University College London

In this course, students learn the skills to write Python code to implement statistical and machine learning algorithms that can be applied in a range of contexts. Each week the course covers an aspect of computer coding using examples and exercises that drawn on bioscience contexts. Topics will include: probability, maximum likelihood, Bayes theorem, supervised learning: regression and classification, unsupervised learning: dimensionality reduction and clustering, model evaluation and improvement, reinforcement learning, and neural networks and deep learning.

Evidence-based healthcare has taken root as one of the central pillars of modern medicine. Arguably, the delivery of healthcare based on scientific evidence has never been more important, as we grapple with unexplained variations in practice and spiraling healthcare costs. Despite its widespread importance for rational decision making, the ideal of truly evidence-based healthcare remains elusive. This course is highly engaging and interactive and supports students in developing the necessary skills to be effective and critical practitioners of evidence-based healthcare. Students learn to apply these principles in their studies and in their professional clinical careers. Students also have the opportunity to experience a research environment by meeting researchers in the field and completing a group project under supervision and presenting the results orally.

This course introduces students to the structure of the British political system and the functioning of British politics in practice. Students start by exploring the social foundations of politics in the UK, looking at the roles of various national identities and of class, gender, and ethnicity. They also explore the main institutions and players in the UK system, setting these within a comparative context. Students seek to understand how the various parts of the system interact with each other in determining the character of the democratic process and the nature of policy outcomes.

This course provides students with an understanding of the tools and techniques required to interface between mechanical components and the wider world, involving sensing, actuation (e.g. motors) modelling and control.