Stanford CS230 | Autumn 2025 | Lecture 5: Deep Reinforcement Learning

ℹ️ EPISODE INFO

Released

October 31, 2025

Duration

1h 45m

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 21, 2025 This lecture covers deep reinforcement learning. 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

  host

  Co-instructor for Stanford CS230 (Deep Learning) and CEO/co-founder of Workera.

🧾 EPISODE SUMMARY

In this episode of Stanford Online, featuring Kian Katanforoosh, Stanford CS230 | Autumn 2025 | Lecture 5: Deep Reinforcement Learning explores deep reinforcement learning fundamentals, deep Q-networks, and RLHF for LLMs Reinforcement learning (RL) is framed as learning good sequences of decisions from experience, especially when labels are delayed and supervised learning targets are ill-defined (e.g., Go).

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