Understand why mathematics is the foundation of all engineering practice and build the robust mathematics skills needed to proceed to more complex modules.

Build on your learning from Mathematics 1A and appreciate fundamental mathematical principles in an engineering context.

Familiarise yourself with the interdisciplinary nature of electrical engineering and analyse the generation, transport and management of electrical power systems.

Become familiar with programming using C++ and learn standard imperative programming skills such as control-flow, variables, and data structures.

Build a foundation in the analysis and design of electronic circuits, and explore key concepts that are essential for higher level study of electronics.

Develop your understanding of digital design and low-level computer operation to understand system design across the hardware - software boundary.

Apply your knowledge to a major group design project which considers the full design process, from the client brief to the demonstration of a prototype.

Discover how information is transmitted from one point to another in the presence of noise and build your awareness of information theory.

Apply your knowledge in a major group design project which considers the full design process from the client brief to the demonstration of a prototype. 

The second year project is a five-day IBM computer architecture workshop, run by staff from Imperial and IBM.

Become acquainted with basic elements of the theory of dynamic systems and the techniques used to design automatic control systems.

Understand how to bridge the analogue/digital divide in computing by using techniques from discrete and continuous maths.

Explore how to take data and transform it or analyse it, and learn how to classify real-world data into different types of signals.

Build on your knowledge of computer architecture by learning the theory and design of language processors and compiliers.

Build on your first year studies to cover more advanced topics in mathematics that are relevant to both electrical and information engineering.

Build on your existing software knowledge and apply it in more complex systems.

Experience design engineering in an industrially relevant context and gain valuable insights into the commercial and project management facets of product development.

Your I-Explore module offers you choices from a range of subjects hosted outside of the department. You will be taught alongside students from other courses with options including business, management and many more.

Gain hands-on experience on an industrial placement, typically undertaken from April to September. 

The placement will be supervised and is assessed by a written and oral report.

Examples of previous placement partners include Bang & Olufsen, Goldman Sachs and IBM.

Understand the efficient formulation of a problem space, aspects of knowledge representation, and concepts of intelligent agents and multi-agent systems for the design of complex, distributed, embedded systems.

Develop a conceptual framework for analysing different communication networks and build your awareness of industry standards.

Analyse how communications systems perform in the presence of noise and compare the performance of various systems.

Build your knowledge of advanced modern control methodologies and explore topics including Kalman filtering and tracking, fault detection and isolation, and linear matrix inequalities.

Assess fundamental concepts and advanced methodologies of deep learning and relate them to real-world problems.

Appreciate the fundamental principles and applications of digital signal processing, including sampling theory, z-transforms and system functions.

Design digital systems of medium complexity, and learn how to implement the design with FPGA/CPLD devices, memory devices and microprocessors.

Engage with the theory and practice of computing in the world of ubiquitous smart devices.

Appreciate the role of modern static type systems, sum and product data structures, immutable code, and higher order functions in program design and analysis.

Build your knowledge of the basic theory of machine learning (ML) and explore the workings of neural networks (NN).

Understand the linear algebra needed for advanced topics in signals, signal proccessing and control.

Explore the fundamentals of classical long-range radar and the new frontiers of short-range radar for many anticipated applications.

Bring together theory and understanding from other lecture courses and apply your knowledge to solve a problem which might be encountered by a DSP engineer in industry.

Design, model and control robotic arms and grippers.

Understand the fundamentals of statistical signal processing, and develop practical experience of using statistical signal processing on your own speech.

Choose a project from an extensive list proposed by members of academic staff. 

Due to the variety of staff expertise, the list covers a wide range of engineering topics. 

Proposing your own project is encouraged, and is done in collaboration with a member of staff who is an expert in the proposed field.

Develop your professional portfolio using the engineering skills you've acquired over the four years of study.

If you have taken the Group Project option in your third year, you must do a summer internship or placement between your third and fourth year and report on this in your professional portfolio.

