Level up your skills and get to grips with the latest software innovations in Oxford Summer Courses' immersive Computer Science summer school. Our tutors will introduce you to the fundamentals of the subject, which could include building confidence in essential programming skills, learning how to run feasible tests, and how to speak the different languages of code.

Our Summer School aims at developing the students’ academic knowledge and professional skills in 2 major topics related to Computer Science – Visual computing and Artificial intelligence. You will be involved in various projects with the teaching staff and you will take courses in Visual Computing and Artificial Intelligence, which will provide you with the tools to create virtual reality, video games, virtual divides, interactive objects and to learn about optimizations methods and data mining. As an additional module, French as a Foreign Language will be included to help you socialize with the French population.

RobotCraft is a two months intensive internship and summer-course program. After the tremendous success of past editions, RobotCraft's 8th edition is coming in the summer of 2023.

Introduction to the fundamental concepts of computer systems. Explores how computer systems execute programs and manipulate data, working from the C programming language down to the microprocessor.

Representation, analysis, techniques, and principles for manipulation of basic combinatoric structures used in computer science. Rigorous reasoning is emphasized.

Topics include counting and combinatorics, random variables, conditional probability, independence, distributions, expectations, point estimation, and limit theorems. Applications of probability in computer science including machine learning and the use of probability in the analysis of algorithms. Prerequisites: 103, 106B or X, multivariate calculus at the level of MATH 51 or CME 100 or equivalent.

The 2025 edition of the Summer School Enabling Technologies for Industrial Internet of Things (ET-I2oT 2025) is organized to provide 6 ECTS (about 52 hours of front lessons) in the fields of Electronics, RFID, Sensors, Networking, Web of Things, SW for IoT, Computer Engineering, targeting on one side an audience of Bachelor (last year), Master and PhD students, and on the other side early stage researchers and practitioners from Academia or Industry. Both HW and SW aspects of IoT will be presented and discussed during the school.

The Summer Course in Human AI invites participants to connect their findings with those of their peers and collaborate on research-based projects. Human processes of all kinds are complex and adaptive. Mental, social, and health-related processes can all change and adapt over time to human behavior.

Covers advanced programming techniques and data structures. Topics include recursion, algorithm analysis, linked lists, stacks, queues, trees, graphs, tables, searching, and sorting. Students must register for two sections: lecture and laboratory.

CS106A introduces code and computer programming for people who have not programmed before. Code and programming are central to so much in modern life, yet code can appear to be impossibly opaque. By working gradually and with its army of section leaders, CS106A takes students into the world code, building things they could not have imagined.

From self-driving cars and augmented reality to intelligent medical imaging helping doctors identify diseases more quickly, computer vision is a rapidly growing field within artificial intelligence and machine learning. In this course, students who are already familiar with the key theoretical foundations of artificial intelligence and machine learning will dive deeper into the exciting capabilities of this area of research and its applications.

Abstraction and its relation to programming. Software engineering principles of data abstraction and modularity. Object-oriented programming, fundamental data structures (such as stacks, queues, sets), and data-directed design. Recursion and recursive data structures (linked lists, trees, graphs). Introduction to time and space complexity analysis. Uses the programming language C++ covering its basic facilities. Prerequisite: 106A or equivalent.

Convex sets, functions, and optimization problems. The basics of convex analysis and theory of convex programming: optimality conditions, duality theory, theorems of alternative, and applications. Least-squares, linear and quadratic programs, semidefinite programming, and geometric programming. Numerical algorithms for smooth and equality-constrained problems; interior-point methods for inequality-constrained problems. Applications to signal processing, communications, control, analog, and digital circuit design, computational geometry, statistics, machine learning, and mechanical engineering.

Artificial intelligence has been a fascinating concept for more than a decade, and we are finally getting close to making AI a reality. We are currently witnessing significant innovations in various technologies that all relate to the influence of AI. This drives demand for understanding not only how to use and implement such technologies but also how the basic concepts of selected components really work.

Client-side technologies are used to create websites such as Google maps or Gmail. Includes HTML5, CSS, JavaScript, the Document Object Model (DOM), and Ajax. Prerequisite: programming experience at the level of CS106A.