Carnegie Mellon University

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.

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)

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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.

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)

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Intelligent 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.

Four courses from the following menu: 

Design and Construction
(at least one course)

Analytical Principles and Domain Foundations
(at least one course)

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)

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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.

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
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. 

Software Engineering (SE)

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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.*

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)

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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.

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)

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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.

Four courses from the following menu:

List 1: Networking
(at least one course)

List 2: Distributed Systems
(at least one course)

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
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. 

Wireless/Embedded Systems (WES)

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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.

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
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. 

Integrated Systems (IS)

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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.

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
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. 

Devices and Nanofab (DN)

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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.

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
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.