Culture, Art and Society (6 ECTS Credits)

This course introduces students to a broad range of topics concerning British “Culture, Art and Society” drawing on theories in the humanities and social sciences to deepen their understanding of UK culture in particular and western culture and society in general. This course provides a platform for future interdisciplinary study helping students to understand the complex arguments regarding the nature of modern social life as well as the relations between culture, art and society. 
During the course, students will go on local field guided visits to Makespace Oxford, Homeless Oxfordshire, Oxford University Colleges in order for students to experience first-hand different communities that make up British society and culture and how local organisations and institutions engage with diversity.

Future Cities and Public Policy (6 ECTS Credits)

This course provides an introductory overview of the role of cities in human development and how public policy can shape urban trajectories. The core topics discussed include why cities exist and how they evolve and transform in the face of continuous challenges. One part of the course is focused on the theoretical underpinning of urban and regional growth, decline, and resilience, whereas the second part is built around case studies of different cities responding to major sudden shocks. The course culminates with the synthesis of theory and practice in the form of a Sustainable Urban Futures Methods workshop, providing students with the necessary skills and tools to complete the final assignment.
The on-campus course will also include local field guided visits in order for students to experience how local organisations and institutions engage in the city.

Entrepreneurship and Management Strategies (6 ECTS Credits)

This course combines academic learning with study visits to companies, start-ups and science parks. There are two main modules to the course, entrepreneurship and management strategies. The first module is designed to provide students with an understanding of how new ventures/entrepreneurs contribute to the economic development of a nation. It introduces them to the principles of entrepreneurship and the processes involved in setting up a new enterprise. Apart from making the business plan, they need to understand different business models, intellectual property, financing mechanisms, marketing, inventory management, human resource management etc. The significance of developing a new product and commercialising is stressed. Besides, by engaging with real-world case studies, students will construct a competitive business strategy based on sustainable economic advantages and operational alignment, through the management strategies module. 

Financial Analysis and Management Strategies (6 ECTS Credits)

This course introduces the fundamental theoretical concepts underlying the modern economic analysis of financial markets and management strategies. From the financial analysis module, students will learn about the relevance of financing and investment for corporate policy and the role of financial markets; how to value investment projects and securities based on their cash flow streams; and how uncertainty affects all the aforementioned. The module on management strategies provides students with a deep understanding of how firms develop and sustain a competitive edge. By engaging with real-world case studies, students will learn the key concepts and theories in the field and how they can be used to interpret and evaluate business situations.

Data Science (6 ECTS Credits)

This course introduces the students to the mathematical foundations of data analysis, as well as to visualising and analysing data with Python. There are three main parts to the course. The first third of the course introduces a statistical basis for data analysis, including means and variance of random variables, Bayes’ formula, the central limit theorem, linear regression, confidence intervals, and hypothesis testing (z-test and t-test). The second third is about data cleaning and visualisation (including creating plots of various types), with many examples in Python. The final third introduces the basics of machine learning in data analysis, covering the k nearest neighbours algorithm, regression using machine learning, and principal component analysis, with an emphasis both on mathematical understanding and the ability to utilise these methods in Python.

Artificial Intelligence and Machine Learning (6 ECTS Credits)

This course is virtually unique in providing not only an introduction to the technology of ML/AI but also a solid introduction to the Ethical, Economic, Social and Sustainability issues that underpin and shape its use. An understanding of these issues is crucial to the fair and equitable application of these powerful technologies. The technology component of the course introduces techniques for automatically organising and categorising information; building models that replicate human decision making and for complex recognition tasks. Participants will learn how to prepare and manipulate data to remove errors and omissions in data and enable model building. The course will provide powerful methods for data visualisations that enable human insight and decision-making.
 

Robotics and Artificial Intelligence (6 ECTS Credits)

This course provides an introductory overview of the field of robotics. Topics related to how robots move, perceive and interact will be discussed. The first half of the course will cover fundamental concepts in robot kinematics, computer vision, robot control, localization and planning. In the second half, the course will cover the foundations of machine learning and AI and explain how a neural network is built and trained. Each topic is accompanied by a programming tutorial where the students will learn to implement the concepts in a hands-on way.