Engineering Tripos Part IIB, 4I7: Electricity & Environment, 2018-19
Module Leader
Lecturer
Professor M Pollitt
Timing and Structure
Lent term. 2 hour sessions. Assessment: 100% coursework.
Prerequisites
Students should have a basic engineering knowledge of electricity (first year undergraduate) and a familiarity with the units and notation associated with energy science and engineering. Assessment will be structured so as to be accessible to students from a range of backgrounds although basic undergraduate physics or engineering proficiency is beneficial.
Aims
The aims of the course are to:
- provide students with a firm foundation in modern electricity policy with an emphasis on the UK.
- introduce students to a wide a variety of mature and emergent electricity generation and demand side technologies.
- expose students to the local, regional and global environmental effects of energy use.
- introduce the key considerations of energy policy and develops frameworks by which progress against policy goals may be achieved.
Objectives
As specific objectives, by the end of the course students should be able to:
- generate scenarios for the future UK electricity system out to 2050
- evaluate and compare the efficacy of different electricity generation technologies
- critique current and future electricity policy
- appreciate how economics and engineering interact in a sustainable electricity system
Content
This module is a postgraduate module of Cambridge Judge Business School. It has its origins as an elective course of the MPhil in Technology Policy and the MPhil in Engineering for Sustainable Development. The module is of the standard size adopted in the Engineering Department and the Judge Business School, i.e. a nominal 16 hours. The course is delivered via one two-hour lecture each week for eight weeks.
Overview - Class Introduction - Michael Pollitt
Lecture 1
- History of Electrical Power and Energy Policy.
- Fundamentals of the UK and USA Electricity System.
- UK Energy Policy and Politics.
- Recent UK Energy White Papers.
Environmental Effects of Fossil Fuel Use and what to do about them (Michael Pollitt)
Lecture 2
- Local Emissions and Impacts
- Putting a Price on Damages?
- Economic approaches to externalities
- Pricing carbon
- Experiences of the EU Emissions Trading System and carbon pricing in Australia
Electricity Demand (Michael Pollitt)
Lecture 3
- Economics of Electricity Demand
- The economics of smart energy services
- Technological aspects of electricity demand
- Social aspects of electricity demand
- Demand side policy
Wind Energy (Jim Platts)
Lecture 4
- Attributes of wind power
- Technology and history
- Wind resources and grid integration
- UK and EU wind policy
- Wind turbine manufacture
Fossil fuel generation, storage and future electricity markets (Michael Pollitt)
Lecture 5
- Current status of fossil-fuel power generation
- Economics of Carbon Capture and Storage
- The economics of electricity storage
- Business models for the internet of energy
- Future electricity market design
Renewables and the Electricity System (Michael Pollitt)
Lecture 6
- Renewables context
- Potential for renewables in the UK
- Place of renewables in electricity system
- How to subsidise renewables
- Lessons from around the world
Electricity Networks (Richard McMahon)
Lecture 7
- Transmission and distribution system engineering considerations
- Design and operation
- History of the grid and legacy issues
- Distributed Generation
- High voltage DC and interconnection
Nuclear Power, Electricity Security and EU Policy (Michael Pollitt)
Lecture 8
- The economics of Nuclear Power
- Energy Security
- EU Energy Policy
- EU 20:20:20 by 2020 Targets
- EU 2030 Targets
- Roadmap 2050
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
|
First piece of coursework Use the UK 2050 calculator to generate own electricity related scenario. Learning objectives:
|
Individual report 1000 words anonymously marked |
11 February 2019 [30/100] |
|
Second piece of coursework Essay on the 2030 decarbonisation challenge facing the UK electricity system. Learning objectives:
|
Individual Report 2000 words anonymously marked |
23 April 2019 [70/100] |
Booklists
Expected reading:
Jamasb, T., Nuttall, W. and Pollitt, M. (2006) Future electricity technologies and systems. Cambridge: Cambridge University Press N.B. Discount available for students on CUP books at CUP bookshop. Printed book at: HD9697.A2 J34 Engineering: DE159 Mar: 26 AC 58 UL: 220:01.c.27.63
Grubb, M., Jamasb, T., and Pollitt, M.G. (2008) Delivering a low-carbon electricity system. Cambridge: Cambridge University Press Printed book at: JBS: TD195.E4 G72 2008 Engineering: DE.166
Recommended reading:
Taylor, S. (2016) The Fall and Rise of Nuclear Power in Britain Cambridge: UIT Printed book at: JBS: HD9698.G72 T39 F3 2016 UL: C212.c.2239
Jamasb, T. and Pollitt, M. (2011) The Future of Electricity Demand Cambridge: Cambridge University Press Printed book at: JBS: HD9685.G72 J35 2011 Engineering: DE.190UL: 235.c.201.356 (South Front 6)
MacKay, D.J.C. (2009) Sustainable energy without the hot air. Cambridge: UIT E-book via withouthotair http://www.withouthotair.com/download.html Printed book at: Engineering: DE.164
HM Government 2050 Pathways analysis Report via DECC Publications http://www.decc.gov.uk/en/content/cms/tackling/2050/2050.aspx
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
S4
Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 21/09/2018 12:11
Engineering Tripos Part IIB, 4I7: Electricity & Environment, 2017-18
Module Leader
Lecturer
Professor M Pollitt
Timing and Structure
Lent term. 2 hour sessions. Assessment: 100% coursework.
