TECH 79 — Systems Under Stress: AI, Cybersecurity, and Critical Infrastructure
Quarter: Fall
Instructor(s): Anders Viden
Date(s): Oct 1—Nov 19
Class Recording Available: Yes
Class Meeting Day: Thursdays
Grade Restriction: No letter grade
Class Meeting Time: 6:00—7:30 pm (PT)
Tuition: $590
Refund Deadline: Oct 3
Unit(s): 1
Enrollment Limit: 45
Status: Registration opens Aug 17, 8:30 am (PT)
Quarter: Fall
Day: Thursdays
Duration: 8 weeks
Time: 6:00—7:30 pm (PT)
Date(s): Oct 1—Nov 19
Unit(s): 1
Tuition: $590
Refund Deadline: Oct 3
Instructor(s): Anders Viden
Grade Restriction: No letter grade
Enrollment Limit: 45
Recording Available: Yes
Status: Registration opens Aug 17, 8:30 am (PT)
Artificial intelligence is becoming deeply embedded in cloud platforms, data centers, energy systems, and other mission-critical infrastructure, often outpacing organizations’ ability to assess and manage risk. As automation expands, so do hidden dependencies, operational complexity, and new failure modes that traditional IT and security models were not designed to address.
Drawing on insights from recent cloud outages, cybersecurity breaches, and infrastructure failures—including the CrowdStrike outage—this course examines how AI, cybersecurity, and large-scale infrastructure interact in real operational environments. Students will explore how systems behave under stress and how technical decisions, organizational structures, and human judgment shape resilience, reliability, and recovery.
Designed for professionals across technology, operations, business, and policy roles, the course offers practical frameworks for evaluating risk and leading effectively in AI-enabled environments. Students will leave better equipped to make decisions in uncertain, high-stakes situations.
Drawing on insights from recent cloud outages, cybersecurity breaches, and infrastructure failures—including the CrowdStrike outage—this course examines how AI, cybersecurity, and large-scale infrastructure interact in real operational environments. Students will explore how systems behave under stress and how technical decisions, organizational structures, and human judgment shape resilience, reliability, and recovery.
Designed for professionals across technology, operations, business, and policy roles, the course offers practical frameworks for evaluating risk and leading effectively in AI-enabled environments. Students will leave better equipped to make decisions in uncertain, high-stakes situations.