Imperial College London

The aim of the class is for students to develop a mind-set for problem solving through experiential and practical based learning in order to tackle the challenges they may face as chemical engineers in industry.

The course provides the fundamental theory for the design and analysis of (pseudo-) homogeneous chemical reactors. It considers ideal isothermal and non-isothermal reactor systems, and reactors involving non-ideal flow. Students learn to describe batch, semi-batch, and continuous reactor operation; homogeneous and heterogeneous reactors; and ideal and non-ideal flow models. They define conversion and the extent of reaction; product yield and selectivity; and residence time, space time, and space velocity. They derive the basic design equations for isothermal and non-isothermal reactors and perform design analysis of multistage reactor configurations, and reactors involving recycle. They determine optimal reactor configurations and operating policies for systems involving multiple reactions. Students perform analysis of reactors involving non-ideal flow based on residence time distribution theory, and zero and one-parameter flow models.

This course explores database systems with particular reference to the relational model, including design, query languages, and update transactions. It introduces entity-relationship modeling and translation to the relational model. In laboratory sessions, students use relational database system, INGRES, and the language SQL.

This course expands students' knowledge and thinking about algorithms and algorithmic design. The course exposes students to several new classes of computational problems and concrete algorithmic solutions, and provides a study of general (or commonly useful) approaches to algorithmic thinking.

In this class you will have the opportunity to demonstrate independence and originality, to plan and organise a large project over a long period, and to put into practice the knowledge, skills and research methods that you have learnt throughout the course. Upon successful completion of this module, you will have demonstrated your ability to apply previously taught knowledge and skills to a substantial problem in Computing, as an individual. You will conduct an independent investigation and apply cutting-edge research, methods and thinking appropriate to the problem, presenting complex technical material orally to a mixed audience. You will exercise scientific writing skills by way of a substantial written report, summarising your findings There will be a small number of supporting lectures that will describe the structure of the project, including expectations, milestones and deliverables,give guidance on writing and presentation skills targeted specifically at individual projects and explain the assessment procedures. Please note this is a graduate level course The rest of the project involves an independent investigation under the supervision of an academic advisor.

This course explores the fundamental principles and devices used in the design of digital computers, including how primitive control logic can be organized to construct a programmable machine. The course covers Boolean algebra, combinatorial logic functions, principles of semiconductor devices and logic gates, adders subtractors and multipliers, bistable storage devices, S-R flip-flop, D-type flip-flop, latch versus edge triggering, J-K flip-flops, registers, shift registers, multiplexers and decoders, counters, finite state machine design, static and dynamic RAM, register transfer descriptions, ALU design and CPU design. Practical laboratory work consists of the design of combinatorial and sequential circuits using modern VLSI design tools.

The class will explore a range of topics in the philosophy of mind, such as the nature of consciousness and thought, the nature of human action and the problem of determinism, the relation between mind (or mental phenomena) and body (or physical phenomena), and the possibility of artificial intelligence. Students will gain a deeper understanding of the interplay between philosophical research in these areas and research across a broad range of scientific disciplines, such as neuroscience, life sciences, medicine and computing. By comparing the work of thinkers as diverse as Dennett, Davidson, Putnam, the Churchlands, Fodor, Ryle, Wittgenstein and Heidegger, students will encounter and critically evaluate the cutting edge of modern thinking about the mind, and to the issues that must be resolved before embarking on any scientific exploration of the mind.

This course explores continuity, differentiation, and integration of complex valued functions, with applications to real integration.