Prerequisites
Students should have a basic engineering knowledge of electricity (first year undergraduate) and a familiarity with the units and notation associated with energy science and engineering. An understanding of undergraduate engineering thermodynamics is desirable if the full benefits of the course are to be achieved. Assessment will be structured so as to be accessible to students from a range of backgrounds although basic undergraduate physics or engineering proficiency is expected.
Aims
The aims of the course are to:
- provide students with a firm foundation in modern electricity policy with an emphasis on the UK.
- introduce students to a wide a variety of mature and emergent electricity generation and demand side technologies.
- expose students to the local, regional and global environmental effects of energy use.
- introduce the key considerations of energy policy and develops frameworks by which progress against policy goals may be achieved.
Content
This module is a postgraduate module of Cambridge Judge Business School. It has its origins as an elective course of the MPhil in Technology Policy and the MPhil in Engineering for Sustainable Development. The module is of the standard size adopted in the Engineering Department and the Judge Business School, i.e. a nominal 16 hours. The course is delivered via one two-hour lecture each week for eight weeks.
Overview - Class Introduction - Michael Pollitt
Lecture 1
- History of Electrical Power and Energy Policy.
- Fundamentals of the UK and USA Electricity System.
- UK Energy Policy and Politics.
- Recent UK Energy White Papers.
Environmental Effects of Fossil Fuel Use and what to do about them (Michael Pollitt)
Lecture 2
- Air Pollution
- Climate Change
- Science of energy related climate change
- Strategies for reducing risk
- Impact of climate change negotiations
Electricity Demand (Michael Pollitt)
Lecture 3
- Economics of Electricity Demand
- Technological aspects of electricity demand
- Social aspects of electricity demand
- Demand side policy
Wind Energy (Jim Platts)
Lecture 4
- Attributes of wind power
- Technology and history
- Wind resources and grid integration
- UK and EU wind policy
- Wind turbine manufacture
Fossil fuel generation, storage and future electricity markets (Michael Pollitt)
Lecture 5
- Current status of fossil-fuel power generation.
- Economics of Carbon Capture and Storage
- Electricity storage
- The economics of electricity storage
- Future electricity market design
Renewables and the Electricity System (Michael Pollitt)
Lecture 6
- Renewables context
- Potential for renewables in the UK.
- Place of renewables in electricity system.
- How to subsidise renewables.
- Lessons form around the world.
Electricity Networks (Richard McMahon)
Lecture 7
- Transmission and distribution system engineering considerations
- Design and operation
- History of the grid and legacy issues
- Distributed Generation
- High voltage DC and interconnection
Nuclear Power, Electricity Security and EU Policy (Michael Pollitt)
Lecture 8
- The economics of Nuclear Power
- Energy Security
- EU Energy Policy
- EU 20:20:20 by 2020 Targets
- EU 2030 Targets
- Roadmap 2050
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
|
First piece of coursework Use the UK 2050 calculator to generate own electricity related scenario. Learning objectives:
|
Individual report 1000 words anonymously marked |
12 February 2018 [30/100] |
|
Second piece of coursework Essay on the 2030 decarbonisation challenge facing the UK electricity system. Learning objectives:
|
Individual Report 2000 words anonymously marked |
24 April 2018 [70/100] |
Booklists
Expected reading:
Jamasb, T., Nuttall, W. and Pollitt, M. (2006) Future electricity technologies and systems. Cambridge: Cambridge University Press N.B. Discount available for students on CUP books at CUP bookshop. Printed book at: HD9697.A2 J34 Engineering: DE159 Mar: 26 AC 58 UL: 220:01.c.27.63
Grubb, M., Jamasb, T., and Pollitt, M.G. (2008) Delivering a low-carbon electricity system. Cambridge: Cambridge University Press Printed book at: JBS: TD195.E4 G72 2008 Engineering: DE.166
Recommended reading:
Nuttall, W.J. (2005) Nuclear renaissance: technologies and policies for the future of nuclear power. Bristol: IOP Pub. Printed book at: JBS: TK9145.N87 Engineering: XA.31 UL: 429:5.c.200.5 (South Front 6)
Jamasb, T. and Pollitt, M. (2011) The Future of Electricity Demand Cambridge: Cambridge University Press Printed book at: JBS: HD9685.G72 J35 2011 Engineering: DE.190UL: 235.c.201.356 (South Front 6)
MacKay, D.J.C. (2009) Sustainable energy without the hot air. Cambridge: UIT E-book via withouthotair http://www.withouthotair.com/download.html Printed book at: Engineering: DE.164
HM Government 2050 Pathways analysis Report via DECC Publications http://www.decc.gov.uk/en/content/cms/tackling/2050/2050.aspx
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
S4
Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 11/08/2017 12:29
Engineering Tripos Part IIB, 4M23: Electricity and Environment, 2020-21
Module Leader
Lecturers
Dr T Long and Professor M Pollitt
Lecturer
Timing and Structure
Lent term. 2 hour sessions. Assessment: 100% coursework.
