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 Introduction to Machine Learning for Engineers 18-751 Applied Stochastic Processes 18-792 Advanced Digital Signal Processing
18-660 Optimization 18-793 Image and Video Processing
18-752 Estimation, Detection, and Learning 18-794 Pattern Recognition Theory
18-665 Advanced Probability and Statistics for Engineers 18-698 Neural Signal Processing
18-662 Principles and Engineering Applications of AI 18-898D Graph Signal Processing and Learning
18-667 Algorithms for Large-Scale Distributed Machine Learning and Optimization 18-668 Data Science for Software Engineering
18-786 Deep Learning* 18-663 Hardware Architectures for Machine Learning
18-797 Machine Learning for Signal Processing* 18-755 Networks in Real World
18-753 Information Theory Measures for Artificial and Natural Intelligence** 18-758 Wireless Communications
18-785 Data, Inference, and Applied Machine Learning 18-781 Speech Recognition and Understanding

KEY

* Cross-list
** Dormant

Occasionally courses are updated or become dormant. 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 under 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, and 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  Computational Problem Solving for Engineers 18-642  Embed System Software Engineering 18-645  How to Write Fast Code I 18-661  Introduction to Machine Learning for Engineers
18-643  Reconfigurable Logic 18-652  Foundations of Software Engineering 18-660  Optimization
18-646  How to Write Fast Code II 18-653SV  Software Architecture and Design* 18-687  Analytical Performance Modeling & Design of Computer Systems
18-649  Mobile Hardware ** 18-709  Advanced Cloud Computing 18-411  Computational Techniques in Engineering
18-740  Modern Computer Architecture and Design 18-745  Rapid Prototyping of Computer Systems 18-665  Advanced Probability & Statistics for Engineers
18-747  How to Write Low Power Code for the IoT** 18-668SV  Data Science for Software Engineering*
18-743  Neuromorphic Computer Architecture and Processor Design
18-648  Real-Time Embedded Systems

KEY

*Course is typically offered in Silicon Valley
** Dormant

Occasionally courses are updated or become dormant. 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.

 Note that the Software Engineering concentration is currently only available to students in Silicon Valley.

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 become dormant. 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 Introduction to Information Security** 18-731 Network Security** 18-636 Browser Security **
18-730 Introduction to Computer Security** 18-732 Secure Software Systems** 18-637 Wireless Security**
18-733 Applied Cryptography** 18-638 Mobile Security**
18-734 Foundations of Privacy** 18-765 Digital Systems Testing and Testable Design
18-632 Introduction to Hardware Security** 18-739 Foundations of Security and Privacy** (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.
*Course is typically offered ONLY in Silicon Valley.
**Course is typically offered at both Pittsburgh AND Silicon Valley.
***Dormant

Occasionally courses are updated or become dormant. 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 Computer Networks 18-749 Building Reliable Distributed Systems 18-748 Wireless Sensor Networks
18-651 Networked Cyber-Physical Systems 18-756 Packet Switching and Computer Networks 18-759 Wireless Networks
18-731 Network Security 18-755 Networks in the Real World 18-750 Wireless Networking Applications
18-637 Wireless Security

Occasionally courses are updated or become dormant. 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 Neuromorphic Computer Architecture & Processor Design 18-637 Wireless Security 18-741 Computer Networks 18-745 Rapid Prototyping of Computer Systems**
18-747 How to Write Low Power Code for the IoT 18-741 Computer Networks 18-744SV Connected Embedded Systems Architecture*,** 18-846SV Wireless Systems Design Experience*,**
18-748 Wireless Sensor Networks
18-750 Wireless Networking and Applications

KEY

No asterisk indicates that the course is typically offered ONLY in Pittsburgh.
*Course is typically offered ONLY in Silicon Valley.
**Dormant

Occasionally courses are updated or become dormant. 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)
18-622 Advanced Digital Integrated Circuit Design 18-625 ULSI Mobile Platform and Server Product Design* 18-610 Fundamentals of Mod CMOS*
18-623 Analog Integrated Circuit Design 18-640 Hardware Arithmetic for Machine Learning 18-614 Microelectromechanical Systems (MEMS)
18-664 ULSI SOC Roadmap* 18-742 Computer Architecture and Systems
18-721 Advanced Analog Integrated Circuits Design 18-760 VLSI CAD*
18-723 RF IC Design and Implementation* 18-762 Circuit Simulation and Optimization Methods: A Power Systems Perspective
18-725 Advanced Digital Integrated Circuit Design 18-765 Digital Systems Testing and Testable Design
18-726 Projects in Integrated Circuit Design: First Silicon 18-632 Introduction to Hardware Security
18-740 Modern Computer Architecture Design 18-743 Neuromorphic Computer Architecture Processor Design
18-729C Power Electronics 18-847E Neuromorphic Computer Architecture

Key

*Dormant

Occasionally courses are updated or become dormant. 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 Fundamentals of Mod CMOS* 18-612 Neural Technology: Sensing and Stimulation 18-819C Nonlinear Optics and Photonics
18-614 Microelectromechanical Systems (MEMS) 18-616 Nano-Bio-Photonics 18-819D Memory Devices and Technology
18-615 Micro and Nano Systems Fabrication 18-622 Advanced Digital Integrated Circuit Design 18-819E Elements of Quantum Communications and Networks
18-623 Analog Integrated Circuit Design 18-819F Introduction to Quantum Computing
18-712 Elements of Photonics for Communications Systems 18-819K Beyond CMOS Devices and Circuits
18-715 Physics of Applied Magnetism 18-669F Micro/Nano Biomedical Devices
18-817 Applied Physics: Fundamentals of Semiconductors and Nanostructures

KEY

*Dormant

Occasionally courses are updated or become dormant. 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. 

 

*Note that 18-699 is a Special Topics course. Several versions of this course have been discontinued. If you have taken a version that does not appear on this list, please check with your academic advisor to see if the course satisfies one of the DN concentration requirements.