Arizona State University Ira A. Fulton Schools of Engineering 6 courses 30 total credits
In the Master of Science program in artificial intelligence engineering with a concentration in chemical engineering, you combine advanced study in AI approaches with deep domain expertise in chemical engineering. The use of AI approaches, including machine learning, large language models, robotics and pattern recognition, is becoming widespread in chemical engineering. You can use such AI tools to develop new production processes, improved and more sustainable chemical products for human health, accelerated manufacturing, optimal nutritional profiles for bioprocesses, and many other applications. You learn how to develop and customize relevant AI approaches to chemical engineering problems. A core curriculum in AI engineering foundations, AI systems and tools, AI ethics and social responsibility, and data collection and evaluation for AI systems is complemented by chemical engineering-specific courses to ensure breadth and depth in AI and in chemical engineering.
| Required Core | 3 credits |
| AI Engineering Foundations | 3 credits |
| AI Systems and Tools | 3 credits |
| Data Collection and Evaluation for AI Systems | 3 credits |
| Concentration | 9 credits |
| Total Credits | 30 credits |
Required Core
| Code | Course Title | Credits |
|---|---|---|
| FSE 561 | Artificial Intelligence Ethics and Social Responsibility | 3 |
| Total Required Core | 3 credits | |
AI Engineering Foundations
AI Systems and Tools
Data Collection and Evaluation for AI Systems
Concentration
| Code | Course Title | Credits |
|---|---|---|
| CHE 533 | Transport Processes I | 3 |
| CHE 543 | Thermodynamics of Chemical Systems | 3 |
| CHE 544 | Chemical Reactor Engineering | 3 |
| Total Concentration | 9 credits | |
Culminating Experience (3 or 6 credit hours)
| Code | Course Title | Credits |
|---|---|---|
| CHE 593 | Applied Project | 3 |
| CHE 599 | Thesis | 6 |
Additional Curriculum Information
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