Prerequisites
A basic engineering knowledge of electricity (first year undergraduate) and a familiarity with the units and notation associated with energy science and engineering is an advantage, but not essential. Assessment will be structured so as to be accessible to students from a range of backgrounds.
Aims
The aims of the course are to:
- provide students with a firm foundation in modern electricity policy with an emphasis on the UK.
- introduce students to a wide a variety of mature and emergent electricity generation and demand side technologies.
- expose students to the local, regional and global environmental effects of energy use.
- introduce the key considerations of energy policy and develop frameworks by which progress against policy goals may be achieved.
- discuss issues with electrification of heating and transport.
Objectives
As specific objectives, by the end of the course students should be able to:
- critique scenarios for the future UK electricity system out to 2050
- evaluate and compare the efficacy of different electricity generation technologies
- understand current and future electricity policy options
- appreciate how economics and engineering interact in a sustainable electricity system
Content
This module is a postgraduate module of Cambridge Judge Business School. It has its origins as an elective course of the MPhil in Technology Policy and the MPhil in Engineering for Sustainable Development. The module is of the standard size adopted in the Engineering Department and the Judge Business School, i.e. a nominal 16 hours. The course is delivered via one two-hour lecture each week for eight weeks.
Overview - Class Introduction - Michael Pollitt
Lecture 1
- History of Electrical Power and Energy Policy.
- Fundamentals of the UK and USA Electricity System.
- UK Energy Policy and Politics.
- Principles of good energy policy.
- Recent UK Energy White Papers.
Environmental Effects of Fossil Fuel Use and what to do about them (Michael Pollitt)
Lecture 2
- Local Emissions and Impacts
- Putting a Price on Damages?
- Economic approaches to externalities
- Pricing carbon
- Experiences of the EU Emissions Trading System and carbon pricing in Australia
Electricity Demand (Michael Pollitt)
Lecture 3
- Economics of Electricity Demand
- The economics of smart energy services
- Technological aspects of electricity demand
- Social aspects of electricity demand
- Demand side policy
Fossil fuel generation, storage and future electricity markets (Michael Pollitt)
Lecture 4
- Current status of fossil-fuel power generation
- Economics of Carbon Capture and Storage
- The economics of electricity storage
- Business models for the internet of energy
- Future electricity market design
Renewables and the Electricity System (Michael Pollitt)
Lecture 5
- Renewables context
- Potential for renewables in the UK
- Place of renewables in electricity system
- How to subsidise renewables
- Lessons from around the world
Electrification of heating and transport? (Michael Pollitt)
Lecture 6
- The economics of heating
- Decarbonising the gas network
- Sector coupling: power to gas
- The economics of transport
- Decarbonisation of transport
- Electrification of transport: cars, trucks, ships and planes?
Electricity Networks (Richard McMahon)
Lecture 7
- Transmission and distribution system engineering considerations
- Design and operation
- History of the grid and legacy issues
- Distributed Generation
- High voltage DC and interconnection
Nuclear Power, Electricity Security and EU Policy (Michael Pollitt)
Lecture 8
- The economics of Nuclear Power
- Energy Security
- EU Energy Policy
- EU 2030 Targets
- Roadmap 2050
- Good electricity policy?
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
|
Essay on the 2030 decarbonisation challenge facing the UK electricity system. Learning objectives:
|
Individual Report 2000 words anonymously marked |
26 March 2021 [100/100] |
Booklists
Expected reading:
Grubb, M., Jamasb, T., and Pollitt, M.G. (eds.) (2008) Delivering a low-carbon electricity system. Cambridge: Cambridge University Press Printed book at: JBS: TD195.E4 G72 2008 Engineering: DE.166
Ozawa, M., Chaplin, J., Pollitt, M., Reiner, D. and Warde, P. (eds.) (2019) In Search of Good Energy Policy. Cambridge: Cambridge University Press.
Recommended reading:
Taylor, S. (2016) The Fall and Rise of Nuclear Power in Britain Cambridge: UIT Printed book at: JBS: HD9698.G72 T39 F3 2016 UL: C212.c.2239
Jamasb, T. and Pollitt, M. (eds.) (2011) The Future of Electricity Demand Cambridge: Cambridge University Press Printed book at: JBS: HD9685.G72 J35 2011 Engineering: DE.190 UL: 235.c.201.356 (South Front 6)
MacKay, D.J.C. (2009) Sustainable energy without the hot air. Cambridge: UIT E-book via withouthotair http://www.withouthotair.com/download.html Printed book at: Engineering: DE.164
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
S4
Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 13/04/2021 14:22
Engineering Tripos Part IIB, 4I7: Electricity & Environment, 2019-20
Module Leader
Lecturer
Lecturer
Lecturer
Timing and Structure
Lent term. 2 hour sessions. Assessment: 100% coursework.
