The imagedeep.io series serves to bridge the knowledge gap between medical imaging and AI education.

It was co-founded and is co-instructed by:

Mazen Zawaideh, MD. Chief Radiology Resident and imagedeep.io co-instructor.

David Haynor, MD, Ph.D. Professor of Neuroradiology and imagedeep.io co-instructor.

Nathan Cross, MD. Assistant Professor of Neuroradiology and imagedeep.io co-instructor.

To learn more, visit www.imagedeep.io

MIT Introduction to Deep Learning 6.S191: Lecture 2
Recurrent Neural Networks
Lecturer: Ava Amini
** New 2025 Edition **

For all lectures, slides, and lab materials: http://introtodeeplearning.com

Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!

MIT Introduction to Deep Learning 6.S191: Lecture 1
*New 2025 Edition*
Foundations of Deep Learning
Lecturer: Alexander Amini

For all lectures, slides, and lab materials: http://introtodeeplearning.com/

Subscribe to stay up to date with new deep learning lectures at MIT, or follow us on @MITDeepLearning on Twitter and Instagram to stay fully-connected!!

For more information about Stanford's flexible graduate programs visit: https://learn.stanford.edu/YouTube-Grad.html

If you're interested in deepening your expertise and progressing your professional skill set, why not look into the graduate course and program options offered by Stanford Online? During our online information session, you'll discover the range of graduate opportunities available to you, what you can look forward to, and essential information to help you make an informed decision prior to enrollment.

The session includes:
Graduate Course Overview: Here’s what you can expect
Key information about applying and enrolling
Audience Q&A

Explore Stanford Online's graduate education options: https://online.stanford.edu/graduate-education

#gradschool #graduateprogram #onlineeducation

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

November 21, 2025
This lecture covers:
• LLM-as-a-judge overview
• Best practices and benefits
• Biases and pitfalls

To follow along with the course schedule and syllabus, visit: https://cme295.stanford.edu/syllabus/

Chapters:
00:00:00 Introduction
00:07:08 Inter-rater agreement metrics
00:18:24 Rule-based metrics
00:21:00 METEOR, BLEU ROUGE
00:28:00 LLM-as-a-judge
00:33:44 Structured outputs
00:36:48 Variants
00:38:47 Position, verbosity, self-enhancement bias
00:47:22 Best practices
00:54:06 Factuality
01:00:15 Agent evaluation
01:23:50 Benchmarks
01:25:12 Knowledge with MMLU
01:29:34 Reasoning AIME, PIQA
01:33:57 Coding with SWE-bench
01:36:15 Safety with HarmBench
01:40:51 Agents with Tau-Bench

Afshine Amidi is an Adjunct Lecturer at Stanford University.

Shervine Amidi is an Adjunct Lecturer at Stanford University.

View the course playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

(March 29, 2010) Stanford professor Robert Sapolsky gave the opening lecture of the course entitled Human Behavioral Biology and explains the basic premise of the course and how he aims to avoid categorical thinking.

Stanford University
http://www.stanford.edu

Stanford Department of Biology
http://biology.stanford.edu/

Stanford University Channel on YouTube
http://www.youtube.com/stanford

For more information about Stanford's online Artificial Intelligence programs visit: https://stanford.io/ai

To learn more about enrolling in this course visit: https://online.stanford.edu/co....urses/cs336-language

To follow along with the course schedule and syllabus visit: https://stanford-cs336.github.io/spring2025/

Percy Liang
Associate Professor of Computer Science
Director of Center for Research on Foundation Models (CRFM)

Tatsunori Hashimoto
Assistant Professor of Computer Science
For more information about Stanford's online Artificial Intelligence programs visit: https://stanford.io/ai

To learn more about enrolling in this course visit: https://online.stanford.edu/co....urses/cs336-language

To follow along with the course schedule and syllabus visit: https://stanford-cs336.github.io/spring2025/

Percy Liang
Associate Professor of Computer Science
Director of Center for Research on Foundation Models (CRFM)

Tatsunori Hashimoto
Assistant Professor of Computer Science

View the entire course playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

View course details: https://online.stanford.edu/co....urses/xcs224r-deep-r

April 2, 2025
This lecture covers:
• Class introduction
• Markov Decisions Processes
• Why study deep reinforcement learning?
• Intro to modeling behavior and reinforcement learning

To learn more about enrolling in the graduate course, visit: https://online.stanford.edu/co....urses/cs224r-deep-re

To follow along with the course schedule and syllabus, visit:
https://cs224r.stanford.edu/

Chelsea Finn
Assistant Professor in Computer Science and Electrical Engineering at Stanford University and co-founder of Pi.

