M.S. Concentrations
M.S. ECE students have the option to follow one of the following concentrations for focused study in a specific area of electrical and computer engineering. M.S. students are not required to complete a concentration in order to graduate. Generally, M.S. students can select from the full range of ECE graduate course offerings to meet their course requirements and to advance toward their individual career objectives.
- AI/ML Systems
- Intelligent Physical Systems
- Computational Engineering Methods/Systems
- Software Engineering
- Computer Security
- Network/Distributed Systems
- Wireless/Embedded Systems
- Integrated Systems
- Devices and Nanofab
Students completing one or more of these concentrations should refer to their degree as a Master of Science in Electrical and Computer Engineering with a concentration in <name of concentration>. Students satisfying the requirements for more than one concentration may acknowledge all concentrationons for which they fulfill the requirements. All concentrations require a minimum of four ECE courses, distributed across categories as described below.
To declare, students should fill out the M.S. Concentration Declaration form in their final semester by the semester course withdrawal deadline. Please note that students must wait until their final semester to submit the form. Once signed by the academic advisor, this form serves as proof of completion of the concentration, as no additional certificate is issued and concentrations are not listed on the transcript. If a student is completing more than one concentration, they should declare each concentration on a separate form.
AI/ML Systems (AIML)
The AI/ML concentration will provide students the opportunity for in-depth specialization in artificial intelligence and machine learning, and their applications to various natural and technological systems. Students will take introductory courses that cover the basics of machine learning, statistics and optimization and their application in numerous fields including advanced speech, image and neural processing. In addition, students will also have the opportunity to apply the techniques in machine learning and AI to specific problem domains such as personalized healthcare, smart grid, computational photography, or social networks.
Course Menu
Four courses from the following menu:
Core (one course from this list |
Algorithm and Methods (at least on from this list) |
Application Domains (at least one from this list) |
18-661 | 18-751 Applied Stochastic Proc. | 18-792 Advanced DSP |
18-660 Optimization | 18-793 Image and Video | |
18-752 Estimation and Detection | 18-794 Pattern Recognition | |
18-665 Statistics for Engineers | 18-698 Neural SP | |
18-662 AI for Engineers | 18-898D Graph SP | |
18-667 Algo for Large-Scale Learning | 18-668 Data Sci for SE | |
18-786 Deep Learning | 18-663 Hardware Arch | |
18-797 MLSP | 18-755 Networks in Real World | |
18-753 Info Theory | 18-758 Wireless Comm | |
18-785 Data, Inference, and Applied ML | 18-781 Speech Recog |
Occasionally courses are updated or retired and these tables can take some time to reflect those changes. Please check with your advisors about course availability if the course has not been offered recently.
Intelligent Physical Systems (IPS)
Back to listIntelligent Physical systems (IPS) are physical and engineered systems whose operations may be monitored, controlled, coordinated or integrated by the cyber components of computing and communication. This MS Concentration will equip students with the relevant computing principles, domain-specific foundations and analytical techniques, and exposure to applications.
Course Menu
Four courses from the following menu:
Design and Construction (at least one course) |
Analytical Principles and Domain Foundations |
Application and Breadth (at least one course) |
18-644* | 18-618 | 18-637** |
18-642 | 18-882L++ | 18-638** |
18-648 | 18-762 | 18-730** |
18-651 | 18-883 K3-K4++ | 18-743** |
18-745 | 18-756 | 18-781** |
18-843** | 18-748 | 18-650 |
18-849 | 18-771 | |
18-776 | ||
18-794 | ||
18-792 | ||
18-797** | ||
18-793** |
Key
No asterisk indicates that the course is typically offered ONLY in Pittsburgh.
*Indicates that the course is typically offered ONLY in Silicon Valley.
**Indicates that the course is typically offered at both Pittsburgh AND Silicon Valley.
†Indicates that the course is typically offered ONLY in Kigali
††Indicates that the course is typically offered in both Pittsburgh and Kigali
Occasionally courses are updated or retired and these tables can take some time to reflect those changes. Please check with your advisors about course availability if the course has not been offered recently.
Computational Engineering Methods/Systems (CEM/S)
This concentration brings together all aspects of computational engineering in a consistent umbrella: computer architecture, software systems, computational algorithms, and software engineering. It allows students to become cross-cutting integration experts who integrate knowledge from architecture, software systems, software engineering, tool chains, up to numerical algorithms and their properties. This concentration enables students to be successful engineers understanding the big picture of software in the context of engineering applications and enables provides the technical underpinning to lead diverse engineering teams that tackle complex and multi-faceted problems.