Industrial placement students must submit a professional portfolio towards achieving the learning outcomes of the course.

Develop your knowledge of computer vision and pattern recognition tasks and consider how these technologies can impact the practical design of intelligent signal analysis.

Examine the fundamental digital image processing methods that stem from a signal processing approach.

Examine the techniques used to verify software and hardware and build your appreciation of how an automated software verification tool works.

Design and build an interactive robot focussing on the 3R concept: real robots, real environments, interacting with real people.

Learn from a computational perspective how systems of autonomous components interact in the context of conventional rules.

Understand why mathematics is the foundation of all engineering practice and build the robust mathematics skills needed to proceed to more complex modules.

Build on your learning from Mathematics 1A and appreciate fundamental mathematical principles in an engineering context.

Familiarise yourself with the interdisciplinary nature of electrical engineering and analyse the generation, transport and management of electrical power systems.

Become familiar with programming using C++ and learn standard imperative programming skills such as control-flow, variables, and data structures.

Build a foundation in the analysis and design of electronic circuits, and explore key concepts that are essential for higher level study of electronics.

Develop your understanding of digital design and low-level computer operation to understand system design across the hardware - software boundary.

Apply your knowledge to a major group design project which considers the full design process, from the client brief to the demonstration of a prototype.

Build on your first year studies to cover more advanced topics in mathematics that are relevant to both electrical and information engineering.

Study the discrete mathematics that underpin formal aspects of computation and develop your understanding of proof methods.

Learn how high-level programs are executed through the sequencing of instructions and further your knowledge of computer architecture.

Build on your existing software knowledge and apply it in more complex systems.

Explore how to take data and transform it or analyse it, and learn how to classify real-world data into different types of signals.

Discover how information is transmitted from one point to another in the presence of noise and build your awareness of information theory.

Become acquainted with basic elements of the theory of dynamic systems and the techniques used to design automatic control systems.

Apply your knowledge in a major group design project which considers the full design process from the client brief to the demonstration of a prototype. 

The second year project is a five-day IBM computer architecture workshop, run by staff from Imperial and IBM.

Experience design engineering in an industrially relevant context and gain valuable insights into the commercial and project management facets of product development.

Your I-Explore module offers you choices from a range of subjects hosted outside of the department. You will be taught alongside students from other courses with options including business, management and many more.

Gain hands-on experience on an industrial placement, typically undertaken from April to September. 

The placement will be supervised and is assessed by a written and oral report.

Examples of previous placement partners include Bang & Olufsen, Goldman Sachs and IBM.

Understand the efficient formulation of a problem space, aspects of knowledge representation, and concepts of intelligent agents and multi-agent systems for the design of complex, distributed, embedded systems.

Analyse how communications systems perform in the presence of noise and compare the performance of various systems.

Develop a conceptual framework for analysing different communication networks and build your awareness of industry standards.

Become familiar with model based control system design and learn how to choose the most appropriate analysis and design techniques.

Assess fundamental concepts and advanced methodologies of deep learning and relate them to real-world problems.

Appreciate the fundamental principles and applications of digital signal processing, including sampling theory, z-transforms and system functions.

Design digital systems of medium complexity, and learn how to implement the design with FPGA/CPLD devices, memory devices and microprocessors.

Engage with the theory and practice of computing in the world of ubiquitous smart devices.

Appreciate the role of modern static type systems, sum and product data structures, immutable code, and higher order functions in program design and analysis.

Build your knowledge of the basic theory of machine learning (ML) and explore the workings of neural networks (NN).

Understand the linear algebra needed for advanced topics in signals, signal proccessing and control.

Explore the fundamentals of classical long-range radar and the new frontiers of short-range radar for many anticipated applications.

Bring together theory and understanding from other lecture courses and apply your knowledge to solve a problem which might be encountered by a DSP engineer in industry.

Examine the design, modelling and control of robotic arms and grippers.

Understand the fundamentals of statistical signal processing, and develop practical experience of using statistical signal processing on your own speech.