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Fall Registration Opens Aug 17
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TECH 41 — Building AI Products Through Rapid Prototyping

Quarter: Fall
Instructor(s): Ata Tahiroglu
Duration: 8 weeks
Location: Online
Date(s): Sep 28—Nov 16
Class Recording Available: Yes
Class Meeting Day: Mondays
 
Class Meeting Time: 7:00—8:30 pm (PT)
Tuition: $590
   
Refund Deadline: Sep 30
 
Unit(s): 1
   
Enrollment Limit: 55
  
Status: Registration opens Aug 17, 8:30 am (PT)
 
Quarter: Fall
Day: Mondays
Duration: 8 weeks
Time: 7:00—8:30 pm (PT)
Date(s): Sep 28—Nov 16
Unit(s): 1
Location: Online
 
Tuition: $590
 
Refund Deadline: Sep 30
 
Instructor(s): Ata Tahiroglu
 
Enrollment Limit: 55
 
Recording Available: Yes
 
Status: Registration opens Aug 17, 8:30 am (PT)
 
 
The best way to build AI products isn’t to spend months in development—it’s to prototype rapidly, test early, and iterate often. This course teaches professionals how to turn AI ideas into working prototypes that solve real business challenges. Students will learn to identify high-impact use cases, scope minimum viable products, and prototype AI solutions using prompt engineering, no-code platforms, and open-source models. Hands-on exercises cover rapid validation techniques, ethical guardrails, and practical deployment strategies. Real-world case studies from finance, consumer tech, and B2B SaaS illustrate common challenges and proven strategies. By the end of the course, students will have a repeatable AI prototyping framework and a working prototype of their own. This course is ideal for product managers, entrepreneurs, business leaders, and technical professionals seeking to move confidently from concept to practical, scalable AI solutions.

No coding or data science expertise is required. This course relies on the use of an external, third-party tool that is not managed or supported by Stanford. Students must purchase their own tool subscriptions and can expect to spend $25–$100 per month. Please see the course syllabus for more details.

ATA TAHIROGLU
Senior Director of Product Management, Salesforce

Ata Tahiroglu has more than a decade of experience in tech, specializing in launching AI-powered products at scale. Prior to joining Salesforce, he led cross-functional AI/ML initiatives at Apple and was head of product at M Science, where he led the development of ML-based platforms like Swipe and Impact. He lectures at Product School on AI product management, and he has built NLP tools for equity trading desks, led teams of data scientists and engineers, and consulted on fintech product launches.