Stanford OnlineStanford CS230 | Autumn 2025 | Lecture 3: Full Cycle of a DL project
Episode Details
EPISODE INFO
- Released
- October 15, 2025
- Duration
- 1h 7m
- Channel
- Stanford Online
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai October 7, 2025 This lecture covers the full cycle of a DL project. To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs230-deep-learning To follow along with the course schedule and syllabus, visit: https://cs230.stanford.edu/syllabus/ More lectures will be published regularly. View the playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rNRRGdS0rBbXOUGA0wjdh1X Andrew Ng Founder of DeepLearning.AI Adjunct Professor, Stanford University’s Computer Science Department Kian Katanforoosh CEO and Founder of Workera Adjunct Lecturer, Stanford University’s Computer Science Department
SPEAKERS
Kian Katanforoosh
hostDeep learning educator and Stanford CS230 instructor, teaching end-to-end deep learning project workflow and deployment considerations.
EPISODE SUMMARY
In this episode of Stanford Online, featuring Kian Katanforoosh, Stanford CS230 | Autumn 2025 | Lecture 3: Full Cycle of a DL project explores deep learning projects: iterate fast, engineer data, monitor drift continuously AI projects differ from traditional software because behavior is driven by both code and unpredictable data, making development inherently iterative and empirical.
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