Data Science, Analytics and Engineering (Sustainable Engineering and Built Environment), MS

Program Overview

This MS program in Data Science, Analytics, and Engineering (Sustainable Engineering and Built Environment) equips students with advanced data science skills while enhancing their expertise in sustainability and the built environment. The curriculum combines high-demand courses with real-world projects, focusing on data science, sustainability, and problem-solving within a data science framework. Graduates are prepared for data science roles in sustainable engineering and the built environment, with opportunities for STEM-OPT extension and leadership roles in data-driven projects.

Program Outline

Data Science, Analytics and Engineering (Sustainable Engineering and Built Environment), MS

Degree Overview:

This program aims to equip students with advanced data science skills while enhancing their expertise in sustainable engineering and the built environment. Combining high-demand courses with real-world client-driven projects, the curriculum focuses on:

• Data science: Probability and Statistics, Machine Learning, Data Mining, Data Engineering
• Sustainability and Built Environment: Specific topics within these fields

Objectives:

• Prepare graduates for data science roles within the context of sustainability and the built environment.
• Foster critical thinking and problem-solving skills within a data science framework.

Outline:

Program Duration and Credits:

• 30 credits and thesis, or
• 30 credits including mandatory capstone course (FSE 570)

Required Core (9 credit hours):

• STP 502 Theory of Statistics II: Inference
• EEE 554 Probability and Random Processes
• CSE 575 Statistical Machine Learning
• One additional course from a list of Machine Learning, Big Data Analytics, and Artificial Intelligence-focused courses

Concentration (9 or 12 credit hours):

• CEE 501 Machine Learning Techniques in Civil Engineering
• Three additional courses from an approved list

Electives (6 or 9 credit hours):

• Choice of courses to further explore specific interests and knowledge areas

Culminating Experience (3 or 6 credit hours):

• Completion of a thesis or capstone project demonstrating acquired knowledge and skills.

Assessment:

• Continuous assessment through assignments, projects, and examinations in individual courses.
• Thesis or capstone project to demonstrate mastery of data science and sustainable engineering concepts.

Teaching:

• Instruction by faculty with expertise in data science, sustainable engineering, and the built environment.
• Use of diverse teaching methods including lectures, hands-on projects, group work, and case studies.
• Opportunity to work on real-world client-driven projects to gain practical experience.

Careers:

• Positions requiring expertise in data analysis and application within sustainable engineering and the built environment, such as:
• Civil, Environmental, Sustainable, or Construction Management Engineer with data science skills.
• Other relevant fields including building, construction, environmental remediation, transportation, and water treatment.

Other:

• This program is eligible for the STEM-OPT extension, allowing international students to extend their F-1 visa and gain valuable work experience in the U.S.
• Graduates are well-equipped for leadership roles within data-driven projects and organizations within sustainable engineering and the built environment.