msc in advanced computer science and it management 2015/16 · school of computer science msc in...

School of Computer Science

MSc in Advanced Computer Science and IT Management

2015/16

WELCOME TO YOUR MSc PROGRAMME I am delighted to welcome you to the School and your MSc programme. As you are aware, this MSc programme is taught in collaboration between the School of Computer Science and the Manchester Business School (MBS). As such, the programme benefits from the offerings and expertise of both schools. MBS is the largest campus-based business and management school in the UK offering world-leading business education informed by leading edge theory and practice. Similarly, the School of Computer Science is renowned as a world-class centre of excellence in computing teaching and research. Your programme will have both modules from Computer Science and MBS. We offer several options for computing modules: - Data on the Web theme

- Data Engineering and IT Governance theme

- Learning from Data

- Security theme

- Software Engineering theme

- Parallel Computing in the Multi-core Era theme

We also offer business choices in the areas of - Project Management

- Strategy and Decision Making

- Commercialisation

- Business Analytics

Finally, we also offer the Information management pathway, which is focused on managing big data.

This document aims to help you choose an option that meets your hopes and expectations. Detailed syllabi for each of the modules offered along with time-tables are available at

http://studentnet.cs.manchester.ac.uk/pgt/syllabus.php This year there will be lots of opportunities here for you, not only in the formal modules offered for your studies, but in research and popular seminars, job fairs, employability training and other extra-curricular activities (students groups, etc.). Make sure that you make the most of them as you lay the foundations of your future career.

Dr Goran Nenadic Programme Director e-mail: [email protected]

http://studentnet.cs.manchester.ac.uk/pgt/syllabus.php

Summary of the taught part programme

Semester 1:

Choose one of the following CS themes

Choose two business modules

- Data Engineering and System Governance

- Data Engineering - IT governance

- Data on the Web

- Modelling Data on the Web - Querying Data on the Web

- Learning from Data

- Foundations of Machine Learning - Modelling & Visualisation of High-

Dimensional Data

- Security

- Cryptography - Computer and Network Security

- Software Engineering

- Software Engineering Concepts in Practice

- Agile and Test-driven Software Development

- Parallel Computing in the Multi-Core Era

- Parallel Programs and their Performance

- Designing for Parallelism and Future Multi-core Computing

- IS Strategy and Enterprise Systems

- Managing projects

- Social Media and Web Analytics - Mathematical Programming and

Optimisation

- Entrepreneurial Commercialisation of Knowledge

- Games Businesses Play

Semester 2:

Chose one Advanced CS module

(please note the pre-requisites from Semester 1)

Choose one business module

(please note the pre-requisites from Semester 1)

- Pattern-based Software Development

- Component-based Software Development

- Text Mining

- Computer Vision

- Mobile Communications

- Mobile Systems

- Introduction to Health Informatics

- Principles of Digital Biology

- Automated Reasoning and Verification

- Ontology Engineering for the Semantic Web

- Data Analytics for Business Decision Making

- Information and Knowledge Management

- Risk, Performance and Decision Analysis

- Simulation and Risk Analysis

- Business Feasibility Study

.

Information Management pathway

"Cutting-edge computing for big data science and analytics” This pathway was introduced in 2012/13 to address the continuing development and growing significance of the field of information management and big data. It has been developed with input from industry – both information and data management companies and their clients, and is focused on the significance of information capture and usage from “big data”, and the need for its effective and efficient management and analysis within business, scientific, educational, entertainment and organisational contexts. The Information management pathway addresses both the technical challenges of information capture and usage from big data, and the need for its effective and efficient management and analysis within business, scientific, educational, entertainment and organisational contexts. Big data constitutes large quantities of raw information generated by changing technologies and corresponding changing organisational practice, and impacts both analytic techniques and organisational context to utilise the analysis results. These impacts have led to the recent emergence of “Data Scientists” and "Chief Information (or Data) officers" in several organisations, highlighting them as careers of future. This MSc pathway focuses on data science and will examine the entire information management life cycle, including data strategy, management, design and warehousing, data analytics and information governance. In addition to the need to work with huge volumes of data, the pathway will also address multi-modality, including un- and semi-structured data, image and video data, spatial and temporal data, etc. In recognition and support of its efforts to develop postgraduate training, the School was awarded the 2013 IBM Faculty Award in Big Data Analytics (to Professor John Keane and Dr Goran Nenadic). Dr Martyn Spink from IBM UK Limited says: "IBM is supportive of the Information Management pathway. The programme fits with some of IBM's core business objectives and also that of some of our clients." The curriculum for this pathway contains 5 core course units from two themes:

- Data Engineering and system governance theme o Data Engineering (COMP60711) o IT Governance (COMP60721)

- Information Management 1 theme o Foundations of Machine Learning (COMP61011) o IS Strategy and Enterprise Systems (BMAN60111) o Information and Knowledge Management (BMAN71652)

and one unit from the following list (Information Management 2 theme):

o Data Analytics for Business Decision Making (BMAN60422) o Text Mining (COMP61332) o Risk, Performance and Decision Analysis (BMAN60092) o Simulation and Risk Analysis (BMAN70142)

Please note: BMAN60092 requires a pre-requisite that needs to be discussed with the course unit leader in advance.

