Master of Science in Civil Engineering with Smart Cities and Urban Informatics Concentration (SCUI)

Cities now rely on data, modeling, and integrated system analysis to make decisions about transportation, utilities, and infrastructure performance. Engineers working in these environments see expectations rising as more of their work depends on interpreting complex information and understanding how systems interact.

The MSCE Smart Cities and Urban Informatics program helps you build the advanced technical and analytical skills needed to meet those expectations through applied work with real urban datasets and real projects.

You gain the depth, practical experience, and cross-disciplinary capability required to contribute at a higher level to the decisions that shape how cities function today and prepare for tomorrow.

This program is delivered on the Purdue Indianapolis campus.

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Curriculum Requirements:

Each student in the program must complete a total of 30 credits. The 30 credits are divided as follows:

  • A minimum of 18 credits from the College of Engineering
  • Core Courses (9 credits)
  • Major Courses (15 credits)
  • Capstone Projects (6 credits)

Core Courses

All students in the proposed major must take the following core courses totaling 9 credits:

  • 1 Urban Data Science course (3 credits)
  • 1 Resilience Engineering course (3 credits)
  • 1 Computational Statistics, Applied Math, and Data Visualization course (3 credits)

Major Courses

Major Courses are to be chosen from the following designated “Urban Data Science Methods”, “Urban Data Science Technologies”, and “Computational Statistics, Applied Math, and Data Visualization” course lists.

Each student should take at least 2 courses (3 credits each) in the three modules including core courses. All core courses in each module will be offered in Indianapolis.

Other courses will also be offered in Indianapolis after discussion with the faculty and incentive program.

Module 1. Urban Data Science Methods

  • CE 564: Data Science for Smart Cities (Core)
  • CE 597: Foundations of Network Models
  • CE 597: Image-based Sensing
  • CE 508: Geographic Information Systems
  • CE 507: Geospatial Data Analytics
  • CE 529: Smart Construction
  • CE 597: Asset Management of Underground Infrastructure
  • CE 597: Introduction to Applied Computer Vision in Engineering

Module 2. Urban Data Science Technologies

  • CE 569: Smart Logistics (core)
  • CE 597: Disaster Resilience and Society
  • AGRY 545: Remote Sensing of Land Resources
  • ASM 540: Geographic Information System (GIS) Applications, 3 credits
  • CE 529: Smart Construction (core)
  • CE 522: Computer Applications in Construction
  • CE 525: Built Environment Modeling
  • CE/POL 597: Sustainable and Resilient Systems: Behavior, Institutions, and Infrastructure (this can be integrated with “CE597 Disaster Resilience and Society” above)
  • CE 597: Sustainable Design
  • CE 597: Pipeline Condition Assessment and Integrity Management
  • CE 597: Development of Underground Space
  • CE 597: Intelligent Transportation Systems

Module 3. Computational Statistics, Applied Math and Data Visualization

  • STAT 51100: Statistical Methods
  • STAT 51200: Applied Regression Analysis
  • STAT 51400: Design of Experiments
  • MA 51100: Linear Algebra
  • MA 52700: Advanced Mathematics for Engineers and Physicists I
  • MA 52800: Advanced Mathematics for Engineers and Physicists II
  • CE 566: Network Models for Connected and Autonomous Vehicles
  • CE 508: Digital Mapping for Geographic Information Systems or CE 661: Algorithms in Transportation (core)
  • MGMT 57100: Data Mining
  • MGMT 57300: Optimization Modeling with Spreadsheets
  • MGMT 59000: Machine Learning
  • MGMT 59000: Visual Analytics
  • MGMT 59000: Analyzing Unstructured Data
  • MGMT 67000: Business Analytics
  • MGMT 67200: Advanced Business Analytics
  • ECON 57600: Statistical & Machine Learning
  • IE58000: Systems Simulation

Capstone Projects

  • Students interested in solving real world problems will work with a government agency, private sector, or Purdue professor to gain hands-on experience on solving a data science problem to solve sustainable cities issues (6 credits). This will be offered in Indianapolis.

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IMPORTANT: This program is part of the West Lafayette campus structure, but offered on-site in Indianapolis.

Students applying to Indianapolis should select the following on the application:

  • Campus: Select "West Lafayette (Main Campus)"
  • Proposed Graduate Major: Select "Civil Engineering"
  • Area of Interest: Select Professional Master's concentration CENG or SCUI
  • Degree Objective: MS in Civil Engineering
  • Location of Study: Indianapolis
  • Course Delivery: Residential

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