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Main
UQU Programs
Science in Artificial Intelligence

AI System Design

AI3104
3 hours English

AI System Design

AI System Design
SE1201 Foundations of Software Engineering
3 hours One requisite
AI3201 Machine Learning
3 hours Two requisites
1 Introduction to AI system design: overview, principles, and the AI lifecycle
2 Solution architectures for AI systems: components, scalability, and reliability
3 Integration of AI components: ML models, foundation models (e.g., GPT), and rule-based systems
4 Deployment patterns and strategies: cloud, edge, and hybrid deployment models
5 Challenges in AI system design: scalability, latency, fault tolerance, and optimization
6 Ethics and explainability in AI: addressing bias, fairness, transparency, and ethical considerations
7 Evaluating AI systems: metrics for performance, robustness, and fairness
8 Solution architecture document (SAD): structure, purpose, and creation of an SAD for AI systems
1.1 Mapped to: K1

Understand the principles and best practices for designing, building, and integrating AI systems.

Teaching Strategy Lectures, discussions
Assessment Methods Exams
1.2 Mapped to: K2

Describe solution architectures for scalable and reliable AI systems.

Teaching Strategy Lectures, discussions
Assessment Methods Exams
1.3 Mapped to: K2

Identify deployment patterns and strategies for AI systems.

Teaching Strategy Lectures, discussions
Assessment Methods Exams
2.1 Mapped to: S1

Analyze deployment patterns and strategies to address scalability, latency, and reliability challenges.

Teaching Strategy Lectures, discussions
Assessment Methods Exams, assignments, Project
2.2 Mapped to: S2

Evaluate deployment challenges and propose effective solutions for real-world applications.

Teaching Strategy Lectures, discussions
Assessment Methods Exams, assignments, Project
2.3

Design and document scalable, production-ready AI systems through hands-on projects and case studies.

Teaching Strategy Project mentorship, discussions
3.1 Mapped to: V1

Demonstrate professional responsibility and ethical behavior in the design and deployment of AI systems.

Teaching Strategy Lectures, discussions
Assessment Methods Assignments, Project
3.2 Mapped to: V2

Recognize and address the social and environmental impact of AI technologies.

Teaching Strategy Lectures, discussions
Assessment Methods Assignments, Project
3.3

Exhibit autonomy and accountability in managing AI system design projects, ensuring scalability, reliability, and fairness.

Teaching Strategy Lectures, discussions
Assessment
Weight
Programming assignments
20%
Quizzes
10%
Midterm
30%
Final Project
40%
Total
100%