Partial Differential Equations
Graduates are well-prepared for careers in research institutions, government labs, and industries requiring advanced computational skills for scientific discovery and engineering innovation.
Social Computing
Alt text: Visualization of a social network, with nodes representing individuals and lines showing connections, illustrating social computing and network analysis.
The Social Computing specialization focuses on the intersection of computer science and social sciences. Students learn to design, analyze, and understand social computing systems, online communities, and the impact of technology on society.
Core Courses (6 hours):
- Social Computing Core (Choose two):
- CS 6470 Design of Online Communities
- CS 6474 Social Computing
- CS 6471 Computational Social Science
Electives (9 hours):
Students choose three electives, including additional courses from the core list and other related areas:
- Social Computing Electives:
- Additional courses from the Core list
- CS 6238 Secure Computer Systems
- CS 6250 Computer Networks
- CS 6456 Principles of User Interface Software
- CS 6465 Computational Journalism
- CS 6505 Computability, Algorithms, and Complexity
- CS 6515 Introduction to Graduate Algorithms
- CS 6675 Advanced Internet Computing Systems and Applications
- CS 6730 Data Visualization: Principles & Applications
- CS 6750 Human-Computer Interaction
- CS 7210 Distributed Computing
- CS 7270 Networked Applications and Services
- CS 7280 Network Science
- CS 7450 Information Visualization
- CS 7451 Human-Centered Data Analysis
- CS 7467 Computer-Supported Collaborative Learning
- CS 7650 Natural Language
This specialization prepares graduates for careers in social media analysis, online community management, social network research, policy making related to technology and society, and user-centered design in social platforms.
Visual Analytics
Alt text: A visual analytics dashboard displaying various charts, graphs, and maps, showcasing data visualization techniques for analysis and decision-making in Visual Analytics.
The Visual Analytics specialization focuses on the science of analytical reasoning facilitated by interactive visual interfaces. Students learn to design and develop visual analytics tools and techniques for exploring large and complex datasets, gaining insights, and making data-driven decisions.
Core Courses (9 hours):
- CS 6730 Data Visualization: Principles & Applications
- CS 7450 Information Visualization
- CSE 6242 Data and Visual Analytics
Electives (6 hours):
Students choose two electives to further specialize in visual analytics techniques and applications:
- Visual Analytics Electives:
- CS 6456 Principles of User Interface Software
- CS 6465 Computational Journalism
- CS 6491 Computer Graphics
- CS 6750 Human-Computer Interaction
- CS 6795 Introduction to Cognitive Science
- CS 7451 Human-Centered Data Analysis
- CS 7641 Machine Learning
- CSE 6740 Computational Data Analysis
Graduates with a Visual Analytics specialization are in demand for roles such as data analysts, business intelligence analysts, visualization specialists, UX researchers in data-intensive domains, and developers of visual analytics software.
Choosing the right specialization within the Georgia Tech Online CS Masters program is a crucial step in shaping your future in computer science. Each specialization offers a unique curriculum and career pathway. By carefully considering your interests and career aspirations, you can leverage the Georgia Tech OMSCS program to achieve your professional goals and contribute meaningfully to the ever-evolving world of technology. Explore the Georgia Tech OMSCS website for the most up-to-date information and to begin your application journey.