Course Menu
Four courses from the following menu:
Prerequisites (mandatory) |
Hardware (pick one) |
Software (pick one) |
Algorithms (pick one) |
18-647 | 18-642 | 18-645 | 18-661 |
18-643 | 18-652 | 18-660 | |
18-646 | 18-653 | 18-687 | |
18-649 | 18-709 | 18-411 | |
18-740 | 18-745 | 18-665 | |
18-747 | 18-668 | ||
18-743 | |||
18-648 |
Software Engineering (SE)
Engineering software systems requires a diverse set of skills that pervade many application domains. This concentration gives students the opportunity to achieve sufficient breadth, depth, and hands-on experience in software engineering well beyond programming. To pursue this concentration, students should be familiar with multiple programming languages and possess sufficient coding skills, which they must demonstrate by completing a set of tasks assigned to them in advance. *This concentration is currently only available to Silicon Valley students.*
Course Menu
Four courses from the following menu:
Breadth Course (required course that must be taken concurrently or before the Depth Courses and no later than in the second semester) |
Depth Courses (at least 3 courses from the following list, which can be taken concurrently or after the Breadth Course) |
18-652*, *** Foundations of Software Engineering | 18-653** Software Architecture and Design |
18-654** Software Verification and Testing | |
18-657** Decision Analysis and Engineering Economics for Software Engineers | |
18-658* Software Requirements and Interaction Design | |
18-668* Data Science for Software Engineering | |
18-659* Software Engineering Methods |
Key
*The course is typically offered in Silicon Valley.
**The course is typically offered at both Pittsburgh AND Silicon Valley.
***Students must enroll in 18-652 early and successfully complete a set of coding tasks before the first class.
Occasionally courses are updated or retired and these tables can take some time to reflect those changes. Please check with your advisors about course availability if the course has not been offered recently.
Computer Security (SEC)
Students will become familiar with computer security fundamentals and will gain deeper proficiency in a core topic area such as software security, systems and networking security, privacy, or cryptography. Students will gain exposure to foundational security and privacy principles as well as hands-on tools and best practices for building secure and privacy-preserving systems.
Course Menu
Four courses from the following menu:
Introductory Computer Security (one course) |
Computer Security Core (two courses) |
Computer Security Electives (one course) |
18-631** | 18-731** | 18-636** |
18-730** | 18-732** | 18-637** |
18-733** | 18-638** | |
18-734** | 18-765 | |
18-632** | 18-739** (All offerings of this special topics course: A, C, E, F, L, M, N, SF, SV) | |
Any core course can count as an elective |
Key
No asterisk indicates that the course is typically offered ONLY in Pittsburgh.
*Indicates that the course is typically offered ONLY in Silicon Valley.
**Indicates that the course is typically offered at both Pittsburgh AND Silicon Valley.
Occasionally courses are updated or retired and these tables can take some time to reflect those changes. Please check with your advisors about course availability if the course has not been offered recently.
Network/Distributed Systems (NDS)
The networked and distributed systems concentration deals with the foundations and system-design issues of large-scale networks, including the Internet, cellular and mobile networks, data center networking and associated design challenges.
Course Menu
Four courses from the following menu:
List 1: Networking (at least one course) |
List 2: Distributed Systems |
List 3: Wireless (at least one course) |
18-741 | 18-749 | 18-748 |
18-651 | 18-756 | 18-759 |
18-731 | 18-755 | 18-750 |
18-637 |
Wireless/Embedded Systems (WES)
The wireless systems concentration explores core wireless technologies and systems-level issues that are at the heart of the Internet of Things, traditional broadband and cellular networks, cyber-physical systems and cloud-connected embedded computing.
Course Menu
Four courses from the following menu:
Devices (one course) |
Networks (one course) |
Systems (one course) |
Design Experience (one course) |
18-743 | 18-637 | 18-741 | 18-745 |
18-747 | 18-741 | 18-744SV | 18-846* |
18-748 | |||
18-750 |
Integrated Systems (IS)
Students achieve in-depth specialization into the design of modern integrated devices and systems. A unique feature of this concentration is a two-course sequence, 18-725 and 18-726, in which students design, fabricate, and test chips of their own design.
Course Menu
Four courses from the following menu:
Foundations (one course) |
Core (two courses) |
Electives (one course) |
18-623 | 18-625 | 18-610 |
18-622 | 18-640 | 18-614 |
18-664 | 18-742 | |
18-725 | 18-760 | |
18-726 | 18-762 | |
18-721 | 18-765 | |
18-723 | 18-727 | |
18-740 |
Devices and Nanofab (DN)
Students learn fundamentals of device physics and engineering techniques to implement electronic, photonic, electromagnetic, and microelectromechanical (MEMS) devices using advanced nanofabrication techniques for data storage, computation, communications, sensing, ranging and biomedical applications. Students are exposed to multi-disciplinary approaches to developing systems that leverage fundamental notions from a wide variety of fields.
Course Menu
Four courses from the following menu:
Foundations (one course) |
Core (two courses) |
Electives (one course) |
18-610 | 18-612 | 18-819C |
18-614 | 18-616 | 18-819D |
18-615 | 18-622 | 18-819E |
18-623 | 18-819K | |
18-712 | 18-469F | |
18-715 | 18-669 | |
18-817 |