Engineering Tripos Part IIB, 4F10: Deep Learning & Structured Data, 2025-26
Module leader
Lecturer
Timing and Structure
Michaelmas term. 14 lectures + 2 examples classes. Assessment: 100% exam
Prerequisites
Part IIA Modules 3F1, 3F3 and 3F8 advisable
Aims
The aims of the course are to:
- This module aims to teach the basic concepts of deep learning and forms of structure that can be used for generative and discriminative models. In addition, the use of models for classifying structured data, such as speech and language, will be discussed
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand the basic principles of pattern classification and deep learning;
- Understand generative and discriminative models for structured data;
- Understand the application of deep-learning to structured data;
- Be able to apply pattern processing techniques to practical applications.
Content
Introduction (1L)
Links with 3F8 and 4F13. General machine learning, examples of structured data, DNA, vision, speech and language processing.
Decision Boundaries and Probability of Error (1L)
Definition of a decision boundary and forms that result from Gaussian class-conditional probability density functions. Calculation of probability of Error.
Graphical Models and Conditional Indpendence (1L)
Graphical models and Bayesian networks. Simple inference examples.
Latent Variable and Sequence Models (2L)
Gaussian mixture models and factor analysis; hidden Markov models and expectation maximisation.
Deep Learning (3L)
Generative and discriminative deep models. Forms of network and activation functions. Convolutional neural networks, density neural networks. Optimisation approaches (first/second order methods, adaptive learning rates) and initialisation.
Deep Learning for Sequences (2L)
Recurrent neural networks and variants of RNN including bidirectional RNNs. Transformer architectures including encoder-only, encode-decoder and decoder only models. Aligning large-language models (LLMs) and Chain of Thought (CoT).
Ensemble Methods and Model Distillation (1L)
Deep ensembles, model combination and model distillation approaches.
Support Vector Machines (2L)
Maximum margin classifiers, handling non-separable data, training SVMs, non-linear SVMs, kernel functions. Multi-class SVMs.
Kernels over Structured Data (1L)
String kernels, graph kernels and Fisher kernels.
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.
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.
Last modified: 05/06/2025 11:55
Engineering Tripos Part IIB, 4F7: Statistical signal and network models, 2025-26
Module Leader
lecturers
Timing and Structure
Michaelmas term. 16 lectures (including examples classes). Assessment: 100% exam
Prerequisites
3F1, 3F3, 3F8 recommended. 3M1 useful.
Aims
The aims of the course are to:
- Introduce time-series models, in particular State-space models and hidden Markov models; understand their role in applications of signal processing.
- Develop techniques for fitting statisical models to data and estimating hidden signals from noisy observations.
- Introduce network models, graph algorithms, and techniques to analyse large scale relational data
Objectives
As specific objectives, by the end of the course students should be able to:
- Understand state-space models, hidden Markov models, and network models including their mathematical characterisation, strengths and limitations.
- Execute the necessary computational tasks involved in fitting the models to data, to estimate unobserved quantities and make future predictions.
- Understand the computational methodology employed, their mathematical derivation, their strengths and weaknesses, how to execute them, and their use more generally in Statistical and data-centric engineering problems.
Content
This course is about fitting statistical models to data that arrives sequentially over time and across network structures. Once an appropriate model has been fitted, tasks such as predicting future trends or estimating quantities not directly observed can be performed. The statistical modelling and computational methodology covered by this course is widely used in many applied areas. For example, data that arrives sequentially over time is a common occurrence in Signal Processing (Engineering), Finance, Machine Learning, Environmental statistics etc.
The model that most appropriately describes data that arrives sequentially over time is a time-series model, an example of which is the ARMA model (studied in 3F3.) However, this course will look at more versatile models that incorporate hidden or latent state variables as these are able to account for richer behaviour. Also, models that aim describe how many really physical processes evolve over time often necessarily have to incorporate unobserved hidden states that form a Markov process.
Besides changing over time, many data are distributed over different individuals or sites. For example, users of a social media platform will each have different properties. Networks (graphs) provide a simple formalism to analyse distributed systems composed of small but interrelated parts.
State space models and time series:
The model that most appropriately describes data that arrives sequentially over time is a time-series model, an example of which is the AR model (studied in 3F3). However, this course will look at more versatile stochastic (random) state-space models that incorporate hidden or latent state variables as these are able to account for richer behaviour. Also, models that aim describe how many really physical processes evolve over time often necessarily have to incorporate unobserved hidden states that form a Markov process.
