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May 16, 2025 by Kevin Lee (khlee2)
May 16, 2025 by Kevin Lee (khlee2)
Viewing outcome relationships between
EECE 682 - Computer Control of Dynamic Systems
and
319 - Master of Science in Artificial Intelligence Engineering
Last approved:
Fri, 16 May 2025 20:44:31 GMT
Last edit:
Fri, 16 May 2025 20:44:28 GMT
Program Code
319 - Master of Science in Artificial Intelligence Engineering
Course Code
EECE 682 - Computer Control of Dynamic Systems
Learning Outcomes Relationships
PLO 3: Ensure they can communicate their technical ideas and findings effectively through clear written, oral, and visual presentations. This underscores the importance of professional communication in the multidisciplinary AI field.
PLO 5: Be prepared to excel in doctoral programs within artificial intelligence, electronics, computer engineering and science, or closely related disciplines. This indicates the program's rigorous academic standards and its potential to serve as a strong foundation for further academic pursuits.
PLO 6: Demonstrate the ability to identify and formulate precise requirements for complex intelligent systems. This focuses on the critical skill of defining the specific needs for advanced AI systems.
PLO 7: Exhibit the capacity to analyze and prioritize diverse requirements and constraints to determine the essential features of advanced intelligent systems. This emphasizes the ability to make informed decisions in the design process of AI systems.
PLO 8: Possess the skill to design and implement intelligent systems effectively by utilizing appropriate AI and machine learning techniques to meet clearly defined specifications. This outcome focuses on the practical application of AI principles in the creation of functional systems.
PLO 10: Demonstrate the aptitude to apply current AI technologies and utilize modern computational tools effectively to solve complex engineering and computational problems. This emphasizes the practical application of contemporary AI tools and techniques in relevant contexts.
PLO 12: Function effectively as collaborative members or leaders within teams engaged in activities relevant to the field of artificial intelligence. This emphasizes the inherently collaborative nature of AI development and research.
Key: 289