Prerequisites
A basic engineering knowledge of electricity (first year undergraduate) and a familiarity with the units and notation associated with energy science and engineering is an advantage, but not essential. Assessment will be structured so as to be accessible to students from a range of backgrounds.
Aims
The aims of the course are to:
- provide students with a firm foundation in modern electricity policy with an emphasis on the UK.
- introduce students to a wide a variety of mature and emergent electricity generation and demand side technologies.
- expose students to the local, regional and global environmental effects of energy use.
- introduce the key considerations of energy policy and develops frameworks by which progress against policy goals may be achieved.
Objectives
As specific objectives, by the end of the course students should be able to:
- generate scenarios for the future UK electricity system out to 2050
- evaluate and compare the efficacy of different electricity generation technologies
- critique current and future electricity policy
- appreciate how economics and engineering interact in a sustainable electricity system
Content
This module is a postgraduate module of Cambridge Judge Business School. It has its origins as an elective course of the MPhil in Technology Policy and the MPhil in Engineering for Sustainable Development. The module is of the standard size adopted in the Engineering Department and the Judge Business School, i.e. a nominal 16 hours. The course is delivered via one two-hour lecture each week for eight weeks.
Overview - Class Introduction - Michael Pollitt
Lecture 1
- History of Electrical Power and Energy Policy.
- Fundamentals of the UK and USA Electricity System.
- UK Energy Policy and Politics.
- Principles of good energy policy.
- Recent UK Energy White Papers.
Environmental Effects of Fossil Fuel Use and what to do about them (Michael Pollitt)
Lecture 2
- Local Emissions and Impacts
- Putting a Price on Damages?
- Economic approaches to externalities
- Pricing carbon
- Experiences of the EU Emissions Trading System and carbon pricing in Australia
Electricity Demand (Michael Pollitt)
Lecture 3
- Economics of Electricity Demand
- The economics of smart energy services
- Technological aspects of electricity demand
- Social aspects of electricity demand
- Demand side policy
Wind Energy (Jim Platts)
Lecture 4
- Attributes of wind power
- Technology and history
- Wind resources and grid integration
- UK and EU wind policy
- Wind turbine manufacture
Fossil fuel generation, storage and future electricity markets (Michael Pollitt)
Lecture 5
- Current status of fossil-fuel power generation
- Economics of Carbon Capture and Storage
- The economics of electricity storage
- Business models for the internet of energy
- Future electricity market design
Renewables and the Electricity System (Michael Pollitt)
Lecture 6
- Renewables context
- Potential for renewables in the UK
- Place of renewables in electricity system
- How to subsidise renewables
- Lessons from around the world
Electricity Networks (Richard McMahon)
Lecture 7
- Transmission and distribution system engineering considerations
- Design and operation
- History of the grid and legacy issues
- Distributed Generation
- High voltage DC and interconnection
Nuclear Power, Electricity Security and EU Policy (Michael Pollitt)
Lecture 8
- The economics of Nuclear Power
- Energy Security
- EU Energy Policy
- EU 2030 Targets
- Roadmap 2050
- Good electricity policy?
Coursework
| One piece of coursework in two parts | Format |
Due date & marks |
|---|---|---|
|
First part of coursework Use the UK 2050 calculator to generate own electricity related scenario. Learning objectives:
|
Individual report 1500 words anonymously marked |
20 March 2020 [50/100] |
|
Second part of coursework Essay on the 2030 decarbonisation challenge facing the UK electricity system. Learning objectives:
|
Individual Report 1500 words anonymously marked |
20 March 2020 [50/100] |
Booklists
Expected reading:
Grubb, M., Jamasb, T., and Pollitt, M.G. (eds.) (2008) Delivering a low-carbon electricity system. Cambridge: Cambridge University Press Printed book at: JBS: TD195.E4 G72 2008 Engineering: DE.166
Ozawa, M., Chaplin, J., Pollitt, M., Reiner, D. and Warde, P. (eds.) (2019) In Search of Good Energy Policy. Cambridge: Cambridge University Press.
Recommended reading:
Taylor, S. (2016) The Fall and Rise of Nuclear Power in Britain Cambridge: UIT Printed book at: JBS: HD9698.G72 T39 F3 2016 UL: C212.c.2239
Jamasb, T. and Pollitt, M. (eds.) (2011) The Future of Electricity Demand Cambridge: Cambridge University Press Printed book at: JBS: HD9685.G72 J35 2011 Engineering: DE.190 UL: 235.c.201.356 (South Front 6)
MacKay, D.J.C. (2009) Sustainable energy without the hot air. Cambridge: UIT E-book via withouthotair http://www.withouthotair.com/download.html Printed book at: Engineering: DE.164
HM Government 2050 Pathways analysis Report via DECC Publications http://www.decc.gov.uk/en/content/cms/tackling/2050/2050.aspx
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
S4
Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 04/06/2019 11:01
Engineering Tripos Part IIB, 4M23: Electricity and Environment, 2022-23
Module Leader
Lecturers
Lecturer
Timing and Structure
Lent term. 2 hour sessions delivered in person. Assessment: 100% coursework.