-
Introduction to state-space models and optimal linear filtering; the Kalman filter; exemplar problems in signal processing.
-
Introduction to hidden Markov models: definition; inference/estimation aims; exact computation of the conditional probability distributions.
-
Importance sampling: introduction; weight degeneracy; statistical properties.
-
Sequential importance sampling and resampling (also known as the particle filter): application to hidden Markov models; filtering; smoothing.
-
Calibrating hidden Markov models: maximum likelihood estimation and its implementation.
-
Exemplar problems in Signal Processing.
-
Examples Papers.
Networks modelling:
Besides changing over time, many data are distributed over different individuals or sites. For example, users of a social media platform will each have different properties. Networks (graphs) provide a simple formalism to analyse distributed systems composed of small but interrelated parts. We will cover:
-
· Fundamentals, basic graph theory and algorithms.
-
· Metrics: centrality (e.g. PageRank), assortativity, clustering, diameter ("six degrees of separation").
-
· Models of networks: Erdős–Rényi, small-world and scale free.
-
· Models on networks: Spreading, reliability and percolation.
-
· Community detection and stochastic block models.
-
· Graph spectra and their applications.
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.
Last modified: 04/06/2025 13:30
Engineering Tripos Part IIB, 4F5: Advanced Information Theory and Coding, 2025-26
Module Leader
Lecturer
Prof A Guillen i Fabregas and Dr Jossy Sayir
Timing and Structure
Lent term. 16 lectures. Assessment: 100% exam
Prerequisites
3F7 assumed, 3F1, 3F4 useful but not necessary
Aims
The aims of the course are to:
- Learn about applications of information theory to hypothesis testing as well as refinements of source and channel coding theorems through error exponents.
- Introduce students to the principles of algebraic coding and Reed Solomon coding in particular
- Give students an overview of cryptology with example of techniques that share the same mathematical background as algebraic coding.
Objectives
As specific objectives, by the end of the course students should be able to:
- have gained an appreciation for the connection between information-theoretic concepts and fundamental problems in statistics
- have a good understanding of the derivations of error exponents for data compression and transmission
- have a good understanding of the fundamental connections between hypothesis testing and information theory
- have gained a practical understanding of the algebraic fundamentals that underlie channel coding and cryptology
- understand the properties of linear block codes over finite fields
- be able to implement encoders and decoders for Reed Solomon codes
- have gained an overview of methods and aims in cryptology (including cryptography, crypt- analysis, secrecy, authenticity)
- be familiar with one example each of a block cipher and a stream cipher
- be able to implement public key cryptosystems, in particular the Diffie-Hellman and Rivest- Shamir-Adleman (RSA) systems
Content
-
This course will introduce students to applications of information theory and coding theory in statistics, information storage, and cryptography.
The first part of the course will discuss applications of information theory to universal data compression, statistics, and inference.
The second part of the course will expand linear coding principles acquired in 3F7 to non-binary codes over finite fields. After establishing the algebraic fundamentals, we will cover Reed-Solomon coding, a technique used in a wide range of communication and storage systems (hard disks, blu ray discs, QR codes, USB mass storage device class, DNA storage, and others.)
The final part of the course will introduce the discipline of cryptology, which includes cryptography, the essential art of ensuring secrecy and authenticity, and cryptanalysis, the dark art of breaking that secrecy. The course will cover a number of methods to provide secrecy, ranging from mathematically provable secrecy to public key methods through which computationally secure communication links can be established over public channels.
Information theory and statistics (7-9L, Prof Albert Guillén i Fàbregas)
- Source coding, optimum fixed-rate coding, error exponents
- Binary hypothesis testing, probability of error, error exponents, Stein's lemma
- M-ary hypothesis testing, probability of error
- Channel coding, connection with hypothesis testing, perfect codes, error exponents
Introduction to practical number theory and algebra (2-3L, Dr Jossy Sayir)
- Elementary number theory
- Groups and fields, extension fields
- 3 equivalent approaches to multiplication in extension fields
- Matrix operations and the Discrete Fourier Transform
Algebraic Coding (3L, Dr Jossy Sayir)
- Linear coding and the Singleton Bound
- Distance profiles and MacWilliams Identities
- Blahut’s theorem
- Reed Solomon (RS) codes
- Encoding and decoding of RS codes
Introduction to Cryptology (2L, Dr Jossy Sayir )
- Overview of cryptology
- Stream ciphers, examples
- Block ciphers, examples
- Public key cryptography, basic techniques
Further notes
Examples papers
Examples papers consist of a recommended list of problems to solve in the lecture notes.
