ENGI47615: Optimisation

• As specified in programme regulations.

• As specified in programme regulations.

• This module is designed solely for students studying Department of Engineering degree programmes.
• To understand optimisation and the tools and techniques that can be used to improve engineering systems.
• To give students the tools and training to recognize optimisation problems that arise in applications.
• To present the basic theory of such problems, concentrating on results that are useful in applications and computation.
• To give students a thorough understanding of how such problems are solved, and some experience in solving them.
• To give students the background required to use the methods in their own research work or applications.

• Optimisation theory and techniques.
• Recognizing and solving convex optimization problems that arise in applications.
• Applications to signal processing, statistics and machine learning, control.

Subject-specific Knowledge:

• A knowledge and understanding of optimisation theory and techniques.

Subject-specific Skills:

• An awareness of current analysis methods along with the ability to apply those methods in novel situations.
• An in-depth knowledge and understanding of specialised and advanced technical and professional skills, an ability to perform critical assessment and review and an ability to communicate the results of their own work effectively.

Key Skills:

• Capacity for independent self-learning within the bounds of professional practice.
• Highly specialised numerical skills appropriate to an engineer.
• Mathematics relevant to the application of advanced engineering concepts.

• Two hour lectures delivered in a single term, structured as one lecture of methods followed by one lecture of exercises.
• The methodology taught in the first hour would be immediately followed by a second hour of exercises to consolidate student knoweldge and understanding of optimisation theory and techniques.
• The module content is delivered in lectures and is reinforced by self-learning sessions and formative problem sheets, equipping students with the required problem-solving capability.
• Students can make use of staff "office hours" to discuss any aspect of the module with teaching staff on a one-to-one basis. These are sign-up sessions available for one hour per week per lecture course.
• Students will be required to submit formative problem sheets throughout the academic year into the virtual learning environment to check their understanding as the course progresses.
• Students will be formed into study groups and will attend timetabled self-learning sessions (up to a maximum of two) during the Michalemas and Epiphany terms.
• A benchmark test will take place at the start of the academic year. This will be used to guage students understanding and direct them to further study as appropriate.
• A mock exam will take place in the Epiphany term. This will be used to provide students with an exam type experience in a formative setting and allow them to discuss their performance with a member of academic staff.
• Written timed examinations are appropriate because of the wide range of analytical, in-depth material covered in this module and allow students to demonstrate the ability to solve advanced problems independently as well as that they have deeply engaged with the material.

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