MSc Cyber Security and Big Data

Institute for Digital Technologies

You will have the opportunity to engage with the very latest Cyber Security and Big Data principles, practices, tools, and techniques through practical application analysing and evaluating problems and responding to challenges in real time.

This programme will provide students with a comprehensive understanding of the challenges in Cyber Security and Big Data faced by industry and society, and will help you develop the necessary skills to address those challenges in the most effective way. This programme will enable you to build knowledge and develop expertise in network security cryptography and big data analytics through action-based learning, analysis and evaluation of application problems to provide you with employment skills essential to the Cyber Security and Big Data industries and related businesses, e-commerce, and governmental organisations.

Programme Aims

a) Provide students with a comprehensive understanding of the challenges in cyber security and big data faced by industry and society, and will help them to develop the necessary skills to address those challenges in the most effective way

b) Utilise both cyber security and big data analytics techniques to analyse and evaluate problems and respond to challenges with practical applications in real time

c) Build students’ knowledge and develop expertise in network security and cryptography, including big data analytics to combat malicious activities and to detect anomalies in the network

d) Provide individuals and teams with employment skills essential to the cyber security and big data industries and related businesses, such as IT, e-commerce, and governmental organisations using action-based learning

Programme Structure

To complete the MSc Cyber Security and Big Data students must complete 8 x 15 credit modules. Students must also choose and complete 4 of the 9 optional modules, 1 of these modules must be completed in Semester 1 and 3 in Semester 2. Students will pick a second subject from the list of nominated second subject modules offered by the other Institutes in the first semester. All students must complete a Dissertation worth 60 credits.

Request a call back

If you would like to speak to the Programme specialist for MSc Cyber Security and Big Data, please complete this form to request a call back. Enquiries relating to an application should be sent to londonadmissions@lboro.ac.uk.

Duration

1 year full-time or up to 4 years part-time

Assessment

Modules are assessed primarily by exams and also include a combination of group exercises, presentations and time-constrained coursework and assignments with varying levels of weighting depending on the nature of each module.

Entry qualifications

Minimum of a lower second class honours degree in electronics, computing, physics, mathematics or a related degree preferably with industrial experience from a UK university, or an equivalent overseas qualification recognised by Loughborough University.

English Language requirements: IELTS 6.5 overall, with a minimum of 6.0 in each subtest (Reading, Listening, Writing and Speaking) or equivalent. See EngLang requirements here.

Career prospects

Graduates from this programme will be in a very strong position to take on digital technology posts in a wide range of sectors, including Internet and cloud based businesses, finance firms, governmental organisations, consultancy companies operating in information, communication and network security, as well as those sectors dealing with massive personal data, such as health and well being, where users' privacy and data security needs safeguarding.

Graduates will also have the opportunity to enhance their knowledge and career prospects further by undertaking an MRes or PhD programme.

Fees and Funding

£10,000 (UK/EU) / £22,650 (International)

Click here to see our available scholarships for 2017 entry.

Compulsory modules

Collaborative Project

Module Description

This module tests your skills in a team environment. With a multi-talented group of students you will work on a brief from a real company looking to solve a real social or business problem for a real client. Student teams will research and build solutions to a business deadline supported by our project tutors, clients and staff. We expect clients to include BT Sport, The London Legacy Development Company and other companies and charities working to respond to the digital age.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Deal with challenges associated with working in interdisciplinary teams

b) Undertake a project development process informed by organisational frameworks

c) Demonstrate interdisciplinary communication skills

d) Apply Design Thinking methods

e) Plan and execute a project plan in collaboration with other team members

f) Identify user needs, collecting and analysing appropriate data, creating conceptual solutions and develop a prototype

Modular Weight

15 credits

Delivery Period

Semester 1

Teaching and Learning

Guided independent study (99 hours)

Supervised time in studio (40 hours)

Lectures (10 hours)

Tutorials (1 hour)

Assessment

Project plan (20%)

Group report (50%)

Project outputs including presentation (30%)

Dissertation

Module Description

The aim of this module is for the student to conduct an individual research project on a core programme related topic which is either an issue of their choice, an exploratory question agreed with an industry/external partner. The project will investigate this research in depth and with rigour. The project should build on methodological skills developed in earlier modules.

Intended Learning Outcomes

The overall goal of the Dissertation module is for the student to display the knowledge and capability required to perform independent work within the context of the programme of study.

