Grad Courses

Both M.S. and Ph.D. students need to meet certain coursework requirements. This page contains information and resources for courses offered by the School of Electrical and Computer Engineering, coursework planning tools, minor information, forms, and permit requests.

ECE Course Information and Syllabi
Graduate Projected Course Schedule
Overload/Permit Request System

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Minors

CS Courses Recommended for Ph.D. Minor

Minors

UNDERGRADUATE COURSES

 

CS Courses Recommended for Ph.D. Minor

Undergraduate Courses

CS 4240Compilers and Interpreters
CS 4400Introduction to Database Systems
CS 4455Video Game Design
CS 4475Computational Photography
CS 4495Computer Vision
CS 4590Computer Audio
CS 4641Machine Learning
CS 4752Philosophical Issues in Computation
CS 4777Vector and Parallel Scientific Computing

 

GRADUATE COURSES

 Graduate Courses 
CS 6035Intro to Info Security
CS 6140Computational Science & Engineering (CSE) Algorithms
CS 6210Advanced Operating Systems
CSE 6220Intro to High Performance Computing
CSE 6230High-Performance Parallel Computing: Tools and Applications
CS 6235Real-Time System Concepts and Implementation
CSE 6236Parallel and Distributed Simulation Systems
CS 6238Secure Computer Systems
CSE 6240Web Search and Text Mining
CS 6241Design and Implementation of Compilers
CSE 6242Data and Visual Analytics
CS 6250Computer Networks
CS 6260Applied Cryptography
CS 6300Software Development Process
CS 6310Software Architecture and Design
CS 6320Software Requirements Analysis and Specifications
CS 6330Software Generation, Testing, and Maintenance
CS 6340Software Analysis and Testing
CS 6365Introduction to Enterprise Computing
CS 6390Programming Languages
CS 6400Database Systems Concepts and Design
CS 6422Database Sys Implement
CS 6440Introduction to Health Informatics
CS 6451Intro to Human-centered Computing
CS 6455User Interface Design and Evaluation
CS 6456Principles of User Interface Software
CS 6457Video Game Design and Programming
CS 6470Design of Online Communities
CS 6480Computer Visualization Techniques
CS 6491Computer Graphics
CS 6505Computability & Algorithms
CS 6520Computational Complexity Theory
CS 6550Design and Analysis of Algorithms
CS 6601Artificial Intelligence
CS 6675Advanced Internet Computing
CS 6725Info Security Policy
CS 6726Privacy Tech Policy Law
CSE 6730 Modeling and Simulation: Foundation and Implementation
CS 6750Human-Computer Interaction
CS 6754Engineering Database Management Systems
CS 6770Mixed Reality Design
CS 6795Introduction to Cognitive Science
CS 7210Distributed Computing 
CS 7260Internetworking Architectures and Protocols
CS 7270Networked Applications and Services
CS 7290Advanced Microarchitecture
CS 7292 Reliable Secure Computer Architectures
CS 7450Information Visualization
CS 7460Collaborative Computing
CS 7470Ubiquitous Computing
CS 7490Advanced Image Synthesis
CS 74913D Complexity
CS 7495Computer Vision
CS 7496Computer Animation
CS 7497Virtual Environments
CS 7510Graph Algorithms
CS 7520Approximation Algorithms
CS 7530Randomized Algorithms
CS 7535Markov Chain Monte Carlo Methods
CS 7575Machine Learning Theory
CS 7610Modeling and Design
CS 7616Pattern Recognition
CS 7630Autonomous Robotics
CS 7631Multi-Robot Systems
CS 7632Game AI
CS 7633Human-Robot Interaction
CS 7637Knowledge-Based AI
CS 7641 Machine Learning
CS 7646Machine Learning for Trading
CS 7649Robot Intelligence and Planning
CS 7650Natural Language Understanding
CS 8803IMS, Mobile Applications and Services for Converged Networks
CS 8803Graduate Introduction to Operating Systems
CS 8803Introduction to Enterprise Computing
CS 8803Machine Learning II: Advanced Topics
CS 88033D Reconstruction and Mapping in Computer Vision, Robotics and Augmented Reality
CS 8803Health Information Exchange
CS 8803Algorithms for Complex Networks
CSE 8803Fast Linear Algebra
CS 8803Game Studio 2
CS 8803Alternative Computing Technologies
CS 8803Sonification Lab R&D Studio
CS 8803 Advanced Software Engineering
CS 8803Building Secure Systems
CS 8803Machine Learning for Robotics
CS 8803Deep Learning for Perception
CS 8803Autonomous Unmanned Systems
CS 8803Statistical Techniques in Robotics
CS 8803Software Defined Networking Lab
CS 8803Big Data Systems and Analytics
CS 8803Humanoid Robotics
 

