Data Science in Engineering Analytics and Decision-Making (Minor)
The Data Science in Engineering Analytics and Decision-Making minor is a 15 credit interdisciplinary credential that offers a path towards developing essential skills in data science with depth in Industrial and Systems Engineering (ISE) content. Students who pursue this minor will have the opportunity to learn from data science instructors, practitioners, and engineering faculty in industry and academia, alongside their peers from various colleges. Students will pursue courses in data management, communication, applications, ethics, engineering, and more, in addition to choosing from electives of interest.
Contact
Data Science and AI Academy
Plan Requirements
| Code | Title | Hours |
|---|---|---|
| Required DSA Courses: At least one course from each category | 6 | |
| Categories and Corresponding Category Numbers (in parentheses) | ||
Data Management & Analysis (1) | ||
Data Communication (2) | ||
Ethics, Policy, & Privacy (3) | ||
Machine Learning and AI (4) | ||
Electives or Internships & Capstones (5) | ||
| Introduction to R/Python for Data Science ((5), Students cannot count both 顿厂础听201 and 滨厂贰听135 towards the minor)) | ||
| Introduction to Data Visualization (2) | ||
| Data Communication (2) | ||
| Introduction to AI Ethics (3) | ||
| Data Science for Social Good (3) | ||
| Introduction to Data Science for Cybersecurity (3) | ||
| Measuring Success (1) | ||
| Data Wrangling and Web Scraping (5) | ||
| Exploratory Data Analysis for Big Data (1) | ||
| Data Internship Preparation for Social Impact (5) | ||
| Exploring Machine Learning (4) | ||
| Predictive Analytics for Improving Services (1) | ||
| Introduction to APACHE Spark Using Big Datasets (1) | ||
| R for Biological Research (1 ) | ||
| Introductory Special Topics in Data Science (see semesterly list of special topics courses accepted within a category) | ||
| Special Topics in Data Science (see semesterly list of special topics courses accepted within a category) | ||
| Graduate Special Topics in Data Science (see semesterly list of special topics courses accepted within a category) | ||
| Required Depth Courses: At least three courses from the following | 9 | |
| Smart Infrastructure Systems | ||
| Civil Engineering Systems | ||
| Introduction to Numerical Methods for Civil Engineers | ||
| Current Topics in Civil Engineering (颁贰听497 special topics applications to this minor require approval) | ||
| Computer Methods and Applications | ||
| Computer-Based Modeling for Industrial Engineering (Students cannot count both 顿厂础听201 and 滨厂贰听135 towards the minor) | ||
| Deterministic Models in Industrial Engineering (Requires 滨厂贰听135; or Instructor permission and 顿厂础听201; or Instructor permission and introductory knowledge of Python programming) | ||
| Database Applications in Industrial & Systems Engineering | ||
| Python Programming for Industrial & Systems Engineers | ||
| Data Analytics for Industrial Engineering | ||
| Applications of Data Science in Healthcare | ||
| R Coding for Data Management and Analysis | ||
| Introduction to Machine Learning | ||
| NOTE 1: Students in the ISE major and ISE minor cannot count the following courses towards the data science minor: 滨厂贰听135, 滨厂贰听361. | ||
| NOTE 2: Students pursuing multiple Data Science and AI Academy credentials must have at least 2 distinct 1-credit DSA courses and 2 distinct 3-credit depth courses between any two credentials (8 distinct credits total). | ||
| NOTE 3: Courses already used to satisfy two or more credit requirements cannot also be used to satisfy the data science minor. | ||
| Total Hours | 15 | |