Coursework
none
Booklists
- Information Theory:
- Elements of Information Theory, T. M. Cover & J. A. Thomas, Wiley-Interscience, 2nd Ed, 2006.
- Information Theory: Coding Theorems for Discrete Memoryless Systems, I. Csiszàr & J. Körner, Cambridge University Press, 2nd Ed. 2011.
- Coding theory:
- The Theory of Error-Correcting Codes, F. J. MacWilliams & N. J. A. Sloane, North Holland.
- Algebraic Codes for Data Transmission, Richard E. Blahut, Cambridge University Press, 2003 (Online 2012)
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.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
E1
Ability to use fundamental knowledge to investigate new and emerging technologies.
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).
US1
A comprehensive understanding of the scientific principles of own specialisation and related disciplines.
US4
An awareness of developing technologies related to own specialisation.
Last modified: 04/06/2025 13:30
Engineering Tripos Part IIB, 4F3: An Optimisation Based Approach to Control, 2025-26
Module Leader and lecturer
Lecturer
Prof I Lestas, Prof G Vinnicombe
Timing and Structure
Lent term. 14 lectures + 2 examples classes, Assessment: 100% exam
Prerequisites
3F1 and 3F2 useful
Aims
The aims of the course are to:
- introduce methods for feedback system design based on the optimization of an objective, including reinforcement learning and predictive control.
- demonstrate how such control laws can be computed and implemented in practice.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand the derivation and application of optimal control methods.
- appreciate the main ideas, applications and techniques of predictive control and reinforcement learning.
Content
Optimal Control (7L + 1 examples class, Prof I Lestas)
- Formulation of convex optimisation problems
- Status of theoretical results and algorithms
- Formulation of optimal control problems. Typical applications
- Optimal control with full information (dynamic programming)
- Control of Linear Systems with a quadratic objective function
- Output feedback: ‘LQG’ control
- Control design with an “H-infinity” criterion
Predictive Control and an Introduction to Reinforcement Learning (7L + 1 examples class, Dr T Burghi)
- What is predictive control? Importance of constraints. Flexibility of specifications. Typical applications
- Basic formulation of predictive control problem without constraints and the receding horizon concept. Comparison with unconstrained Linear Quadratic Regulator
- Including constraints in the problem formulation. Constrained convex optimization
- Terminal conditions for stability
- Emerging applications: advantages and challenges
- Policy and generalized policy iteration; rollout algorithms and predictive control
- Approximate dynamic programming
- Deep neural nets as universal approximators for value and policy.
- Simulation based vs state space models - Q learning.
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.
Last modified: 04/06/2025 13:30
Engineering Tripos Part IIB, 4F2: Robust and Nonlinear Control, 2025-26
Module Leader
Lecturer
Timing and Structure
Lent term. 14 lectures + 2 computer lab sessions. Assessment: 100% coursework
Prerequisites
3F2 assumed.
Aims
The aims of the course are to:
- introduce fundamental concepts from nonlinear dynamic systems
- introduce techniques for the analysis and control of nonlinear and multivariable systems.
Objectives
As specific objectives, by the end of the course students should be able to:
- apply standard analysis and design tools to multivariable and nonlinear feedback systems.
- appreciate the diversity of phenomena in nonlinear systems.
Content
Part I. ROBUST CONTROL (7L + 1 Computer Lab session, Prof F Forni)
1. Uncertainty and Nonlinearity in control systems: simple models.
2. Signal spaces and system gains.
3. The small-gain theorem and the passivity theorem. Phase versus gain uncertainties
4. Dissipativity theory
5. Robust stability and performance. Stability margins.
6. An introduction to H-infty control.
7. Gap metrics
PART 2: NONLINEAR SYSTEMS (7L + 1 computer lab session, Prof F Forni)
1. Small and large signal analysis. Contractive systems. Fading memory operators.
2. State-space analysis and Nyquist. Differential stability. Differential dissipativity. Differential circle criterion.
3. Feedback systems: simple models.
4. Phase portrait analysis.
5. Analysis and design of switches and clocks. Robust differential control.
6. Monotone systems. Scale relative graphs (SRGs). Applications in biology.
7. Describing function analysis.
Further notes
ASSESSMENT
Coursework only.
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
|
[Coursework activity #1 Robust control of haptic interfaces Coursework 1 brief description Learning objective:
|
Individual Report anonymously marked |
27 February 2026 [30/60] |
|
[Coursework activity #2 Feedback oscillations control ] Coursework 2 brief description Learning objective:
|
Individual Report anonymously marked |
27 March 2026 [30/60] |
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.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
D4
Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
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).