Prerequisites
A basic engineering knowledge of electricity (first year undergraduate) and a familiarity with the units and notation associated with energy science and engineering is an advantage, but not essential. Assessment will be structured so as to be accessible to students from a range of backgrounds.
Aims
The aims of the course are to:
- provide students with a firm foundation in modern electricity policy with an emphasis on the UK.
- introduce students to a wide a variety of mature and emergent electricity generation and demand side technologies.
- expose students to the local, regional and global environmental effects of energy use.
- introduce the key considerations of energy policy and develop frameworks by which progress against policy goals may be achieved.
- discuss issues with electrification of heating and transport.
Objectives
As specific objectives, by the end of the course students should be able to:
- critique scenarios for the future UK electricity system out to 2050
- evaluate and compare the efficacy of different electricity generation technologies
- understand current and future electricity policy options
- appreciate how economics and engineering interact in a sustainable electricity system
Content
This module is a postgraduate module of Cambridge Judge Business School. It has its origins as an elective course of the MPhil in Technology Policy and the MPhil in Engineering for Sustainable Development. The module is of the standard size adopted in the Engineering Department and the Judge Business School, i.e. a nominal 16 hours. The course is delivered via one two-hour lecture each week for eight weeks.
We take the UK electricity system as a working example which we will refer to throughout the course.
Overview - Class Introduction (Michael Pollitt)
Lecture 1
- History of Electrical Power and Energy Policy
- Fundamentals of the UK and USA Electricity System
- The nature of the current UK electricity bill and electricity market
- UK Energy Policy and Politics
- Principles of good energy policy
Environmental Effects of Fossil Fuel Use and what to do about them (Michael Pollitt)
Lecture 2
- Local Emissions and Impacts
- Putting a Price on Damages?
- Economic approaches to externalities
- Pricing carbon
- Experiences of the EU Emissions Trading System and carbon pricing in Australia
Electricity Demand (Michael Pollitt)
Lecture 3
- Economics of Electricity Demand
- The economics of smart energy services
- Technological aspects of electricity demand
- Social aspects of electricity demand
- Demand side policy
Fossil fuel generation, storage and future electricity markets (Michael Pollitt)
Lecture 4
- Current status of fossil-fuel power generation
- Economics of Carbon Capture and Storage
- The economics of electricity storage
- Business models for the internet of energy
- Future electricity market design
Renewables and the Electricity System (Michael Pollitt)
Lecture 5
- Renewables context
- Potential for renewables in the UK
- Place of renewables in electricity system
- How to subsidise renewables
- Lessons from around the world
Electrification of heating and transport? Electricity in Net Zero (Michael Pollitt)
Lecture 6
- Electrification of everything?
- Decarbonising heating with electricity
- Decarbonising transport with electricity
- Sector coupling and modelling Net Zero
- Policy recommendations for Net Zero
Electricity Networks (Teng Long)
Lecture 7
- Transmission and distribution system engineering considerations
- Design and operation
- History of the grid and transport electrification
- Distributed Generation
- High voltage DC and interconnection
Nuclear Power, Electricity Security and EU Policy (Michael Pollitt)
Lecture 8
- Nuclear Power Technology
- History and Economics of Nuclear Power
- EU and UK energy security
- National security of electricity supply
- Meeting UK targets by Electricity Market Reform
- Good electricity policy?
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
|
Essay on the 2030 decarbonisation challenge facing the UK electricity system. Learning objectives:
|
Individual Report 2000 words anonymously marked |
24 March 2023 [100/100] |
Booklists
Expected reading:
Glachant, J-M., Joskow, P. and Pollitt, M. (eds.) (2021) Handbook on Electricity Markets. Cheltenham: Edward Elgar. Online on iDiscover.
Ozawa, M., Chaplin, J., Pollitt, M., Reiner, D. and Warde, P. (eds.) (2019) In Search of Good Energy Policy. Cambridge: Cambridge University Press. Online on iDiscover.
Recommended reading:
Taylor, S. (2016) The Fall and Rise of Nuclear Power in Britain Cambridge: UIT Printed book at: JBS: HD9698.G72 T39 F3 2016 UL: C212.c.2239
Jamasb, T. and Pollitt, M. (eds.) (2011) The Future of Electricity Demand Cambridge: Cambridge University Press Printed book at: JBS: HD9685.G72 J35 2011 Engineering: DE.190 UL: 235.c.201.356 (South Front 6)
MacKay, D.J.C. (2009) Sustainable energy without the hot air. Cambridge: UIT E-book via withouthotair http://www.withouthotair.com/download.html Printed book at: Engineering: DE.164
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
S4
Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 24/05/2022 16:44
Engineering Tripos Part IIB, 4M23: Electricity and Environment, 2022-23
Module Leader
Lecturers
Lecturer
Timing and Structure
Lent term. 2 hour sessions delivered in person. Assessment: 100% coursework. The lectures will be recorded. 2-4pm Thursdays. Lecture Room 4 Engineering.
