MSc Machine Learning

The unit encompasses all aspects of a 60 credit project in advanced computer science.  The unit includes a project selection process, delivery of project skills and ethical/professional considerations, supervision of the work of the project and preparation of a report together with assessment of the project outcomes and learning achieved.

Provide the skills to undertake, manage and deliver a technical project of approximately 3 months duration in the broad area of computer science. 

Ensure that an appropriate level of professional competence in the realisation of a research project is demonstrated.

Provides the skills to communicate the outcome of the work, principally in a written report. 

On completion of the course, students will be able to:

1. Be able to plan and execute a 3 months duration project in advanced computer science identifying technical milestones, risks and ethical considerations. 
2. Develop communication skills through a written report and presentation (video demonstration). Understand what constitutes good prose/style for technical writing, correct use of figures and tables, together with proper use and formatting of references. 
3. Be able to undertake an appropriate literature review to identify and select relevant literature, and conduct and present a summary of the literature in a report. 
4. Understand quantitative and qualitative methods for evaluating project outcomes. Know how to represent and critically analyse results. 
5. Develop an awareness of ethical and professional considerations as applied to computer science and specifically to MSc projects. Understand the difference between doing the right thing and doing things right. 

The lectures and study will cover the following topics:

• Project planning / Research methods (3 hours supervised study – 17 hours private study)

Introduction to the project and project planning. Define what constitutes a good plan and the important considerations. Understand how to define technical goals and milestones. Appreciate the importance of monitoring progress and adapting the project objectives as in light of progress made and learning gained including risk and contingency planning.

• Ethics (3 hours supervised study – 17 hours private study)

Students will be introduced to ethical frameworks. These frameworks will be useful in order to judge a number of ethical issues featured in media about AI, autonomous vehicles, software engineering, computer science and social networks. Coursework will involve assessing the ethical issues of a current computer science ethical dilemma using the ethical framework implemented by the School of Computer Science Ethics online tool.

• Professional issues (3 hours supervised study – 17 hours private study)

What should a CS professional know?

Great software failures

How should a professional talk?

Purchasers, users, developers

Right’ Decisions Repertoire

Designing in non-functional requirements

• Research writing (3 hours supervised study – 17 hours private study)

Communicate ideas simply and unambiguously. Getting comments of others on written work. Correctly structuring a report or paper. Use of proper archival references and correct formatting of references. Good use of figures/tables and informative captions. Proper use and formatting of mathematical objects (equations).

• Systematic literature review (3 hours supervised study – 17 hours private study)

Defining research questions

Developing a review protocol

Identifying relevant literature

Selecting studies

Extracting required data

Reporting the review

• Evaluation (& testing) (3 hours supervised study – 17 hours private study)

Methods for empirical evaluation, analysis of evaluation data, testing and profiling.

1) Initial workshop style lecture/activities to understand the basics of project management, ethics and report writing.

2) Individual or small group supervision throughout the project duration

Feedback is provided on both pieces of submitted work which are the assessment for this unit (i) the Project Overview and Plan and (ii) Dissertation. The feedback takes the form of comments provided by the report markers.

Recommended texts:

   Frank Bott, Professional Issues in Information Technology, 2nd edition, BCS, 2014, (ISBN 9781780171807)

   B. Kitchenham et. al. Guidelines for performing systematic literature reviews in software engineering, School of Computer Science and Mathematics, Keele University, 2007.

Supplementary reading:

·Association for Computing Machinery Code of Ethics and Professional Conduct; http://www.acm.org/about/code-of-ethics.

·The Institute of Electrical and Electronics Engineers Code of Ethics; http://www.ieee.org/about/corporate/governance/p7-8.html

   H. Zhang, and M. A. Babar, and P. Tell, Identifying relevant studies in software engineering. Information and Software Technology, 53(6), pp.625-637, 2011.

   Ian F. Alexander, A Taxonomy of Stakeholders: Human Roles in System Development, Issues and Trends in Technology and Human Interaction, Editor(s): Bernd, Carsten, Stahl (De Montfort University, UK) IRM Press. 25-71 pp., 2007

   M. J. Carr, S. L. Konda, Taxonomy-Based Risk Identification, Software 2003

   Michael Cavanagh, Second Order Project Management, Routledge, 2012 (ISBN 9781409410942)