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.
Last modified: 20/01/2026 11:10
Engineering Tripos Part IIB, 4F1: Control System Design, 2025-26
Module Leader
Lecturer
Lab Leader
Timing and Structure
Michaelmas term. 12 lectures + 2 examples classes + coursework. Assessment: 75% exam/25% coursework
Prerequisites
3F1 and 3F2 useful
Aims
The aims of the course are to:
- establish for the students a fundamental approach to the design of linear control systems.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand the role and importance of feedback for the control of uncertain dynamical systems.
- demonstrate the information conveyed via root locus diagrams for transient behaviour and basic frequency response analysis using Nyquist (polar) and Bode plots.
- following its basic derivation, illustrate the use of the Nyquist stability criterion with both open loop stable and open loop unstable systems;
- understand factors which limit achievable performance in feedback systems.
- use analytical tools to understand trade-offs (e.g. Bode gain/phase relations, sensitivity integrals).
- translate general requirements for robustness and performance into specifications on the open-loop frequency response.
- use computer software for simple control system design and system simulation
- design simple compensators to achieve such specifications.
Content
Control system design (11L)
- System dynamics, stability and instability, principles and use of root locus plots, derivation of Nyquist stability criterion, Bode theorems and plots.
- Design of simple P.I.D. controllers and phase compensators. Sensitivity, complementary sensitivity and SISO robustness. Non-minimum phase systems and limitations, bandwidth. Delays in systems.
- Two degree of freedom design.
Introduction to Coursework (1L)
Case studies and simulation.
Coursework
Case studies and design by simulation and computer software, e.g. use of Matlab. Four hours DPO time plus report (further four hours).
| Coursework | Format |
Due date & marks |
|---|---|---|
|
Coursework activity #1 Final Coursework 1 brief description Learning objective:
|
Individual Report anonymously marked |
Fri week 9 [15/60] |
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.
D1
Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.
D4
Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.
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).
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.
Last modified: 04/06/2025 13:30
Engineering Tripos Part IIB, 4E12: Project Management, 2025-26
Module Leader
Lecturer
Dr N Oraiopoulos
Timing and Structure
Lent term. Eight 2-hour sessions + coursework. Assessment: 100% coursework (please see details below)
Aims
The aims of the course are to:
- introduce the principal elements of project management; equipping students with the basic skills to enable them to manage a project and to operate effectively as part of a project team.
Objectives
As specific objectives, by the end of the course students should be able to:
- use a set of tools and frameworks that enable effective project planning and execution.
- understand the need for appropriate governance structures and control systems in the delivery of project objectives.
- run a small scale project and to be an effective member of any project team.
Content
Session 1: Introduction to Project Management
- Wide applicability of Project Management (PM)
- Reasons why project fail
- History of PM: Roots of change
- Critical Path Method (CPM): Dragonfly Case - part 1
Session 2: Project Planning and Control
- Beyond the CPM; the PERT method
- EVA/ABC
- Design Structure Matrix
- Monte Carlo Simulation and Limitations
- Dragonfly Case - part II
Session 3: Ambiguity in Large Innovative Projects
- Flying Car Case
- Managing Residual Uncertainty
- Strategies for Managing Ambiguity
Session 4: Project Risk Management
- Intro to PM Risk Management
- Review of decision trees
- Real Options
Session 5: Managing Project Teams
- In-class exercise
- Heavyweight vs lightweight project managers
- Functional vs. project-based organizations
Session 7: Portfolio Management
- Scoring tables and financial indices: value and limitations
- Risk return matrices and visual tools
- The need for diversification in high risk projects
Session 8: Project Management Contracts
- Fixed fee/Time and Materials/Performance-based contracts
- Comparison and applicability of each contract type
- Risk-sharing through optimal contract design
- Barganining power and negotiations
Coursework
Individual Coursework (100%).
| Coursework | Format |
Due date & marks |
|---|---|---|
|
[Coursework activity: Project Prioritization and Analysis / Final] Brief description You will be given a case study and asked to analyse the risk profiles of different projects portfolios. You will have to make a recommendation regarding what projects should the company select and defend your recommendation with both quantitative and qualitative arguments. Learning objectives:
|
Individual Report anonymously marked |
Beginning of Easter Term
|
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.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S2
Extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately to strategic and tactical issues.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
P7
Awareness of quality issues.