Information Management pathway

Semester 1

Day 09:00

– 10:00

10:00 –

11:00

11:00 –

12:00

12:00 –

13:00

13:00 –

14:00

14:00 –

15:00

15:00 –

16:00

16:00 –

17:00

Mon

CORE: COMP60721 (Period 2 only)

IT Governance

Tues


Data Engineering

Wed

CORE: COMP61011 (Period 1 only) Foundations of Machine Learning

Thurs

Fri

CORE: BMAN60111

IS Strategy and Enterprise Systems

Semester 2

CORE UNIT:

BMAN71652 Information and Knowledge Management OPTIONAL UNIT:

One course unit is selected from these

- Data Analytics for Business Decision Making (BMAN60422)

- Text Mining (COMP61332)

- Risk, Performance and Decision Analysis (BMAN60092)

- Simulation and Risk Analysis (BMAN70142) [Please note that BMAN60092 requires a specific pre-requisite]

Data on the Web Theme As the World Wide Web evolves from a web of documents to a web of documents, data and applications, standards, techniques and practices have evolved for modelling, managing and querying web data at scale. This theme explores a range of topics that have emerged from web data standards and practices, including semi-structured data management, linked open data and big data querying. This is not a theme aimed at those who wish to build web sites, but is for those students who are seeking a deeper understanding of the technologies that are being used to support the continuing evolution of the Web.

Course units in Semester 1: two CORE units (one in Period 1, one in Period 2) and two units from MBS options (whole semester, except MCEL40021).

Day 09:00

– 10:00

10:00 –

11:00

11:00 –

12:00

12:00 –

13:00

13:00 –

14:00

14:00 –

15:00

15:00 –

16:00

16:00 –

17:00

Mon

OPTION: BMAN60101

Mathematical Programming and Optimisation

OPTION: BMAN71641 Social Media and Web

Analytics

(cohort 1)

OPTION: MCEL40021 (Period 1 only)

Entrepreneurial Commercialisation of Knowledge

Tues


Analytics (cohort 2)

OPTION: BMAN73291

Games Businesses Play

Wed

Thurs

OPTION: BMAN73291


Fri

CORE: COMP60411 (Period 1 only) Modelling data on the web


Querying Data on the Web

In Semester 2, the students choose one module from the ACS options (Semester 2) and one from the IT Management options (Semester 2, MBS units) – see the end of the document for the list.

Data Engineering and System Governance theme This theme aims to provide students with an overview and understanding of the entire data life cycle, including data creation, modelling, acquisition, representation, use, maintenance, preservation and disposal, as well as the general use of IT to secure data and information. It discusses database design, data warehousing, maintenance and analytics, data standards and data quality, as well as managing the human behaviour affecting the security of data and information systems. Course units in Semester 1: two CORE units (one in Period 1, one in Period 2) and two units from three MBS options (whole semester, except MCEL40021).

Day 09:00

– 10:00

10:00 –

11:00

11:00 –

12:00

12:00 –

13:00

13:00 –

14:00

14:00 –

15:00

15:00 –

16:00

16:00 –

17:00

Mon




IT Governance

Tues

CORE: COMP60711 (Period 1 only) Data Engineering

Wed

Thurs

Fri

OPTION: BMAN60111 IS Strategy and

Enterprise Systems

OPTION: BMAN70391 Managing projects


Learning from Data theme The amount and complexity of data being produced and processed by modern technologies is growing rapidly. Computer applications are increasingly required to adapt and learn from these vast data resources. Manchester researchers are mining huge document collections, adaptively optimizing multi-core processors and understanding the complexity of the genome. Although these seem like very different applications, it turns out that they can all be tackled with a core set of common algorithms, drawn from the field of machine learning. This theme will give you the chance to learn the core set of skills in this field, first studying the basics of machine learning, and quickly accelerating to the more advanced state of the art methods in high dimensional data analysis. Course units in Semester 1: two CORE units (one in Period 1, one in Period 2) and two units from MBS options (whole semester, except MCEL40021).

