Data Science, Analytics and Engineering (Mechanical and Aerospace Engineering), MS

Program Overview

The MS in Data Science, Analytics and Engineering (Mechanical and Aerospace Engineering) at Arizona State University equips students with data science skills while enhancing their core expertise in mechanical and aerospace engineering. The program offers a comprehensive curriculum with required core courses, concentration areas, electives, and a culminating experience. Graduates are prepared for high-demand careers in data science, engineering, and related fields.

Program Outline

Degree Overview:

The MS in Data Science, Analytics and Engineering (Mechanical and Aerospace Engineering) at Arizona State University aims to equip students with the data science skills needed for the modern economy while also enhancing their core expertise in mechanical and aerospace engineering.

Program Objectives:

• Develop statistical and data science skills through interdisciplinary courses within and beyond engineering.
• Collaborate with colleagues to solve client-driven data science problems.
• Gain expertise in probability and statistics, machine learning, and data engineering.
• Apply knowledge to solve problems in aeronautics, astronautics, mechanics, energy systems, and controls.
• Combine data science and mechanical/aerospace engineering expertise for high-demand careers.

Outline:

Program Structure:

• 30 credit hours with one of the following options:
• Thesis
• Applied project course (MAE 593)
• Capstone course (FSE 570)
• Consists of required core courses, concentration courses, electives, and a culminating experience.
• Concentration areas focus on specific areas within mechanical/aerospace engineering.

Required Core Courses (9 credits):

• STP 502: Theory of Statistics II: Inference (3 credits)
• EEE 554: Probability and Random Processes (3 credits) or DSE 501: Statistics for Data Analysts (3 credits)
• CSE 511: Data Processing at Scale (3 credits) or CSE 512: Distributed Database Systems (3 credits) or IFT 530: Advanced Database Management Systems (3 credits)
• Choose one of the following:
• CSE 572: Data Mining (3 credits)
• CSE 575: Statistical Machine Learning (3 credits)
• EEE 549: Statistical Machine Learning: From Theory to Practice (3 credits)
• IEE 520: Statistical Learning for Data Mining (3 credits)
• IFT 511: Analyzing Big Data (3 credits)
• IFT 512: Advanced Big Data Analytics/AI (3 credits)
• MAE 551: Applied Machine Learning for Mechanical Engineers (3 credits)
• STP 550: Statistical Machine Learning (3 credits)

Concentration (9 credits):

• Selected in consultation with the program advisor.
• Examples include:
• Machine Learning
• Data Mining
• Artificial Intelligence
• Big Data Analytics
• Computer Vision
• Natural Language Processing

Electives (6-9 credits):

• Can be chosen from a wide variety of courses related to data science, mechanical engineering, and aerospace engineering.

Culminating Experience (3-6 credits):

• FSE 570: Data Capstone (3 credits)
• MAE 593: Applied Project (3 credits)

Careers:

Potential Career Paths:

• Data scientist
• Machine learning engineer
• Data analyst
• Artificial intelligence engineer
• Big data engineer
• Aerospace engineer
• Mechanical engineer
• Research scientist
• Technical consultant

Career Opportunities:

• Aircraft design
• Energy systems
• Manufacturing
• Product design
• Space systems
• Government agencies
• Research institutions
• Tech companies

Other:

• The program is designed for students with a background in mechanical engineering, aerospace engineering, or a related field.
• Students need a minimum cumulative GPA of 3.00 in their last 60 hours of their first bachelor's degree or applicable master's degree program.
• Relevant coursework or experience in Matlab, Python, SQL, R, linear algebra, and statistics is required.

Overall:

The MS in Data Science, Analytics and Engineering (Mechanical and Aerospace Engineering) at ASU offers a comprehensive and rigorous program for students who want to combine their expertise in engineering with the latest advances in data science. The program provides students with the skills and knowledge needed to pursue a successful career in a variety of high-demand fields.