Last modified: 04/06/2025 13:28
Engineering Tripos Part IIB, 4E11: Strategic Management, 2025-26
Module Leader
Timing and Structure
Lent term. 8 sessions + coursework.
Aims
The aims of the course are to:
- provide participants with an opportunity to discuss the strategic challenges facing managers in today’s business environment and to develop a facility for critical strategic thinking.
Objectives
As specific objectives, by the end of the course students should be able to:
- show a critical, reflective approach to managerial concepts.
- show familiarity with some of the key models used in strategic analysis.
- show some understanding of these models' application and limitations.
- show a broad overview of managerial disciplines and their interdependency.
Content
Overview
Why are some firms more successful than others, and what, if anything, does strategy have to do with it? Because superior performance accrues to firms with a competitive advantage, this course examines how firms develop and maintain competitive advantage. Strategy is the field of management that has been developed to help general managers (as opposed to functional managers whose responsibilities focus on one particular function such as finance, production, marketing, human resources, IT etc.), make better decisions that will improve the competitive position of the organization in the long run and create value for its key stakeholders. The field of strategy is made up of all theories, concepts, methods and tools that top managers can use to ensure the profitable and long-term growth of their organizations. It divides into works on content of strategy - what activities and sectors the organization will compete in and how it will compete in those -, and process of strategy - the mechanisms by which organizations choose to compete in certain ways, activities and sectors and how they implement these choices. Both process and content approaches address issues of business and corporate-level strategy.
Course Content:
- Nature and context of strategic management
- Theories, concepts and models of strategic analysis
- Applications to strategic management practice
Learning Objectives
The fundamental focus of the strategy core course is on helping participants develop skills that will allow them to make robust strategic decisions in the face of uncertainty and complexity. By the end of the module participants will be able to synthesize the set of concepts and frameworks you have gained to address challenging strategic management problems. In particular, you will be able to:
- Analyze industry structure and environmental trends to assess industry potential
- Evaluate firms’ competitive positioning and assess firm-level resources and capabilities
- Formulate business-unit and corporate strategies to achieve competitive advantage
- Evaluate and manage complex ethical and social issues facing firms in implementing strategy and organizing the firm for strategic success.
Method of Instruction
Method of Instruction:
The course will be taught through a mixture of case discussions and lectures. Each session of the course will focus on a specific subset of corporate strategic decisions. The class will mix theoretical content (with a particular focus on mastering the tools to present, frame and analyse a corporate strategy) and practical cases. Students will be invited to participate and share their thoughts on theoretical and practical considerations in relation with the content of the course. They should feel free to ask questions and discuss, especially if they want to clarify or challenge the content covered in the course.
Assessment - Due March 27, 2025
Regarding the form of individual assessment, it will be 100% coursework (essay of 2,500 words):
You will prepare and write up a complete strategic analysis of the current and prospects for a company of your choice. The paper should contain a comprehensive industry and market analysis, including a detailed analysis of relevant competitors, and conclude with strategic recommendations (including corporate and business strategies) for top management. The selection of companies for strategic analysis is entirely up to each student; however, firms in industries that are in transition or firms that are undergoing major strategic changes are potentially more interesting. You should conclude your essay with a brief description of if/how you used LLM tools in the preparation of your analysis.
Teaching Staff
| Dr Chris Coleridge |
Department: |
Strategy and International Business |
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Email: |
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Tel: |
+44 (0) 1223 768128 |
Course Structure & Selected Readings
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SESSION |
DATE |
TOPIC |
READING |
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1. |
What is Strategy |
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2. |
Gaining a Competitive Advantage by Building on Particular Industry Features |
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3. |
Resource-Based Approaches to Strategy and Growth |
Case: Netflix vs Disney, Grant 12th Ed, p358 |
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4. |
Disruption |
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5. |
Strategic Management of Innovation |
Case: Nvidia, Grant 12th Ed, p401 |
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6. |
Ecosystem Strategy |
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7. |
Platform Strategy |
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8. |
Strategy Formulation and Implementation |
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Book
Contemporary Strategy Analysis, 12th Edition
Robert M. Grant
ISBN: 978-1394251599 December 2024 512 Pages
Strategic Management
The lectures will cover a range of topics that provide a basic introduction to strategic management. In each session, the lecturer will introduce a basic concept and explain its role in the strategic management process. The class will then analyse a case or discuss the situation facing some well-known firm in order to explore the application of the concept. The module will cover eight topics.