Prerequisites
A basic engineering knowledge of electricity (first year undergraduate) and a familiarity with the units and notation associated with energy science and engineering is an advantage, but not essential. Assessment will be structured so as to be accessible to students from a range of backgrounds.
Aims
The aims of the course are to:
- provide students with a firm foundation in modern electricity policy with an emphasis on the UK.
- introduce students to a wide a variety of mature and emergent electricity generation and demand side technologies.
- expose students to the local, regional and global environmental effects of energy use.
- introduce the key considerations of energy policy and develop frameworks by which progress against policy goals may be achieved.
- discuss issues with electrification of heating and transport.
Objectives
As specific objectives, by the end of the course students should be able to:
- critique scenarios for the future UK electricity system out to 2050
- evaluate and compare the efficacy of different electricity generation technologies
- understand current and future electricity policy options
- appreciate how economics and engineering interact in a sustainable electricity system
Content
This module is a postgraduate module of Cambridge Judge Business School. It has its origins as an elective course of the MPhil in Technology Policy and the MPhil in Engineering for Sustainable Development. The module is of the standard size adopted in the Engineering Department and the Judge Business School, i.e. a nominal 16 hours. The course is delivered via one two-hour lecture each week for eight weeks.
We take the UK electricity system as a working example which we will refer to throughout the course.
Overview - Class Introduction (Michael Pollitt)
Lecture 1
- History of Electrical Power and Energy Policy
- Fundamentals of the UK and USA Electricity System
- The nature of the current UK electricity bill and electricity market
- UK Energy Policy and Politics
- Principles of good energy policy
Environmental Effects of Fossil Fuel Use and what to do about them (Michael Pollitt)
Lecture 2
- Local Emissions and Impacts
- Putting a Price on Damages?
- Economic approaches to externalities
- Pricing carbon
- Experiences of the EU Emissions Trading System and carbon pricing in Australia
Electricity Demand (Michael Pollitt)
Lecture 3
- Economics of Electricity Demand
- The economics of smart energy services
- Technological aspects of electricity demand
- Social aspects of electricity demand
- Demand side policy
Fossil fuel generation, storage and future electricity markets (Michael Pollitt)
Lecture 4
- Current status of fossil-fuel power generation
- Economics of Carbon Capture and Storage
- The economics of electricity storage
- Business models for the internet of energy
- Future electricity market design
Renewables and the Electricity System (Michael Pollitt)
Lecture 5
- Renewables context
- Potential for renewables in the UK
- Place of renewables in electricity system
- How to subsidise renewables
- Lessons from around the world
Electrification of heating and transport? Electricity in Net Zero (Michael Pollitt)
Lecture 6
- Electrification of everything?
- Decarbonising heating with electricity
- Decarbonising transport with electricity
- Sector coupling and modelling Net Zero
- Policy recommendations for Net Zero
Electricity Networks (Teng Long)
Lecture 7
- Transmission and distribution system engineering considerations
- Design and operation
- History of the grid and transport electrification
- Distributed Generation
- High voltage DC and interconnection
Nuclear Power, Electricity Security and EU Policy (Michael Pollitt)
Lecture 8
- Nuclear Power Technology
- History and Economics of Nuclear Power
- EU and UK energy security
- National security of electricity supply
- Meeting UK targets by Electricity Market Reform
- Good electricity policy?
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
|
Essay on the 2030 decarbonisation challenge facing the UK electricity system. Learning objectives:
|
Individual Report 2000 words anonymously marked |
24 March 2023 [100/100] |
Booklists
Expected reading:
Glachant, J-M., Joskow, P. and Pollitt, M. (eds.) (2021) Handbook on Electricity Markets. Cheltenham: Edward Elgar. Online on iDiscover.
Ozawa, M., Chaplin, J., Pollitt, M., Reiner, D. and Warde, P. (eds.) (2019) In Search of Good Energy Policy. Cambridge: Cambridge University Press. Online on iDiscover.
Recommended reading:
Taylor, S. (2016) The Fall and Rise of Nuclear Power in Britain Cambridge: UIT Printed book at: JBS: HD9698.G72 T39 F3 2016 UL: C212.c.2239
Jamasb, T. and Pollitt, M. (eds.) (2011) The Future of Electricity Demand Cambridge: Cambridge University Press Printed book at: JBS: HD9685.G72 J35 2011 Engineering: DE.190 UL: 235.c.201.356 (South Front 6)
MacKay, D.J.C. (2009) Sustainable energy without the hot air. Cambridge: UIT E-book via withouthotair http://www.withouthotair.com/download.html Printed book at: Engineering: DE.164
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S3
Understanding of the requirement for engineering activities to promote sustainable development.