Note: CS 6260 and ECE 6280 cannot both be taken for credit.

OTHER COURSES

Students wishing to have additional courses considered for use toward the minor requirements must provide a course outline/syllabus to the ECE Graduate Affairs Office no later than two weeks (and preferably four weeks) prior to the first day of the final phase of registration for the term in which the non-ECE special topic course is offered. The student must provide either a hard copy of the course outline/syllabus or a link to electronic media outlining the course for which approval is sought.

CS Special Problems courses (CS 8903 taken for 1, 2, or 3 credit hours) and CS seminars are now accepted for both M.S. and Ph.D. students towards group IV (electives).

Math Courses Recommended for Ph.D. Minor

 

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UNDERGRADUATE LEVEL

4107Abstract Algebra I
4108Abstract Algebra II
4150Introduction to Number Theory
4255Monte Carlo Methods
4261Mathematical Statistics I
4305 Topics in Linear Algebra 
4317 Introduction to Analysis I 
4318 Introduction to Analysis II 
4320 Complex Analysis 
4347Partial Differential Equations I
4387Partial Differential Equations II
4431 Introductory Topology 
4432 Introduction to Algebraic Topology 
4441Differential Geometry
4542Dynamics and Bifurcations II
4580Linear Programming
4640Numerical Analysis I
4641Numerical Analysis II
4782Quantum Information and Quantum Computing

GRADUATE LEVEL

Most 6000 (or higher) level math courses will be considered for approval for use toward the minor requirement.

Special Problems

Special Problems hours (ECE 8901, ECE 8902, ECE 8903, and CS 8903) are independent study courses under the direction of a faculty supervisor. Special Problems courses are an excellent way to get to know faculty members and to become involved in research that is going on at Georgia Tech. To learn more about Special Problems, refer to the Graduate Student Handbook.

Special Problems Course Approval (requires original signature from faculty member)

Certify Special Problems Hours (only use for hours to count toward Ph.D. degree)

M.S. COURSEWORK PLANNING

Use the coursework planning forms to plan courses.

PH.D. COURSEWORK PLANNING

Responsible Conduct of Research 

The Coursework Completion Form must be completed on the ECE secure website, prior to the submission of the Ph.D. Proposal.

Students who wish to count course credit earned at other universities toward their Ph.D. degree requirements should request the class evaluation during their second term or later. The classes have to be graduate or senior undergraduate level. No classes that were used to satisfy an undergraduate degree can be used toward the Ph.D. degree. Up to 30 hours of credits earned toward a graduate degree with a grade of C and above at a different institution can be used towards the Ph.D. degree. M.S. Thesis can be used in Group IV (electives) for a maximum of 12 credit hours. The approved classes will only count toward the Ph.D. degree course requirements and will not be transferred on the Georgia Tech transcript.

The following package needs to be submitted to the Academic Office for evaluation and approval:

Copy of the Coursework Completion form, filled out entirely. The classes have to show the institution name, number, and title. If the coursework is not completed at the time of the submission, future classes need to be included for a total of 43 hours. The future classes can be later changed to other eligible classes. Please use the classes taken at Georgia Tech in Groups I, II, and III as much as you can.

Non-official transcript from the institution where the classes have been taken. The transcript needs to show that the classes have been used toward a graduate degree and whether the institution is on the semester or quarter system.

Syllabi/course descriptions for all the classes to be used in Groups I, II, and III.

A soft copy of the M.S. thesis (if used in the coursework plan).

 

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