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1. What is Strategy |
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2. Gaining a Competitive Advantage |
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3. The Resource-based View |
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4. Disruption |
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5. Strategic Management of Innovation |
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6. Ecosystem Strategy |
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7. Platform Strategy |
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8. Strategy Formulation and Implementation |
Coursework
| Coursework | Format |
Due date & marks |
|---|---|---|
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Coursework activity: Final You will prepare a complete strategic analysis of the current and future prospects for a company of your choice. The paper should contain a comprehensive industry and market analysis, including a detailed analysis of relevant competitors, and conclude with strategic recommendations (including corporate and business strategies) for top management. The selection of companies for strategic analysis is entirely up to each student; however, firms in industries that are in transition or firms that are undergoing major strategic changes are potentially more suitable for analysis. You should conclude your essay with a brief description of if/how you used LLM tools in the preparation of your analysis.
Learning objective:
Grading criteria:
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Individual Essay of 2500 words anonymously marked |
27 March 2025 5pm
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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.
S2
Extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately to strategic and tactical issues.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
Last modified: 21/11/2025 13:59
Engineering Tripos Part IIB, 4E6: Accounting & Finance, 2025-26
Module Leader
Lecturers
Lecturer
Timing and Structure
Michaelmas term. 16 lectures (including examples classes). Assessment: 100% exam
Aims
The aims of the course are to:
- provide an introductory understanding of financial reporting and decision making by companies.
Objectives
As specific objectives, by the end of the course students should be able to:
- construct the company financial statements from a jumble of raw data.
- interpret these statements.
- understand how to identify and finance the investments companies should undertake.
- understand why and how companies compensate their investors.
Content
The first part of the module examines fundamental accounting concepts, and shows how to construct and interpret company accounts, a critical source of information to outside investors. The second part of the module tackles the three key areas of company decision making: the capital budgeting decisions of how the company should invest; the financing decisions of how the company should raise the investment capital; and the payout decisions of how the company should compensate its shareholder
Financial Accounting
Detailed discussion of fundamental accounting concepts; construction of company financial statements (balance sheet, income statement, cash flow statement); an awareness of creative accounting
Finance
Nature and objectives of finance; time value of money and risk versus return; capital budgeting decisions (opportunity cost of capital, investment rules such as Net Present Value; financing decisions (debt versus equity); payout decisions (dividends and share repurchases).
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.
S1
The ability to make general evaluations of commercial risks through some understanding of the basis of such risks.
S2
Extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately to strategic and tactical issues.
E3
Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
Last modified: 04/06/2025 13:28
Engineering Tripos Part IIB, 4E5: International Business, 2025-26
Lecturer
Timing and Structure
Lent term. 8 x 2 hour sessions. Assessment: 100% coursework
Aims
The aims of the course are to:
- Deepen understanding of the international business environment through class lectures and discussion on :
- (i) globalization;
- (ii) megatrends such as technology, climate change, macroeconomics;
- (iii) socio-cultural and political variation in business environments;
- (iii) international business strategy
Objectives
As specific objectives, by the end of the course students should be able to:
- appreciate the complexities of the international organizational environment when making strategic decisions;
- understand and apply the concepts and theories of international business strategy.
- understand and apply key concepts related to the institution-based view in strategic management;
- conduct a comparative analysis of institutional environments in different countries;
- develop strategies to reduce political risks and manage cultural differences;
Content
In an era of rapid technological change, geopolitical uncertainty, climate change, and global interdependence, this course explores what it really takes to succeed in international business. International expansion offers companies immense potential—new markets, talent pools, supply chains, and innovation ecosystems—but also exposes them to complex challenges: trade wars, political & regulatory complexity, climate pressures, and institutional voids.
This course equips students with a strategic and systems-level perspective on how businesses navigate these cross-border dynamics. While we explore foundational themes like market entry strategies and global industry analysis, and we go further—unpacking the social, political, and cultural dimensions that shape business decisions in different parts of the world. From managing institutional differences to understanding stakeholder legitimacy in diverse contexts, students will develop the ability to think holistically and act strategically in an international setting.
During eight interactive lectures we will address the advantages and disadvantages of different foreign entry modes, critically discuss highly-influential ideas on understanding cross-border differences, examine exemplary internationalisation cases and enter into short class debates. This course will give you a powerful strategic lens for operating in an interconnected and disrupted global economy. Whether you're aiming for a career in multinational corporations, international startups, consulting, or policy, this module will help you make sense of the world—and how businesses navigate it.
The course is structured around eight two-hour sessions comprising highly interactive lectures and class discussions around case studies, examples and contemporary news events.