Statistical Learning, featuring Deep Learning, Survival Analysis and Multiple Testing

Trevor Hastie, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.ed....u/people/trevor-j-ha

Robert Tibshirani, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.ed....u/people/robert-tibs

Jonathan Taylor, Professor Statistics at Stanford University - https://statistics.stanford.ed....u/people/jonathan-ta

You are able to take Statistical Learning as an online course on EdX, and you are able to choose a verified path and get a certificate for its completion. You can choose to take the course in R (https://www.edx.org/course/statistica) or in Python (https://www.edx.org/learn/data....-analysis-statistics

For more information about courses on Statistics, you can browse our Stanford Online Catalog: https://stanford.io/3QHRi72

Is it ever too late to expand your knowledge of computer science and AI? Mehran Sahami, Professor and Chair of the Computer Science Department at Stanford University, addresses this and other questions as he shares his expertise.

Learn about Code in Place:
https://codeinplace.stanford.edu/

Learn about our Artificial Intelligence Courses and Programs:
https://online.stanford.edu/ar....tificial-intelligenc

Learn about our Computer Science & Security Programs:
https://online.stanford.edu/co....mputer-science-secur

For more information about Stanford's online Artificial Intelligence programs visit: https://stanford.io/ai

This lecture covers:
1. The course (10 mins)
2. Human language and word meaning (15 mins)
3. Word2vec introduction (15 mins)
4. Word2vec objective function gradients (25 mins)
5. Optimization basics (5 mins)
6. Looking at word vectors (10 mins or less)

Key learning: The (astounding!) result that word meaning can be represented rather
well by a (high-dimensional) vector of real numbers

To learn more about enrolling in this course visit: https://online.stanford.edu/co....urses/cs224n-natural

To follow along with the course schedule and syllabus visit: hhttps://web.stanford.edu/class..../archive/cs/cs224n/c

Professor Christopher Manning
Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science
Director, Stanford Artificial Intelligence Laboratory (SAIL)

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/co....urses/cs230-deep-lea

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/playli....st?list=PLoROMvodv4r

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

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

February 6, 2026
This lecture covers:
• A randomized controlled trial examining the impact of AI-mediated feedback on students' disciplinary writing performance and learning
• An introduction to and evaluation of FeedbackWriter
• How knowledge engineering can enhance cognitive fidelity and enable reliable feedback generation

To follow along with the seminar schedule, visit: https://hci.stanford.edu/

Xu Wang is an Assistant Professor in Computer Science and Engineering and the School of Information (By courtesy) at the University of Michigan.

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai

September 23, 2025
This lecture covers:
1. Class introduction
2. Examples of deep learning projects
3. Course details

To learn more about enrolling in this course, visit: https://online.stanford.edu/co....urses/cs230-deep-lea

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/playli....st?list=PLoROMvodv4r

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

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai

November 11, 2025
This lecture covers agents, prompts, and RAG.

To learn more about enrolling in this course, visit: https://online.stanford.edu/co....urses/cs230-deep-lea

Please follow along with the course schedule and syllabus: https://cs230.stanford.edu/syllabus/

More lectures will be published regularly.
View the playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

NOTE: There was no class on November 4, 2025 (Lecture 7). The previous lecture is Lecture 6.

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

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

December 5, 2025
This lecture covers:
• Recap
• Trending topics
• Closing thoughts

To follow along with the course schedule and syllabus, visit: https://cme295.stanford.edu/syllabus/

Chapters:
00:00:00 Introduction
00:01:12 Transformer
00:06:35 Transformer-based models & tricks
00:11:17 Large Language Models
00:15:05 LLM training
00:24:09 LLM tuning
00:29:41 LLM reasoning
00:38:37 Agentic LLMs (RAG, tool calling)
00:44:09 LLM evaluation
00:48:57 Vision Transformer
01:04:02 Diffusion-based LLMs
01:23:38 Closing thoughts
01:50:16 Thank you!

Afshine Amidi is an Adjunct Lecturer at Stanford University.

Shervine Amidi is an Adjunct Lecturer at Stanford University.

View the course playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r