Alan Turing Institute Courses

Data, Privacy and Public Health - Countering COVID-19 with Technology and Trust

Exploring ethical challenges in using data and technology for COVID-19 response, balancing public health benefits with privacy concerns and trust in government interventions.

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

Technology and Public Participation in Constitution-Making - Felix-Anselm van Lier, Max Planck

Explore how digital platforms and machine learning can enhance citizen engagement in policy-making, addressing challenges and opportunities in direct democracy initiatives.

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

Neural Opinion Dynamics Model for the Prediction of User-Level Stance Dynamics - Yulan He, Warwick

Explore neural opinion dynamics for predicting user stance shifts in digital democracy platforms, enhancing citizen engagement and policy-making through machine learning techniques.

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

Ethics Review of Machine Learning in Children’s Social Care - Ellie Ott & David Leslie

Explores ethical considerations and practical principles for implementing machine learning in children's social care, addressing risks, data quality, and strategies to improve outcomes for families.

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

Approximate Cross Validation for Large Data and High Dimensions - Tamara Broderick, MIT

Explore efficient cross-validation techniques for large datasets using linear approximation and dimensionality reduction. Learn about error bounds, high-dimensional challenges, and practical applications in machine learning.

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

Benign Overfitting - Peter Bartlett, UC Berkeley

Explore benign overfitting in machine learning, focusing on linear regression, deep networks, and statistical implications. Gain insights into effective rank, regularization, and future research directions.

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

A Function Space View of Overparameterized Neural Networks - Rebecca Willet, University of Chicago

Explore function spaces of overparameterized neural networks, focusing on weight-bounded networks and their approximation capabilities. Insights from Radon transform analysis reveal novel perspectives on learning with ReLU networks.

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

Learning From Ranks, Learning to Rank - Jean-Philippe Vert, Google Brain

Explore differentiable approaches to integrate permutations, sorting, and ranking in machine learning, focusing on embedding techniques and relaxation of ranking operators.

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

Can Learning Theory Resist Deep Learning? - Francis Bach, INRIA

Exploring global convergence of gradient descent in non-convex optimization for deep learning, highlighting challenges in bridging theory and practice in machine learning algorithms.

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

From Causal Inference to Autoencoders, Memorization & Gene Regulation - Caroline Uhler, MIT

Exploring causal inference, autoencoders, and gene regulation through genomics and 3D genome organization. Integrates data modalities, analyzes overparameterized autoencoders, and links memorization to real-valued data retrieval.

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

Fast and Optimal Low-Rank Tensor Regression via Importance - Garvesh Raskutti, UW-Madison

Explore low-rank tensor regression using importance sketching for efficient high-dimensional data analysis, with theoretical guarantees and practical applications in neuroimaging.

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

Big Data Is Low Rank - Madeleine Udell, Cornell University

Explore big data's low-rank structure, generalized low-rank models, and their applications in machine learning. Learn about dimensionality reduction, autoML, and latent variable models for efficient data analysis.

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

Does Learning Require Memorization? A Short Tale About a Long Tail - Vitaly Feldman, Google Brain

Exploring the necessity of memorization in learning algorithms, this talk delves into privacy concerns, long-tail distributions, and the role of memorization in achieving optimal generalization error in deep learning.

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

Unsupervised Doodling and Painting with Generative Agents

Explore unsupervised learning in generative art, reinforcement learning agents as image creators, and the potential of AI in artistic tools and creative processes.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

Better Decisions with Machine Learning - Peter Flach

Explore machine learning techniques for better decision-making, including ROC curves, calibration methods, and precision-recall-gain curves. Learn to adapt models to deployment contexts and measure ML performance.

• YouTube
• 1 hour 4 minutes
• Self-Paced
• Free Video