- Introduction to international business;
- Globalization: historic and current trends;
- The institution-based view in international business;
- Bridging institutional distances: "Glocalization" Strategies
- Formal institutions: differences in economic, legal and political systems;
- Informal institutions: cross-cultural differences;
- Institutional voids: differences in institutional development;
- International Business and the Anthropocene
A selection of guest speakers including entrepreneurs, business leaders and subject matter experts will bring in additional perspectives
Course Outline
ENGINEERING TRIPOS PART IIB – 2025-26 Module 4E5: International Business
Course Outline
Please see Boolist on the Moodle Page for all required and supplementary reading, including case preparation materialsfor each session.
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Session |
Learning Points |
Preparation for the Final Assignment |
|---|---|---|
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1. Defining International Business
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- Defining what international business is about - Understanding the aims and structure of the course CASE: Why did Grab build Maps? |
Start developing ideas for your assignment scenario |
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2. Globalization: Historic and Current Trends
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- Defining what globalization is and how it may affect business - Understanding the different sides of debates around globalization - What are critical resources for the new economy? Is Tiktok / social media a matter of national security? |
Decide on your assignment scenario |
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3. The Institution-Based View in International Business
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- Understanding what are institutions - Being able to apply the institution-based view as a lens to international business issues through the use of the notion of “institutional distance” - Guest Lecture |
Acquaint yourself with the resources available to study institutional distance and explore how your selected home and host country may differ. |
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4. Formal Institutions: Differences in Economic, Legal and Political Systems
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- Being able to classify different economic, legal and political systems - Understanding the different dimensions across which economic systems may differ and the impact on business CASE: Walmart in Europe - Guest Lecture |
Assess the differences across your selected home and host country |
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5. Bridging Institutional Distances: Glocalization
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- Understanding the impact of institutional distances on local market entry - Understanding the need for balancing global and localization strategies CASE: IKEA in India |
Assess the differences across your selected home and host country and consider potential localization needs |
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6. Institutional Voids: Emerging Economies
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- Being able to classify differences in institutional development - Understanding the impact of institutional development on international business CASE: For Some Platforms, Network Effects Are No Match for Local Know-How - Uber vs Grab |
Assess the differences in economic development across your selected home and host country.
Select two dimensions of institutional distance that you will focus on in your paper. |
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7 International Business and the Anthropocene
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- Develop an informed opinion on how the international business environment is going to evolve - Reflect on the role of international businesses in the unfolding global stage CASE: Transparency, Traceability, and Compliance in Uniqlo's Global Value Chain |
Write your paper. |
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8. Informal Institutions: Cross-Cultural Difference* Note: schedule change due to Guest Lecturer |
- Being able to classify different cultures according to Hofstede’s dimensions - Understanding the impact of cultural differences on international business - Guest Lecture |
Assess the differences across your selected home and host country |
Coursework
ENGINEERING TRIPOS PART IIB
Module 4E5: International Business
| Coursework | Format |
Due date & marks |
|---|---|---|
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Analysis of Institutional Distance and Recommendation on Internationalization Strategy You will investigate the “institutional distance” between two different countries of your choosing and make an informed recommendation for the internationalization strategy of a fictitious firm. The aim of the assignment is to provide you with the opportunity to directly apply the concepts learned during the course to an empirical setting and encourage you to critically reflect on the different manners in which firms can cross borders. Detailed guidelines are provided below. Learning objective:
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Individual Report Anonymously marked |
DEADLINE: Refer to Moodle HAND-IN LOCATION: Moodle MARKS: [60/60] |
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INDIVIDUAL ASSIGNMENT GUIDELINES
Assignment Description
You will investigate the “institutional distance” between two different countries of your choosing and make an informed recommendation for the internationalisation strategy of a (fictitious) firm of your choosing. The aim of the assignment is to provide you with the opportunity to directly apply the concepts learned during the course to an empirical setting and encourage you to critically reflect on the different manners in which firms can cross borders.
You need to imagine the following situation:
You are responsible for the internationalisation strategy of a firm that operates in {insert sector}. The firm’s headquarters are based in {insert home country} and top management has asked you to assess the possibility of expansion toward {insert host country}. Top management has determined that there are considerable business opportunities in {insert host country}, but has limited local knowledge of this country nor does it have any prior experience with doing business in countries that are similar to this country. As such, top management is uncertain if and how the identified opportunities can be captured. Assess the institutional distance between your home country and the proposed host country and make an informed recommendation regarding the entry strategy your firm should follow. In your assessment, you can assume that there are no resource constraints as top-management has assured you that it has all the resources available to execute any recommendation you make.
