English Courses

Rethinking Architecture Design for Data Heterogeneity in FL - Liangqiong Qu

Explores innovative architecture designs for federated learning in medical AI, focusing on Transformers to address data heterogeneity challenges and improve model performance across diverse healthcare institutions.

• YouTube
• 38 minutes
• Self-Paced
• Free Video

Frontiers of Medical AI - Therapeutics and Workflows

Explore cutting-edge AI applications in medicine, focusing on therapeutics and workflow optimization. Learn about AI-driven cancer treatment decisions, protein engineering, and specialized medical search engines.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

Style Transfer Augmentations for Computational Pathology - Rikiya Yamashita

Innovative style transfer augmentation technique for improving machine learning model generalization in computational pathology, enhancing robustness to domain shifts and achieving state-of-the-art performance in classification tasks.

• YouTube
• 52 minutes
• Self-Paced
• Free Video

Learning the Structure of EHR with Graph Convolutional Transformer - Edward Choi

Explore graph convolutional transformers for learning EHR structure, combining graph convolution and self-attention for supervised prediction tasks in healthcare analytics and representation learning.

• YouTube
• 1 hour 30 minutes
• Self-Paced
• Free Video

Stanford Seminar - Failures & Where to Find Them: Considering Safety as a Function of Structure

Explore autonomous systems safety, from structured driving environments to unstructured scenarios, using failure identification and anomaly detection techniques for robust decision-making.

• YouTube
• 1 hour
• Self-Paced
• Free Online Course

Using Data for Increased Realism with Haptic Modeling and Devices

Explore innovative haptic modeling techniques using data-driven approaches for enhanced realism in touch-based interactions and social touch applications.

• YouTube
• 56 minutes
• Self-Paced
• Free Online Course

Forecasting and Aligning AI - Jacob Steinhardt

Modern ML systems sometimes undergo qualitative shifts in behavior simply by “scaling up” the number of parameters and training examples. Given this, how can we extrapolate the behavior of future ML systems and ensure that they behave safely and are alig…

• YouTube
• 55 minutes
• Self-Paced
• Free Online Course

Stanford Seminar - Cognitively Appropriate Computing Education for Young Learners

Explore cognitively appropriate computing education for young learners through voice-based storytelling and visual tools, addressing literacy challenges and fostering computational thinking skills.

• YouTube
• 51 minutes
• Self-Paced
• Free Online Course

Stanford Seminar - The What and Why of Continuous Discovery, Teresa Torres

Explore continuous product discovery techniques, including customer engagement, opportunity solution trees, and effective decision-making for product teams to drive innovation and success.

• YouTube
• 51 minutes
• Self-Paced
• Free Online Course

Stanford Seminar - Representation Learning for Autonomous Robots, Anima Anandkumar

I will describe some key ingredients to enable this: (1) robust self-supervised learning (2) uncertainty awareness (3) compositionality. We utilize NVIDIA Isaac for GPU-accelerated robot learning at scale on a variety of tasks and domains.

• YouTube
• 56 minutes
• Self-Paced
• Free Online Course

Stanford Seminar - The FATE of AI Ethics, Anna Bethke

Explore AI ethics principles, their importance, and strategies to incorporate fairness, accountability, transparency, and human rights into AI development processes.

• YouTube
• 55 minutes
• Self-Paced
• Free Online Course

Stanford Seminar - Developing Design Spaces for Visualization - Tamara Munzner

Explore visualization design spaces, their creation, assessment, and application in data representation. Insights on chart combinations, data wrangling, and task abstraction for effective visual communication.

• YouTube
• 57 minutes
• Self-Paced
• Free Online Course

Stanford Seminar - Theories of Inference for Visual Analysis

Explore theories of visual inference, including uncertainty visualization, effect size judgments, and Bayesian cognition. Learn how visualizations support causal inference and model checks in data analysis.

• YouTube
• 1 hour
• Self-Paced
• Free Online Course

Extended Reality for Everybody - Michael Nebeling

Explore extended reality design challenges and solutions, empowering novice designers and instructors with accessible tools and methods for creating AR/VR experiences.

• YouTube
• 57 minutes
• Self-Paced
• Free Online Course

Bayesian Networks 3 - Maximum Likelihood - Stanford CS221: AI (Autumn 2019)

Explore maximum likelihood estimation in Bayesian networks, covering parameter learning, probabilistic inference, and advanced concepts like regularization and Expectation Maximization.

• YouTube
• 1 hour 24 minutes
• Self-Paced
• Free Online Course