Lecture 15 - PCA and ICA | Stanford CS229: Machine Learning Andrew Ng - Autumn 2018
Lecture 15 - PCA and ICA | Stanford CS229: Machine Learning Andrew Ng - Autumn 2018
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai
Andrew Ng
Adjunct Professor of Computer Science
https://www.andrewng.org/
To follow along with the course schedule and syllabus, visit:
http://cs229.stanford.edu/syllabus-autumn2018.html
Sneak Peek: Design and Control of Haptic Systems
For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education
Take a sneak peek at the Stanford Online course Design and Control of Haptic Systems, which focuses on device modeling (kinematics and dynamics), synthesis and analysis of control systems, design and implementation, and human interaction with haptic systems.
Now available for spring enrollment! Learn more:
https://online.stanford.edu/courses/me327-design-and-control-haptic-systems
Spring enrollment ends March 15, 2026.
Allison Okamura is a Richard W. Weiland Professor in the School of Engineering with Appointments in Mechanical Engineering and Computer Science.
Course Overview: Design and Control of Haptic Systems (ME327)
For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education
Are you interested in studying the design and control of haptic systems?
The Stanford Online course, Design and Control of Haptic Systems, focuses on device modeling (kinematics and dynamics), synthesis and analysis of control systems, design and implementation, and human interaction with haptic systems. Coursework includes homework/laboratory assignments and a hands-on project.
Design and Control of Haptic Systems is now open for enrollment in the spring quarter!
Learn more details about this course:
https://online.stanford.edu/courses/me327-design-and-control-haptic-systems
Spring quarter enrollment ends March 15, 2026.
Allison Okamura is a Richard W. Weiland Professor in the School of Engineering with Appointments in Mechanical Engineering and Computer Science.
Stanford AA228 Decision Making Under Uncertainty | Autumn 2025 | Offline Belief State Planning
For more information about Stanford’s Robotics and Autonomous Systems graduate programs, visit: https://online.stanford.edu/programs/robotics-and-autonomous-systems-graduate-certificate
November 13, 2025
This lecture covers offline belief-state planning.
To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/aa228-decision-making-under-uncertainty
To follow along with the course schedule and syllabus, visit: https://aa228.stanford.edu/
Sydney Katz is a postdoctoral researcher at Stanford's Intelligent Systems Lab.
Stanford CS547 HCI Seminar | Winter 2026 | Does GenAI Work in Education?
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.
Stop second-guessing high-stakes decisions.
Make product decisions you can stand behind. Learn how to run effective experiments and translate the results into actionable insights that drive better product outcomes.
Learn to:
- Design experiments that answer real questions
- Extract causal insights from messy data
- Leverage AI for faster testing
- Turn results into a clear strategy
This course empowers product leaders, designers, and builders to leverage data science without becoming statisticians.
Learn more about the course: https://stanford.io/4kBTRrW
#ProductDevelopment #DataScience #ProductManagement #Stanford #AI #ProductDesign #OnlineCourse
Stanford Robotics Seminar ENGR319 | Winter 2026 | Bringing AI Up To Speed
For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education
January 30, 2026
This seminar covers:
• How to refine testing methodologies to advance the safety of autonomous vehicles
• How high-speed autonomous racing provides a unique proving ground to test the boundaries of AI’s physical capabilities
• How racing at high speeds and in close proximity to other vehicles exposes unsolved challenges in perception, planning, and control
To follow along with the seminar schedule, visit: https://stanfordasl.github.io/robotics_seminar/
Dr. Madhur Behl, Associate Professor in the Department of Computer Science at the University of Virginia and an Amazon Scholar
Stanford CS547 HCI Seminar | Winter 2026 | Creation, Evolution, and Formalization of Notations
For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education
January 30, 2026
This lecture covers:
• Common patterns and stages for the development of notations across computational, scientific, and artistic fields
• The role of cultural context, linking and grounding metaphors, and cognitive processes of analogical alignment
• Building a more pluralistic future for human-AI communication
To follow along with the seminar schedule, visit: https://hci.stanford.edu/
Ian Arawjo is an Assistant Professor of Human-Computer Interaction at Université de Montréal in the Department of Computer Science and Operations Research (DIRO), and an Associate Member of the Mila-Quebec AI Institute.
Course Overview: Mastering Difficult Conversations with AI
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.
New Course: Mastering Difficult Conversations with AI
The difficult conversations you're avoiding? You can practice them first.
Confront toxic behavior
Motivate disengaged talent
Push back on your boss
… all in a low-stakes rehearsal space with AI coaching. Learn more: https://stanford.io/49VsoxE
Stanford Webinar - Human-Centered AI: Designing Systems People Trust
View the details of our Generative AI: Technology, Business, and Society Program https://online.stanford.edu/programs/generative-ai-technology-business-and-society-program
Tune into this engaging discussion with Professor James Landay, Co-Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI), and Vanessa Parli, Managing Director of Programs and External Engagement for Stanford HAI.
Explore how to design AI systems that enhance human capabilities and earn stakeholder trust, and discover insights from the forefront of AI development. Uncover the principles of human-centered design that transform AI from risk to opportunity.
In this webinar, audience members learn directly from leading experts in human-computer interaction about the principles of human-centered AI design, real-world applications, and how Stanford is shaping the future of responsible AI development that truly serves humanity's best interests.
Innovation for Growth and Sustainability in the Era of AI
Join Professor Mike Lepech and Jeff Wong, former Ernst & Young Global Chief Innovation Officer, as they discuss scaling innovation in today's AI-powered business environment. They uncover what it takes to lead transformation while balancing performance and purpose, and share practical insights from leaders operating at the intersection of strategy, technology, and sustainability. The session features a fireside chat, an interactive Q&A, and a brief overview of Stanford Doerr School of Sustainability’s Executive Education program for Summer 2026: The Stanford Leadership Experience: Science, Innovation, and Resilience Program (5 days, on the Stanford campus) https://stanford.io/4ri00v8
This program is offered in collaboration with the World Business Council for Sustainable Development (WBCSD). https://www.wbcsd.org/
#AI #climatechange #energy #innovation #cleantech
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