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AI Engineering for Engineers: Designing Robust and Trustworthy AI Systems
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AI Engineering for Engineers: Designing Robust and Trustworthy AI Systems |
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Course Description: |
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This course introduces AI Engineering as an emerging engineering discipline focused on the robust and trustworthy deployment of AI in real-world systems. The course emphasizes engineering principles rather than algorithmic theory, equipping engineers with a practical framework for understanding AI-related risks, managing uncertainty, and maintaining accountability across the system lifecycle. |
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Learning Objectives: |
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Upon successful completion of this course, participants will be able to: • Explain why traditional software engineering methods are insufficient for AI-enabled systems
• Identify key risks and failure modes unique to AI-based engineering systems • Describe the core principles of trustworthy and robust AI engineering • Distinguish between solution-level, system-level, and technology-level AI engineering concerns • Understand how uncertainty and learning affect system safety and performance • Recognize the importance of verification, validation, and assurance throughout the AI lifecycle • Apply AI engineering concepts to safety-critical and infrastructure-based applications |
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