S4
Awareness of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety, and risk (including environmental risk) issues.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 05/01/2023 12:55
Engineering Tripos Part IIB, 4F13: Probabilistic Machine Learning, 2023-24
Module Leader
Lecturers
Prof C Rasmussen
Timing and Structure
Michaelmas term. 14 lectures + 2 examples classes. Assessment: 100% coursework
Prerequisites
3F3 useful
Aims
The aims of the course are to:
- introduce students to basic concepts in machine learning, focusing on statistical methods for supervised and unsupervised learning.
Objectives
As specific objectives, by the end of the course students should be able to:
- demonstrate a good understanding of basic concepts in statistical machine learning.
- apply basic ML methods to practical problems.
Content
Machine learning (ML) is an interdisciplinary field focusing on both the mathematical foundations and practical applications of systems that learn, reason and act. The goal of machine learning is to automatically extract knowledge from observed data for the purposes of making predictions, decisions and understanding the world.
The aim of this module is to introduce students to basic concepts in machine learning, focusing on statistical methods for supervised and unsupervised learning. The module will be structured around three recent illustrative successful applications: Gaussian processes for regression and classification, Latent Dirichlet Allocation models for unsupervised text modelling and the TrueSkill probabilistic ranking model.
- Linear models, maximum likelihood and Bayesian inference
- Gaussian distribution and Gaussian process
- Model selection
- The Expectation Propagation (EP) algorithm
- Latent variable models
- The Expectation Maximization (EM) algorithm
- Dirichlet Distribution and Dirichlet Process
- Variational inference
- Generative models, graphical models: Factor graphs
Lectures will be supported by Octave/MATLAB demonstrations.
A detailed syllabus and information about the coursework is available on the moodle website: https://www.vle.cam.ac.uk/course/view.php?id=69021
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
|
[Coursework activity #1 Gaussian Processes] Coursework 1 brief description Learning objective:
|
Individual/group Report / Presentation anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
day during term, ex: Fri week 5 [20/60] |
|
[Coursework activity #2 Probabilistic Ranking] Coursework 2 brief description Learning objective:
|
Individual Report Anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
Fri week 7 [20/60] |
| [Coursework activity #3 Latent Dirichlet Allocation models for documents] Coursework 3 brief description Learning objective:
|
Individual Report Anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
Fri week 9 [20/60] |
Booklists
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 30/05/2023 15:31
Engineering Tripos Part IIB, 4F13: Probabilistic Machine Learning, 2024-25
Module Leader
Lecturers
Prof C Rasmussen
Timing and Structure
Michaelmas term. 14 lectures + 2 examples classes. Assessment: 100% coursework
Prerequisites
3F3 useful
Aims
The aims of the course are to:
- introduce students to basic concepts in machine learning, focusing on statistical methods for supervised and unsupervised learning.
Objectives
As specific objectives, by the end of the course students should be able to:
- demonstrate a good understanding of basic concepts in statistical machine learning.
- apply basic ML methods to practical problems.
Content
Machine learning (ML) is an interdisciplinary field focusing on both the mathematical foundations and practical applications of systems that learn, reason and act. The goal of machine learning is to automatically extract knowledge from observed data for the purposes of making predictions, decisions and understanding the world.
The aim of this module is to introduce students to basic concepts in machine learning, focusing on statistical methods for supervised and unsupervised learning. The module will be structured around three recent illustrative successful applications: Gaussian processes for regression and classification, Latent Dirichlet Allocation models for unsupervised text modelling and the TrueSkill probabilistic ranking model.
- Linear models, maximum likelihood and Bayesian inference
- Gaussian distribution and Gaussian process
- Model selection
- The Expectation Propagation (EP) algorithm
- Latent variable models
- The Expectation Maximization (EM) algorithm
- Dirichlet Distribution and Dirichlet Process
- Variational inference
- Generative models, graphical models: Factor graphs
Lectures will be supported by Octave/MATLAB demonstrations.
A detailed syllabus and information about the coursework is available on the moodle website: https://www.vle.cam.ac.uk/course/view.php?id=69021
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
|
[Coursework activity #1 Gaussian Processes] Coursework 1 brief description Learning objective:
|
Individual/group Report / Presentation anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
day during term, ex: Fri week 5 [20/60] |
|
[Coursework activity #2 Probabilistic Ranking] Coursework 2 brief description Learning objective:
|
Individual Report Anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
Fri week 7 [20/60] |
| [Coursework activity #3 Latent Dirichlet Allocation models for documents] Coursework 3 brief description Learning objective:
|
Individual Report Anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
Fri week 9 [20/60] |
Booklists
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 31/05/2024 10:08
Engineering Tripos Part IIB, 4F13: Probabilistic Machine Learning, 2022-23
Module Leader
Lecturers
Prof C Rasmussen, Dr D Krueger
Timing and Structure
Michaelmas term. 14 lectures + 2 examples classes. Assessment: 100% coursework
Prerequisites
3F3 useful
Aims
The aims of the course are to:
- introduce students to basic concepts in machine learning, focusing on statistical methods for supervised and unsupervised learning.