Modular Weight

60 Credits

Delivery Period

Semester 1 and 2

Teaching and Learning

Guided independent study (555 hours)

Lectures (25 hours)

Tutorials (20 hours)

Assessment

Dissertation (80%)

Project proposal (20%)

Applied Cryptography

Module Description

This module will cover modern cryptographic algorithms and mechanisms for cyber security with emphasis on the applications and engineering implementations. The first part covers some theoretical foundations of cryptography, cryptographic building blocks as well as the basic, intermediate and advanced protocols.

The second part is about cryptographic techniques including key and its management, algorithm types and modes.

The third part covers cryptographic algorithms which are widely used in the network and security industry, including various ciphers such as block ciphers (DES, AES, RC2, Blowfish, etc.) and stream ciphers (A5, RC4, SEAL, and cascading multiple stream ciphers), one-way hash functions, (MD2, MD5, SHA), public-key algorithms (RSA, ElGamal, Elliptic Curve), digital signature and key exchange algorithms.

The fourth part covers the applications and implementations of selected algorithms and protocols to address security issues in data and security service industry in the real world.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Develop a critical understanding of different cryptographic protocols, techniques, algorithms and implementations that are widely used in protection of confidentiality, integrity, authentication and nonrepudiation, and be able to use their knowledge to address real-world security issues.

b) Understand the fundamentals of security including privacy, integrity, authentication and non-repudiation in internetconnected world

c) Understand the concepts, protocols and algorithms of modern cryptographic mechanisms

d) Understand the implementations and applications of cryptography in cyber security

e) Be able to apply gained knowledge in cryptography in protection of data and user security for real world scenarios

f) Critically analyse detailed cryptographic mechanisms for weakness and potential threats pertaining to big data systems

g) Be able to analyse the cryptographic requirements for real security issues in data systems

h) Apply gained knowledge in cryptographic protocols, algorithms and mechanisms in addressing the security concerns of data systems

i) Demonstrate gained knowledge in cryptography in security applications & APIs

j) Apply their critical analysis and problem solving skills in the industry for tackling problems and providing solutions for both cyber security and big data services

k) Evaluate data security protections with sufficient detail with critical thinking

l) Apply gained knowledge in research, development, implementation and maintenance of advanced cyber security systems

Modular Weight

15 Credits

Delivery Period

Semester 2

Teaching and Learning

Guided independent study (120 hours)

Lectures (26 hours)

Tutorials (4 hours)

Assessment

Final coursework report (30%)

Project presentation (10%)

In-class test (60%)

Principles of Data Science

Module Aims

The aims of this module are to:

  • Introduce students to the concepts of data science and their use in Data Analytics Systems.

  • Enable them to gain theoretical and practical experience in simulating complex data systems involved in a variety of industries including, smart digital systems, Internet of Things, financial industries, and entertainment industries.

Intended Learning Outcomes:

On completion of this module students should be able to:

Knowledge and Understanding

  • Critical awareness of the challenges caused by the proliferation of data generation processes

  • Systematic understanding of the process of extraction of actionable knowledge from data to enable decision making

  • Theoretical background in descriptive and inferential statistics for big data

  • Machine learning algorithms for classification and pattern analysis in large data sets

  • Advanced analytical techniques, such as model building, network graph analysis, outlier detection

  • Methods for maximising predictive performance of algorithms and validation techniques

Modular Weight

15 Credits

Delivery Period

Semester 1

Teaching and Learning

Guided independent study 120 hours Lecture 24 hours Supervised time in studio/workshop 6 hours

Assessment

Project Report (40%)

Presentation (20%)

Final Examination (40%)

Optional modules

Choose four modules only

Media Processing and Coding

Module Description

Students taking this module will gain knowledge in essential topics on: audio and video signal processing, their coding techniques including scalable and multi-view aspects, as well as integration of audio and video applications.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Have gained knowledge in essential topics on: audio and video signal processing, coding techniques including scalable and multi-view aspects, as well as integration of audio and video applications.

