Online Master of Engineering (MEng)

MENG 400. Engineering Law | 4 Credit Hours 
Overview of the legal system. Legal principles affecting the engineering profession. Professional ethics in engineering. Intellectual property law. Basic contract and tort principles. Environmental law.

MENG 401. Engineering Management | 4 Credit Hours 
This course will cover the project lifecycle for successful and effective managing of the engineering projects in accordance with the theories, insights, and principles of the Project Management Body of Knowledge. The course will elaborate on understanding the sophisticated dynamics of Engineering Management through expanding on project constraints, such as scope, cost, time, risk, quality, and so forth as well as providing details on the means and methods to enable engineering managers to attain a better and multi-dimensional understanding of the project lifecycle, and the necessary skill sets to efficiently manage the engineering enterprise.

MENG 404. Math Fundamentals for AI Engineers and Data Scientists | 4 Credit Hours 
MENG 404 sets the stage for the ML and AI topics that students will see throughout the MENG program. While recalling important mathematical and statistical topics, MENG 404 will also familiarize students with Python which has become an industry standard for ML and AI calculations. Also, while refreshing the students’ background material they will be introduced to applications where that material will be covered more thoroughly and further applied in their upcoming MENG courses.

MENG 407. Innovation Tools and Methods | 4 Credit Hours 
Working engineers need to know about Innovation Tools & Methods because these are the interdisciplinary business techniques that ensure that the problems we choose to solve and the products we make to solve them actually meet the needs of the human beings who use them (and thus achieve success in the marketplace). Most engineering have heard about the importance of figuring out what people actually need, but this course teaches the concrete techniques are currently accepted best practices for doing so.

MENG 416. Intro to Machine Learning | 4 Credit Hours 
This course gives an introduction to common machine learning tasks (e.g., classification, density estimation, clustering) and some of the successful machine learning techniques and broader paradigms that have been developed for these tasks. The course is programming-intensive and a large emphasis will be placed on tying existing machine learning techniques to specific real-world applications through hands-on experience. By taking the course, students will be able to explain the mechanism of different common machine learning task settings and be able to apply existing machine learning tools to a broad range of data sets. They will also be able to identify appropriate problem formulations and machine learning techniques for framing and solving predictive data analysis problems, along with evaluating and measuring the performance of different learning techniques on predictive tasks. Prerequisite: MENG 404. Formerly CS 412.

MENG 417. Intro to Deep Neural Networks | 4 Credit Hours 
Deep Neural Networks (DNN) are the leading pattern recognition methods in AI. They are very successful at correctly classifying a wide range of input data, including images, video, speech, text, and they successfully model consumer preferences. We now use DNNs in our daily life ranging from automated telephone systems to user recommendations on online shopping and entertainment applications (Amazon, Netflix). DNNs can also automatically generate graphics, natural looking images, natural sounding speech and text.
Formerly ECE 491.

MENG 418. Image Analysis and Computer Vision I | 4 Credit Hours  
Image formation, geometry and stereo. Two-dimensional image analysis by fourier and other 2-D transforms. Image enhancement, color, image segmentation, compression, feature extraction, object recognition. Formerly ECE 415.

MENG 419. Artificial Intelligence | 4 Credit Hours 
MENG 419 will provide students with experience with a range of AI tools including search, reinforcement learning, probabilistic models, and game theory with the goals of understanding their strengths and limitations and being able to apply then to problems they may face during their career. Formerly CS 411.

MENG 420. Natural Language Processing | 4 Credit Hours 
In the class, we will study some background theory and focus on engineering techniques and libraries to allow computers interact with humans in a natural language. We will also cover topics such as extracting facts and concepts from text, and other applications of NLP to mainstream applications. Formerly CS 421.

Yes — this program is ideal for working professionals, with accelerated eight-week terms and full- or part-time pacing options.

The online MEng is designed for individuals with bachelor’s degrees in engineering, as well as closely related fields like biology, chemistry, computer science, mathematics, or physics.

View our full list of admission requirements, including math and science credits, GPA, and recommended work experience.

No — GRE scores are not required for admission to the online Master of Engineering with a concentration in AI and ML program.

Contact our enrollment specialists with any questions about the program, admission requirements, or the application process.