Objectives
As specific objectives, by the end of the course students should be able to:
- demonstrate a good understanding of basic concepts in statistical machine learning.
- apply basic ML methods to practical problems.
Content
Machine learning (ML) is an interdisciplinary field focusing on both the mathematical foundations and practical applications of systems that learn, reason and act. The goal of machine learning is to automatically extract knowledge from observed data for the purposes of making predictions, decisions and understanding the world.
The aim of this module is to introduce students to basic concepts in machine learning, focusing on statistical methods for supervised and unsupervised learning. The module will be structured around three recent illustrative successful applications: Gaussian processes for regression and classification, Latent Dirichlet Allocation models for unsupervised text modelling and the TrueSkill probabilistic ranking model.
- Linear models, maximum likelihood and Bayesian inference
- Gaussian distribution and Gaussian process
- Model selection
- The Expectation Propagation (EP) algorithm
- Latent variable models
- The Expectation Maximization (EM) algorithm
- Dirichlet Distribution and Dirichlet Process
- Variational inference
- Generative models, graphical models: Factor graphs
Lectures will be supported by Octave/MATLAB demonstrations.
A detailed syllabus and information about the coursework is available on the moodle website: https://www.vle.cam.ac.uk/course/view.php?id=69021
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
|
[Coursework activity #1 Gaussian Processes] Coursework 1 brief description Learning objective:
|
Individual/group Report / Presentation anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
day during term, ex: Fri week 5 [20/60] |
|
[Coursework activity #2 Probabilistic Ranking] Coursework 2 brief description Learning objective:
|
Individual Report Anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
Fri week 7 [20/60] |
| [Coursework activity #3 Latent Dirichlet Allocation models for documents] Coursework 3 brief description Learning objective:
|
Individual Report Anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
Fri week 9 [20/60] |
Booklists
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 24/05/2022 13:12
Engineering Tripos Part IIB, 4F13: Probabilistic Machine Learning, 2025-26
Module Leader
Lecturers
Dr H Ge, Dr A Tewari, Dr G Cantwell
Timing and Structure
Michaelmas term. 14 lectures + 2 examples classes. Assessment: 100% coursework
Prerequisites
3F3 useful
Aims
The aims of the course are to:
- introduce students to basic concepts in machine learning, focusing on statistical methods for supervised and unsupervised learning.
Objectives
As specific objectives, by the end of the course students should be able to:
- demonstrate a good understanding of basic concepts in statistical machine learning.
- apply basic ML methods to practical problems.
Content
Machine learning (ML) is an interdisciplinary field focusing on both the mathematical foundations and practical applications of systems that learn, reason and act. The goal of machine learning is to automatically extract knowledge from observed data for the purposes of making predictions, decisions and understanding the world.
The aim of this module is to introduce students to basic concepts in machine learning, focusing on statistical methods for supervised and unsupervised learning. The module will be structured around three recent illustrative successful applications: Gaussian processes for regression and classification, Latent Dirichlet Allocation models for unsupervised text modelling and the TrueSkill probabilistic ranking model.
- Linear models, maximum likelihood and Bayesian inference
- Gaussian distribution and Gaussian process
- Model selection
- The Expectation Propagation (EP) algorithm
- Latent variable models
- The Expectation Maximization (EM) algorithm
- Dirichlet Distribution and Dirichlet Process
- Variational inference
- Generative models, graphical models: Factor graphs
Lectures will be supported by Octave/MATLAB demonstrations.
A detailed syllabus and information about the coursework is available on the moodle website: https://www.vle.cam.ac.uk/course/view.php?id=69021
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
|
[Coursework activity #1 Gaussian Processes] Coursework 1 brief description Learning objective:
|
Individual/group Report / Presentation anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
day during term, ex: Fri week 5 [20/60] |
|
[Coursework activity #2 Probabilistic Ranking] Coursework 2 brief description Learning objective:
|
Individual Report Anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
Fri week 7 [20/60] |
| [Coursework activity #3 Latent Dirichlet Allocation models for documents] Coursework 3 brief description Learning objective:
|
Individual Report Anonymously marked for MPHIL/MLSALT & Undergraduates Nonanonymously marked for PhDs |
Fri week 9 [20/60] |
Booklists
Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.
Examination Guidelines
Please refer to Form & conduct of the examinations.
UK-SPEC
This syllabus contributes to the following areas of the UK-SPEC standard:
Toggle display of UK-SPEC areas.
GT1
Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.
IA1
Apply appropriate quantitative science and engineering tools to the analysis of problems.
IA2
Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.
KU1
Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.
KU2
Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
E2
Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
E4
Understanding of and ability to apply a systems approach to engineering problems.
P1
A thorough understanding of current practice and its limitations and some appreciation of likely new developments.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P8
Ability to apply engineering techniques taking account of a range of commercial and industrial constraints.
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US2
A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 04/06/2025 13:30
Pages
