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

October 28, 2025
This lecture provides walkthroughs of examples of AI projects and making day-to-day decisions in building AI systems.

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

NOTE: There was no class on November 4, 2025 (Lecture 7). The next lecture is Lecture 8.

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

January 9, 2026
This lecture covers:
• How the ongoing integration of LLMs into our social worlds is creating new risks and opportunities
• Best practices for designing rehabilitative bots

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

Jeremy Foote is an Assistant Professor in the Brian Lamb School of Communication at Purdue University and a faculty member in the Community Data Science Collective.

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

August 7, 2025

Guest Lecture:
Gabor Angeli
AI Research Engineer, Resolve AI

Bharat Khandelwal
AI Research Engineer, Resolve AI

Spiros Xanthos
Founder & CEO, Resolve AI

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

In an effort to spread knowledge and promote life-long learning, Stanford University has put extensive efforts into offering free online courses available to anyone, anywhere.

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

November 14, 2025
This lecture covers:
• Retrieval-augmented generation
• Advanced RAG techniques
• Function calling
• Agents
• ReAct framework

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

Chapters:
00:00:00 Introduction
00:06:38 RAG overview
00:27:39 Similarity search with SBERT and bi-encoders
00:34:25 Heuristic search with BM25
00:37:54 HyDE and contextual retrieval
00:41:00 Prompt caching
00:45:24 Re-ranking with cross-encoders
00:47:49 Retrieval evaluation with NDCG, MRR
00:59:28 Tool calling
01:26:22 Tool selection
01:29:17 Model Context Protocol (MCP)
01:31:56 Agents with ReAct
01:42:16 Safety and closing thoughts

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

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

October 17, 2025
This lecture covers:
• Pretraining
• Quantization
• Hardware optimization
• Supervised finetuning (SFT)
• Parameter-efficient finetuning (LoRA)

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

Chapters:
00:00:00 Introduction
00:07:19 Pretraining
00:13:26 FLOPs, FLOPS
00:16:34 Scaling laws, Chinchilla law
00:24:49 Training optimizations overview
00:31:09 Data parallelism with ZeRO
00:35:51 Model parallelism
00:38:26 Flash Attention
00:52:37 Quantization
00:56:00 Mixed precision training
01:02:31 Supervised finetuning
01:09:21 Instruction tuning
01:37:53 Parameter-efficient finetuning with LoRA
01:45:16 QLoRA

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

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

Learn about Stanford's online artificial intelligence professional and graduate programs:
https://stanford.io/3CDAIOV

Stanford Online Graduate and Professional AI programs provide the foundational and advanced skills you need to accelerate your career in AI, including machine learning, reinforcement learning, neural networks, and natural language processing and understanding. Learn about the differences between the programs in this video.

#artificialintelligence #machinelearning #deeplearning #reinforcementlearning #neuralnetworks #naturallanguageprocessing

Sam Altman, President of Y Combinator, and Dustin Moskovitz, Cofounder of Facebook and Asana, kick off the How to Start a Startup Course. Dustin discusses Why to Start a Startup and Sam introduces the 4 key components of Starting a Startup: Idea, Product, Team and Execution.
http://www.slideshare.net/Stev....enPham7/lecture-1-ho

Explore Stanford Online courses: https://online.stanford.edu/explore

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

November 18, 2025
This lecture covers career advice and a guest speaker.

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/

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

Guest Speaker
Laurence Moroney
Best-selling AI author and award-winning researcher

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

October 14, 2025
This lecture covers adversarial robustness and generative models.

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

Course details: https://stanford.io/4qjWTCk

Think back to the first time you had to tell a direct report their work wasn’t good enough, or persuade your supervisor to change course. For most new managers, those difficult conversations might not have gone as planned. But research shows these early moments can shape the trajectory of your entire career. The good news is you don’t have to wait for the next high-stakes conversation to get it right.

In this course, Stanford faculty combine decades of research with the emergent superpowers of generative AI to give you a “practice field” for leadership. You will rehearse critical conversations in a low-stakes environment and gain the skills and confidence to lead with authority and empathy.

You will learn to:
- Craft clear, respectful communication strategies that shift outcomes
- Give and receive constructive feedback that accelerates growth

Using generative AI, you will role-play high-pressure situations such as confronting difficult team members, motivating diverse talent, or disagreeing with your manager. Each practice round gives you structured, real-time feedback on tone, presence, and empathy so you can iterate and improve.

The course begins with three preset scenarios drawn from the experiences of Stanford alumni.

For each, you will:
- Observe: Hear how young leaders confronted real challenges
- Practice: Role-play with an AI partner as your conversational counterpart
- Get Feedback: Receive personalized feedback from our tough conversation AI coach
-Reflect and Repeat: Apply insights, refine your approach, and try again

Finally, you will design your own AI conversation partner for a current workplace challenge, building a personalized tool you can use beyond the course. Along the way, Stanford faculty share research, alumni share lived experiences, and you gain the playbook to shift your career trajectory.

Please note: This course requires a free ChatGPT account to participate in practice activities.

MIT 15.401 Finance Theory I, Fall 2008
View the complete course: http://ocw.mit.edu/15-401F08
Instructor: Andrew Lo

License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu

MIT 18.642 Topics in Mathematics with Applications in Finance, Fall 2024
Instructor: Peter Kempthorne
View the complete course: https://ocw.mit.edu/courses/18....-642-topics-in-mathe
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

The lecture introduces linear algebra with a focus on its applications in quantitative finance, covering vector and matrix fundamentals, portfolio valuation, and concepts like short selling, arbitrage, and contingent claims. It further explores stochastic matrices and Markov chains, eigenvalues and eigenvectors, and their roles in modeling financial markets, culminating in discussions on no-arbitrage conditions, market completeness, and pricing measures essential for option pricing theory.

License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu
Support OCW at http://ow.ly/a1If50zVRlQ

We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments.

MIT 8.04 Quantum Physics I, Spring 2013
View the complete course: http://ocw.mit.edu/8-04S13
Instructor: Allan Adams

In this lecture, Prof. Adams introduces wave functions as the fundamental quantity in describing quantum systems. Basic properties of wavefunctions are covered. Uncertainty and superposition are reiterated in the language of wavefunctions.

License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu

MIT 18.200 Principles of Discrete Applied Mathematics, Spring 2024
Instructor: Ankur Moitra
View the complete course: https://ocw.mit.edu/courses/18....-200-principles-of-d
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

We first describe the mechanics of the course. We then discuss the pigeonhole principle, explaining what it is and giving several surprising applications of it. The we briefly discuss foundations of probability and sample spaces.

License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu
Support OCW at http://ow.ly/a1If50zVRlQ

We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments.