Alan Turing Institute Courses

Spotify - Personalising the Listening Experience - Mounia Lalmas

Explore Spotify's approach to personalizing music recommendations using machine learning, focusing on user intents, relevance, diversity, and satisfaction to enhance the listening experience.

• YouTube
• 36 minutes
• On-Demand
• Free Video

Reinforcement and Mean-Field Games in Algorithmic Trading - Sebastian Jaimungal

Explore reinforcement learning and mean-field games in algorithmic trading, covering deep Q-learning, reinforced deep Kalman filters, and heterogeneous agent interactions with differing beliefs in financial markets.

• YouTube
• 1 hour 14 minutes
• On-Demand
• Free Video

An Unethical Optimisation Principle

Explore the ethical implications of AI optimization strategies and their potential for unintended consequences in financial markets and AI regulation.

• YouTube
• 53 minutes
• On-Demand
• Free Video

We Need to Talk About Statistics - Neil Sheldon, Teaching Statistics Trust

Exploring how precise language enhances statistical understanding for teachers, students, and citizens. Emphasizes interpretation over calculation, addressing common misunderstandings and the importance of clear communication in statistics.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

Explaining Generalisation and Individual Justice - Reuben Binns

Explore the challenges of balancing generalization and individual justice in AI decision-making, focusing on explainability, limitations, and ethical implications in real-world contexts.

• YouTube
• 21 minutes
• On-Demand
• Free Video

The Limits of Explainability - Alison Powell

Explore the ethical implications and limitations of AI explainability, focusing on individual justice, societal contexts, and human interpretation in algorithmically supported decision-making.

• YouTube
• 22 minutes
• On-Demand
• Free Video

Sequential Design Based on Mutual Information for Computer Experiments - Joakim Beck, KAUST

Explore uncertainty quantification using Gaussian Process emulators for complex systems. Learn about sequential design methods, mutual information criteria, and applications in climate, tsunami, and earthquake modeling.

• YouTube
• 20 minutes
• On-Demand
• Free Video

Known Boundary Emulation of Complex Computer Models - Ian Vernon, Cambridge

Explore efficient methods for emulating complex computer models using Known Boundary Emulation, focusing on uncertainty quantification and applications in climate, tsunami, and earthquake problems.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Deep Gaussian Processes for Bayesian Inversion - Matt Dunlop, Courant

Explore deep Gaussian processes for Bayesian inversion, covering theoretical foundations, numerical methods, and applications in uncertainty quantification for complex physical systems.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Pragmatically Ambitious Multiscale Global Temperature Reconstruction - Finn Lindgren, Edinburgh

Explore pragmatic approaches to global temperature reconstruction using multiscale models, data sources, and statistical techniques for uncertainty quantification and bias correction.

• YouTube
• 41 minutes
• On-Demand
• Free Video

Gaming for Military Precision Decisions - Simon Lucas

Explore how Game AI and statistical forward planning algorithms can enhance military decision-making and operational planning, with insights from Simon Lucas.

• YouTube
• 30 minutes
• On-Demand
• Free Video

Data for Disaster Management - Steven Reece

Explore machine learning approaches for data fusion in disaster management, combining diverse sources to enhance situation awareness and improve response effectiveness.

• YouTube
• 38 minutes
• On-Demand
• Free Video

Open Source Challenges in the Enterprise - Mark Little, Red Hat Inc.

Explore enterprise open source challenges, benefits, and success factors. Gain insights into its impact on technology, industry adoption, and future implications for software development and innovation.

• YouTube
• 59 minutes
• On-Demand
• Free Video

Optimal Transport for Machine Learning - Gabriel Peyre, Ecole Normale Superieure

Explore optimal transport in machine learning, covering Kantorovitch's formulation, entropic regularization, and applications in generative models and GANs. Gain insights into cutting-edge advances in data science.

• YouTube
• 42 minutes
• On-Demand
• Free Video

Nonlinear Approximation by Deep ReLU Networks - Ron DeVore, Texas A&M

Explores deep ReLU networks for nonlinear approximation, covering architecture, error analysis, and manifold approximation. Bridges mathematics, statistics, and computer science in data science applications.

• YouTube
• 47 minutes
• On-Demand
• Free Video