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• Foundational topics in Statistical ML and Deep Learning

• ⁠From mathematics of ML and optimisation, to fundamentals of deep learning, NLP and computer vision.

• Every day will be a conniption of theoretical + applied lectures, and case studies (i.e., hands-on coding).

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• For scientists/engineers and product designers/managers who want to build Gen.AI products.

• An overview of the latest developments in generative foundation models in language, vision and more.

• A deep dive into emerging research and design patterns in Agentic Workflow and Alignment/Trust.

• Applied talks by industry-leading Generative-AI products on best practices, design patterns, and more.

• A masterclass combining theoretical ML talks with applications of ML in healthcare and biomedical sciences/research/technology.

• ⁠From imaging, proteomics, genomics, and EHR, to comp. bio, drug discovery, multi-omics, wearable, and more.

• Delivered by the leading researchers in both academic and industry.

• ⁠Covering the latest developments in representation learning, including those behind the success of generative AI.

• Deep dive into ML in domains such as NLP (including LLMs), computer vision (including foundational/frontier image, video and multi-modal models), Bayesian ML, Reinforcement Learning, Geometrical DL, and more.

• Several talks on the applications of DL and Gen. AI across key domains and industry verticals.