Day 09:00

– 10:00

10:00 –

11:00

11:00 –

12:00

12:00 –

13:00

13:00 –

14:00

14:00 –

15:00

15:00 –

16:00

16:00 –

17:00

Mon

OPTION: BMAN60101



Analytics

(cohort 1)



Tues


Analytics (cohort 2)

OPTION: BMAN73291


Wed

CORE: COMP61011 (Period 1 only) Foundations of Machine Learning


Modelling and visualization of high-dimensional data

Thurs

OPTION: BMAN73291


Fri

OPTION: BMAN60111


OPTION: BMAN70391

Managing projects


Security theme The large-scale application of the Internet and telecommunication technologies routinely generates enormous amount of information that is transmitted, processed, stored and managed on networked systems on a global scale. Information recorded electronically on a networked system is particularly vulnerable to security threats, such as: theft, manipulation or misuse of valuable or confidential information; deliberate damage to systems and services; and fraud and forgeries in e-business dealings. These threats could endanger national security, national critical infrastructure, business interests and personal privacy. The field of Security, namely the study of countermeasures to address these serious threats, is therefore of paramount importance to our quality of life. This Security theme is aimed at introducing the technologies, standards, policies, procedures and practices that can be used to secure information and distributed systems. It embraces a range of technologies such as cryptography, and computer, network and distributed system security, and also includes risk assessment procedures and the study of how security can best be managed. Course units in Semester 1: two CORE Computer Science units (one in Period 1, one in Period 2) and option of two MBS units (whole semester). If you are interested in COMP60721 (IT governance), please talk to Programme Director.

Day

09:00 –

10:00

10:00 –

11:00

11:00 –

12:00

12:00 –

13:00

13:00 –

14:00

14:00 –

15:00

15:00 –

16:00

16:00 –

17:00

Mon

CORE: COMP61411 (Period 1 only) Cryptography

OPTION: COMP60721 (Period 2 only)

IT Governance

Tues

CORE: COMP61421(Period 2 only) Cyber Security

Wed

Thurs

Fri

OPTION: BMAN60111


OPTION: BMAN70391

Managing projects


Software engineering theme Software Engineering tools and techniques are central to computer science, underpinning systematic development and evolution of software systems. This theme provides experience of modern approaches to software engineering, with a view to enabling students to deploy agile software development practices, and to work effectively with large software systems. Course units in Semester 1: two CORE units (one in Period 1, one in Period 2) and two units from MBS options (whole semester, except MCEL40021).

Day 09:00

– 10:00

10:00 –

11:00

11:00 –

12:00

12:00 –

13:00

13:00 –

14:00

14:00 –

15:00

15:00 –

16:00

16:00 –

17:00

Mon

OPTION: BMAN60101


OPTION: BMAN71641

Social Media and Web Analytics

(cohort 1)



Tues

OPTION: BMAN71641


(cohort 2)

Wed

Thurs

CORE: COMP61511 (Period 1 only) Software Engineering Concepts in Practice


Agile and Test-Driven Software Development

Fri

OPTION: BMAN60111


OPTION: BMAN70391

Managing projects

In Semester 2, the students choose one module from the ACS options (Semester 2) and one from the IT Management options (Semester 2, MBS units) – see the end of the document for the list. Please also note that there are two software engineering modules in Semester 2 that might be useful for consideration (please contact Programme Director if you consider taking both):

- Component-based Software Development (COMP62352)

- Pattern-based Software Development (COMP62542)

Parallel Computing in the Multi-core Era theme In the universal move to multi-core processors, microprocessor manufacturers have presented the software industry with its most serious challenge ever. Essentially all CPUs are now multi-core, and the number of cores in the CPU is increasing inexorably. The consequences of this multi-core revolution are profound because parallel computing now needs to be handled as the norm, rather than the exception; today's programmers need parallel programming skills that are currently possessed by very few. This theme introduces students to the complexities of parallel computing by reviewing hardware developments and by providing programming techniques and tools that can alleviate the ensuing problems of correctness, reliability and performance of modern parallel systems. Course units in Semester 1: two CORE units (one in Period 1, one in Period 2) and two units from MBS options (whole semester, except MCEL40021).

Day 09:00

– 10:00

10:00 –

11:00

11:00 –

12:00

12:00 –

13:00

13:00 –

14:00

14:00 –

15:00

15:00 –

16:00

16:00 –

17:00

Mon

OPTION: BMAN60101


OPTION: BMAN71641


(cohort 1)



Tues

OPTION: BMAN71641


(cohort 2)

Wed

Thurs

CORE: COMP60611 (Period 1 only) Parallel Programs and their Performance


Designing for Parallelism and Future Multi-core Computing

Fri

OPTION: BMAN60111


OPTION: BMAN70391

Managing projects


MSc ACS&ITM: Semester 2 choices

In the second semester, the students choose one module from the Advanced Computer Science course units and one from the MBS offering: Advanced Computer Science course unit options Period 3 Pattern-based Software Development (COMP61542) Component-based Software Development (COMP62352)

Principles of Digital Biology (COMP60532) Text Mining (COMP61332) [please note a pre-requisite] Mobile Systems (COMP61232)

Automated Reasoning and Verification (COMP60332) Period 4 Computer Vision (COMP61342) [please note a pre-requisite] Introduction to Health Informatics (COMP60542) Mobile Communications (COMP61242) Ontology Engineering for the Semantic Web (COMP62342) Manchester Business School course units Business Feasibility Study (MCEL40042) Information and Knowledge Management (BMAN71652)

Risk, Performance and Decision Analysis (BMAN60092) [please note a pre-requisite] Simulation and Risk Analysis (BMAN70142) Data Analytics for Business Decision Making (BMAN60422)

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