Environmental Decision Support
To support effective decisions that protect natural environmental systems, human health and sustainability, integrated approaches are being developed by teams of scientists, engineers and economists. These tools include advanced methods in high-performance computing, distributed sensing, data management, statistics, optimization, cost-benefit analysis, risk and decision analysis, risk communication, and public participation.
As a student in the Environmental Decision Support MS program you will learn essential elements of these methods, their assumptions, advantages and disadvantages, and their implementation and integration through class readings, assignments, and projects.
- 12-704 Probability and Estimation Methods for Engineering Systems
- 12-706 Civil Systems Investment Planning and Pricing
- 12-726 Mathematical Modeling of Environmental Quality Systems
- 12-768 Decision Analysis for Business and Policy
- 19-707 Multiple Criteria Decision Making
12-645 Smart Cities
12-712 Sustainable Engineering Principles
12-714 Environmental Life Cycle Assessment
- 12-735 Urban Systems Modeling
- 12-740 Data Acquisition
- 12-741 Data Management
12-746 Introduction to Python Prototyping for Infrastructure Systems
12-749 Climate Change Adaptation
12-774 Foundations of Intelligent Infrastructure Systems
12-780 Advanced Python for Infrastructure Systems
12-783 Geographic Information Systems
19-685 Engineering Optimization
24-787 Machine Learning and Artificial Intelligence for Engineer
24-784 Trustworthy AI Autonomy
24-789 Deep Learning for Engineers
18-661 Introduction to Machine Learning for Engineers
18-785 Data, Inference, and Applied Machine Learning
18-786 Introduction to Deep Learning
How to Apply
Ready to Apply?
All applications are submitted online through the CMU College of Engineering. For application information, visit our Admissions Information page.