Assignment Steps
- Select a sector of interest in which your firm is active;
Think of a sector that you are personally interested in or imagine a firm that you are interested in and use this as inspiration for your scenario. For the purpose of the assignment, it is helpful to work with a stylized or fictional scenario to allow you to focus on the most crucial part of the assignment (the comparative institutional analysis of a chosen home and host country). However, do make sure to develop an idea of what unique capabilities define the firm that would need to be somehow replicated or transferred across borders.
- Select a home country and a host country;
Base the headquarters of your firm in a country of your choosing and select a host country in which it may be interested in operating. Ideally, you should pick at least one country that you are relatively unfamiliar with in order to enhance your learning experience. Setting up a realistic scenario may be helpful, but is not required! As stressed in the scenario above, you can assume that there are considerable business opportunities in the host country you decide to choose. In other words, if you are working with a scenario where the firm is seeking a new market, you do not have to do any market research to justify why you have selected a particular host country.
- Observe institutional distance between home and host country with help of concepts discussed during sessions 3-7;
Before each session from week 3 until week 7 of the course, take some time to explore the institutional differences across the two countries that you have selected based on the concepts discussed in class. At this stage, you do not have to write a report but be prepared to be able to discuss your initial findings in class.
- Select two dimensions of institutional distance that you will focus on in your paper;
After the final session, you should have acquired a good understanding of the institutional differences between your home and host country. At this stage, you should select two dimensions of institutional distance that you deem to be most relevant for your scenario. Ideally, you would want to focus on dimensions for which (a) distance appears to be the greatest and that are (b) most relevant to the unique capabilities of your firm.
- Write an investigative paper in which you analyse the relevant institutional distance between your selected home and host country across the two selected dimensions and make an informed, detailed and realistic recommendation for an entry strategy.
Your paper should make use of course concepts and provide definitions in own words (not quotes) where necessary. Make sure your paper follows the structure outlined below.
Structure of the Paper
The paper should be no more than 3,000 words (excluding references) and has to contain the following parts:
- Title page: Title and Student Number
- Introduction: Very briefly introduce the firm, including the sector in which it is active, its unique capabilities and in which country headquarters are located. Succinctly introduce the internationalisation problem following the scenario you have crafted.
- Theory: Very briefly introduce and define key perspectives (e.g. the institution-based view) or concepts (e.g. various entry strategies) used in the assignment. There is no need to directly reproduce course content and/or tables.
- Method: Briefly describe which dimensions of institutional distance you will focus on and justify your choice. Discuss which sources you will rely on for your assessment.
- Analysis: Report in detail on your analysis of the two dimensions of institutional distance between the home and host country. Make sure to refer to any sources you have used. Where possible, make your analysis specifically relevant to your firm by considering how institutional differences may pose challenges for your firm’s usual mode of operating / its unique capabilities.
- Conclusion and Discussion: Conclude with a detailed recommendation for an entry strategy that your firm should follow when entering the host country in which you make use of the relevant course frameworks on internationalisation strategy. Refer back to your analysis and consider how the firm can practically navigate any challenges in transferring or recreating the necessary capabilities for success in the host country. Discuss any other issues that the firm may need to consider in relation to your recommendation. Discuss any limitations of your analysis and/or make suggestions for further research.
- References: Follow the Harvard system to carefully reference relevant literature and avoid plagiarism. See: https://infolib.blog.jbs.cam.ac.uk/2017/09/28/referencing-advice-all-you....
Assessment Criteria
- Clarity of constructed scenario (5%): Is the firm properly and succinctly introduced? Is the internationalisation problem clearly but succinctly described?
- Coverage of relevant literature (25%): Does the student engage with the literature in a constructive and concise manner? Has the student used additional (academic) sources, other than the ones covered in lectures?
- Critical analysis (25%): Has the student put effort in conducting a comparative institutional analysis? Are the reported observations and implications clear, relevant, and based on coherent argumentation? Is sufficient evidence provided?
- Practical recommendations (25%): Does the report provide a clear and coherent recommendation? Does the report provide detailed considerations for how the recommendation should be implemented in practice? Does the recommendation adequately connect back to the scenario and analysis? Are potential limitations considered?
- Originality (10%): Is the report creative and original? Does the report provide some new angle on the topic?
- Style and structure (10%): Is the paper clearly structured, well written and formatted with care?
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.
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.
P3
Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).
Last modified: 01/02/2026 21:27
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