Engineering Science MS: AI and Data Innovation Focus

The Engineering Science MS with a focus on AI and Data Innovation bridges the power of artificial intelligence and data science to prepare the next generation of engineers, innovators and problem solvers. Students will get a balanced foundation across statistical learning, machine learning, data analytics, and applied AI to equip them with the skills to design, develop and apply intelligent systems that transform data into actionable insights.

Required Core (18 credits)

EAS 501LEC - Introduction to Numerical Mathematics for Computing and Data Science Credits: 3
EAS 502LEC - Introduction to Probability Theory for Data Science Credits: 3
EAS 508LEC - Statistical Learning and Data Mining I Credits: 3
EAS 510LEC - Basics of Artificial Intelligence Credits: 3
EAS 574LEC - Intro Machine Learning Credits: 3
EAS 587LEC - Data Intensive Computing Credits: 3

Electives (9-12 credits)

CDA 500LEC - Special Topics Credits: 1 - 3
CSE 531LEC - Algorithms Anal & Dsgn 1 Credits: 3
CSE 535LEC - Information Retrieval Credits: 3
CSE 546LEC - Reinforcement Learning Credits: 3
CSE 555LEC - Intro Pattern Recognition Credits: 3
CSE 567LEC - Computational Linguistics Credits: 3
CSE 573LEC - Comp Vision & Image Proc Credits: 3
CSE 601LEC - Data Mining and Bioinformatics Credits: 3
CSE 635LEC - NLP and Text Mining Credits: 3
CSE 674LEC - Advanced Machine Learning Credits: 3
CSE 676LEC - Deep Learning Credits: 3
EAS 509LEC - Statistical Learning and Data Mining II Credits: 3

Culminating Experience: Exam, Project, or Internship (0-3 credits)

For students completing EXAM:
EAS 559TUT - Engineering Science Capstone Credits: 0
For students completing PROJECT:
EAS 560TUT - Data Science Project Credits: 1 - 3
EAS 563TUT - Artificial Intelligence Capstone Credits: 1 - 3
For students completing INTERNSHIP:
- EAS XXX - Course number and title pending Credits: 3

Total Credit Hours: 30

3.0 Degree GPA required

Program Learning Outcomes (PLOs)

Ability to demonstrate domain expertise with engineering methods and tools
Ability to develop relevent programming abilities
Ability to use basic engineering concepts flexibly in a variety of contexts
Ability to apply domain-specific concepts and methods to solve problems in real-world contexts and will communicate these solutions effectively

SED Statement

This program is officially registered with the New York State Education Department (SED).