Undergraduate degrees in the Department of Electrical and Computer Engineering are organized around a core of required courses and a selection of elective courses from four Specialization Areas:
- Computer Engineering: provides a broad background in computer systems engineering, including computer architecture, digital hardware engineering, software engineering, and computer systems performance analysis
- Data Science & Systems: integrates the foundations, tools and techniques involving data acquisition, data analytics, data storage and computing infrastructure in order to enable meaningful extraction of actionable information from diverse and potentially massive data sources. Applications include wireless communication systems, digital signal processing, image processing, and networking
- Neuroengineering: exploits engineering techniques to understand, repair, manipulate, or treat the diseases of human neural systems and networks
- Photonics, Electronics, and Nano-devices: encompasses studies of electronic materials, including nanomaterials, semiconductor and optoelectronic devices, lasers and their applications.
Specialization Area Requirements
- For BSECE, a minimum of six specialization area courses; For B.A., minimum of four.
- For BSECE, three or more in one area; for BA, two or more in one area.
- For both BSECE and BA, at least two areas.
- For both BSECE and BA, each course must be at least 3 semester hours.
The department may add or delete courses from the areas, and graduate courses and equivalent courses from other departments may be used to satisfy area requirements with permission. Graduate courses, in the 500-level series, can often count as specialization courses with Advisor's approval.
Unrestricted Electives
Additional courses to provide the BA minimum requirement of 120 semester hours or the BSECE minimum of 125 semester hours.
Specialization Electives
Computer Engineering*
*The sequence of COMP 182, COMP 215, and COMP 222 is recommended for the CE Area as these are prerequisites for many of the CS courses.
- COMP 321 Introduction to Computer Systems
- COMP 382 Reasoning About Algorithms
- COMP 430 Introduction to Database Systems
- ELEC 323 Principles of Parallel Programming
- ELEC 410 Secure and Cloud Computing
- ELEC 411 Microwave Engineering
- ELEC 414 Wireless Integrated Circuits and Systems
- ELEC 421 Operating Systems and Concurrent Programming
- ELEC 422 VLSI Systems Design
- ELEC 423 Digital Integrated Circuits
- ELEC 424 Mobile and Embedded System Design and Application
- ELEC 425 Computer Systems Architecture
- ELEC 426 Advanced Digital Integrated Circuits Design
- ELEC 429 Introduction to Computer Networks
- ELEC 434 Advanced High-Speed System Design
- ELEC 437 Introduction to Communication Networks
- ELEC 442 Introduction to Analog Integrated Circuits
- ELEC 450 Algorithmic Robotics
Data Science & Systems
- COMP 330 Tools and Models for Data Science
- DSCI 302 Data Science Tools and Models
- ELEC 403 Linear Algebra for Data Science
- ELEC 406 Linear Algebra for Data Science
- ELEC 430 Digital Communication
- ELEC 431 Digital Signal Processing
- ELEC 432 Mobile Bio-Behavioral Sensing
- ELEC 434 Advanced High-Speed System Design
- ELEC 436 Fundamentals of Control Systems
- ELEC 437 Introduction to Communication Networks
- ELEC 439 Data and Systems
- ELEC 440 Artificial Intelligence
- ELEC 441 Computational Imaging
- ELEC 445 Introduction to Digital Image and Video Processing
- ELEC 447 Introduction to Computer Vision
- ELEC 448 3D Vision: From Autonomous Cars to the Metaverse
- ELEC 475 Learning from Sensor Data
- ELEC 478 Intro to Machine Learning
- ELEC 498 Introduction to Robotics
- MECH 488 Design of Mechatronic Systems
- STAT 413 Introduction to Statistical Machine Learning
Neuroengineering
- ELEC 380 Introduction to Neuroengineering
- ELEC 435 Neural Interface Engineering Laboratory
- ELEC 438 Biomedical Optics II: Imaging
- ELEC 481 Electromagnetism and the Brain
- ELEC 483 Machine Learning and Signal Processing for Neuroengineering
- ELEC 488 Theoretical Neuroscience: From Cells to Learning Systems
- ELEC 489 Neural Computation
Photonics, Electronics, and Nano-devices
- ELEC 262 Introduction to Waves and Photonics
- ELEC 361 Quantum Mechanics for Engineers (or PHYS 311)
- ELEC 460 Physics of Sensor Materials and Nanosensor Technology
- ELEC 461 Solid State Physics (or PHYS 412)
- ELEC 462 Optoelectronic Devices
- ELEC 468 Introduction to Quantum Computing with Qiskit
- PHYS 302 Intermediate Electrodynamics
- PHYS 416 Computational Physics