PGFS 207 AI System Fundamentals & Architecture offers an in-depth look at the mechanisms behind intelligent machine behavior including its historical development, core applications, and evolving trends. The course examines the main elements of AI architecture, such as data processing, algorithms, and computing infrastructure. Students will apply their skills and understanding to real-world scenarios.
Prerequisites: PGFS 205 with a minimum grade of 60%
Accessibility Services Notice
Students who would like an academic accommodation and who have a documented disability should contact Accessibility Services, if they have not already done so.Course Details| Total number of weeks | 4 |
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| Total Credits | |
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| Total Hours | 60 |
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Typical hours per week breakdown| Lecture | 11.25 |
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| Lab (lab, field, computer) | 3.75 |
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Learning Outcomes
Upon successful completion of this course, the learner will be able to:
- Describe the key milestones and breakthroughs in the history and current applications of AI
- Explain the essential components of AI architecture, such as data management, algorithm selection, and computing infrastructure, and their roles in AI system design
- Classify and compare different types of machine learning algorithms, such as supervised, unsupervised, and reinforcement learning, and apply them to specific use cases
- Distinguish between structured, unstructured, and semi-structured data types and their suitability for different AI applications, such as natural language processing and computer vision
- Assess the advantages and disadvantages of different computing infrastructure options for AI, such as cloud computing, edge computing, and distributed systems, based on cost, performance, and scalability
- Design and implement AI systems for real-world problems, leveraging the principles of AI architecture, such as data preprocessing, algorithm selection, and model evaluation, and using appropriate computing infrastructure and data management techniques
Grading Table
Standard Academic and Career Programs Grading Table
| Percentage |
Letter Grade |
GPA |
| 90-100 |
A+ |
4.33 |
| 85-89 |
A |
4.00 |
| 80-84 |
A- |
3.67 |
| 76-79 |
B+ |
3.33 |
| 72-75 |
B |
3.00 |
| 68-71 |
B- |
2.67 |
| 64-67 |
C+ |
2.33 |
| 60-63 |
C |
2.00 |
| 55-59 |
C- |
1.67 |
| 50-54 |
P |
1.00 |
| 0-49 |
F |
0.00 |
| |
DNW |
0.00 |
See the Academic Calendar for General Information including how to withdraw from course(s) and other regulations.
Disclaimer
Information contained in this course outline is correct at the time of publication. Content of the course is revised on an ongoing basis to ensure relevance to changing educational, employment and market needs. The instructor will endeavor to provide notice of changes to students as soon as possible. The instructor reserves the right to add or delete material from courses.