Computer Science Minor

The department of Electrical Engineering offers a minor in Computer Science. Students seeking a minor in Computer Science must complete Data Structures & Algorithms I (ECE 264), Data Structures & Algorithms II (ECE 365), or a course selected from a list of alternative courses (see below), and 12 additional credits at the 300 or 400 level from a list of approved courses. At most six credits of 300 level courses that are required in the major can be applied toward the requirements for the Computer Science Minor. For students receiving both the Math Minor and the Computer Science Minor, at most three credits can be used to satisfy both minor requirements. Any 400 level courses used to fulfill the requirements for the Computer Science Minor cannot be used to fulfill the requirements for the Master of Engineering degree. The minimum cumulative GPA for the set of courses (including ECE 264) used to fulfill the requirements for the Computer Science Minor is 3.0.

Courses That Can Substitute for ECE 365, Data Structures & Algorithms II

All courses are 3 credits unless indicated otherwise.

ECE 414 Machine Learning*

ECE 462 Computer Graphics

ECE 464 Databases

ECE 465 Cloud Computing

ECE 467 Natural Language Processing

ECE 468 Computer Vision

ECE 469 Artificial Intelligence

ECE 474 Frequentist Machine Learning

ECE 475 Bayesian Machine Learning

*Course no longer offered.

Computer Science Minor

All courses are 3 credits unless indicated otherwise.

ECE 303 Computer Networks

ECE 305 Computer Security**

ECE 311 Hardware Design

ECE 323 Embedded Systems

ECE 357 Operating Systems

ECE 365 Data Structures & Algorithms II (2 credits)

ECE 366 Software Engineering

CS/ECE 371 Data Visualization

ECE 414 Machine Learning**

ECE 417 Custom Design of DSP Hardware

ECE 453 Advanced Computer Architecture

ECE 455 Cybersecurity

ECE 462 Computer Graphics

ECE 464 Databases

ECE 465 Cloud Computing

ECE 466 Compilers

ECE 467 Natural Language Processing

ECE 468 Computer Vision

ECE 469 Artificial Intelligence

ECE 474 Bayesian Machine Learning

ECE 475 Frequentist Machine Learning

ECE 478 Financial Signal Processing

CE 422 Finite Element Methods

CE 483 Building Information Modeling

ChE 352 Process Simulation

ChE 488 Convex Optimization

EID 377 Distributed AI & Blockchain

ME 353 Mechatronics

ME 412 Autonomous Mobile Robots

ME4 58 Industrial Robots

MA 336 Statistics

MA 352 Discrete Math

MA 402 Numerical Analysis

**Course no longer offered.

Courses with a “selected topics” or “research problem” designation can be considered, on a case by case basis, for the Computer Science minor. When such courses are not offered by the Electrical Engineering Department, the department that offers the course would be consulted in order to determine if they would qualify for the Computer Science minor. Recent examples:

  • Computational Graphs (Deep Learning)
  • Machine Learning and Art
  • Data Science for Social Good
  • Founded by inventor, industrialist and philanthropist Peter Cooper in 1859, The Cooper Union for the Advancement of Science and Art offers education in art, architecture and engineering, as well as courses in the humanities and social sciences.

  • “My feelings, my desires, my hopes, embrace humanity throughout the world,” Peter Cooper proclaimed in a speech in 1853. He looked forward to a time when, “knowledge shall cover the earth as waters cover the great deep.”

  • From its beginnings, Cooper Union was a unique institution, dedicated to founder Peter Cooper's proposition that education is the key not only to personal prosperity but to civic virtue and harmony.

  • Peter Cooper wanted his graduates to acquire the technical mastery and entrepreneurial skills, enrich their intellects and spark their creativity, and develop a sense of social justice that would translate into action.