b) Understand fundamental theory and practice related to audio capturing, processing, and coding, sound control, noise cancellation

c) Video processing techniques (e.g., object detection, segmentation), fundamentals of video compression and key standards, advanced video representation and rendering techniques, including 3D

d) Analyse digital data and formulate a diagnosis in media processing

e) Comprehend the use of multimedia signals in systems, and effectively apply multimedia signal processing skills for the design of those systems

f) Use coding skills with C++ and Matlab for digital media signals

g) Implement digital filters for audio and video signals

h) Implement multimedia rendering and control systems

i) Use development hardware and software tools for data processing

Modular Weight

15 Credits

Delivery Period

Semester 1

Teaching and Learning

Guided independent study (120 hours)

Lectures (26 hours)

Tutorials (4 hours)

Assessment

Final exam (70%)

Final coursework report (30%)

Internet and Communication Networks

Module Description

This module provides students with an introduction to the Internet and communication networks systems, including computer networks and communications technologies, network architectures, protocol layers, algorithms, and application areas.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Have gained knowledge of communication networks, fixed and mobile communication systems and the Internet, and be able to relate their knowledge to real-world examples

b) Understand key elements and operation of the communication networks, fixed and mobile systems, and the Internet

c) Understand the data rates available on these networks and systems

d) Understand what applications would operate using these data rates with their major limitations of channel characteristics variations

e) Gain experience with system performance analysis, understanding of operational data rates and limitations

f) Critically analyse and reflect on the problems that the current communication networks are facing due to channel variations and relate some possible solutions

g) Obtain communication networks design experience and their practical limitations

h) Synthesise necessary information to evaluate data rates for given services, their channel error performances and the provided Quality of user Experience (QoE)

i) Apply their communication networks knowledge when working in industry

j) Critically evaluate communication networks related problems and deal with their possible solutions

k) Present themselves in the area of research and development in communication networks & the Internet to secure advanced level jobs

Modular Weight

15 Credits

Delivery Period

Semester 1

Teaching and Learning

Guided independent study (120 hours)

Lectures (26 hours)

Tutorials (4 hours)

Assessment

Exam (70%)

Final coursework report (30%)

Internet of Things and Applications

Module Description

This module covers the emerging IoT technologies including concepts, platforms, networked sensors/devices/actuators, applications, as well as their up-to-date examples. Device to device (M2M) connectivity is a key technology also covered.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Demonstrate understanding of the main concepts into the usage scenarios of IoT communication and highly scalable consumption of data from geographically dispersed physical objects and sensors, as well as the processing and delivery of such data to end-users.

b) Understand the interaction and communication between objects and with the environment to support decision making, improve situational awareness, and increase operational efficiency

c) Understand modern applications of smart cities and smart homes

d) Understand the concepts pertaining to the IoT systems

e) Critically analyse and reflect on the limitations and problems faced in those systems and relate some possible solutions

f) Analyse the emerging IoT platforms and devices, and the associated technologies considered in their design

g) Distinguish the requirements pertaining to different contextual information collected and exploited within different IoT scenarios

Modular Weight

15 Credits

Delivery Period

Semester 2

Teaching and Learning

Guided independent study (120 hours)

Lectures (26 hours)

Tutorials (4 hours)

Assessment

Final exam (60%)

Final coursework report (40%)

Introduction to Programming and MatLab

Module Description

This module aims to provide the students with basic concepts and skills of programming in C++ and MatLab for developing digital signal processing applications and simulations.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Demonstrate basic programming skills in C++ and MatLab

b) Demonstrate necessary programming techniques in digital signal processing to develop applications and simulations for media processing

c) Understand cross-platform programming structure and skills in general

d) Understand How to use digital signal processing tools and functions

e) Understand techniques used in developing applications and related numerical simulations

f) Understand the concept of advanced techniques of class, inheritance, templates

g) Identify, utilise and optimise tools, algorithms and functions for simulation of complex digital signal processing applications

h) Implement functions and algorithms in C++ and MatLab

i) Understand the use of advanced techniques of, e.g. class, inheritance, templates and optimisation

j) Gain knowledge of different algorithms, functions and their usage in DSP tool box

Modular Weight

15 Credits

Delivery Period

Semester 2

Teaching and Learning

Guided independent study (120 hours)

Lectures (26 hours)

Tutorials (4 hours)

Assessment

Coursework report (100%)

Media Cloud Applications and Services

Module Description

This module aims to provide the students with an overview of the cloud technology with a special emphasis on media cloud applications, their associated challenges, and their wider use in managing media services, from processing to networking.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Develop an overview of the cloud technology, demonstrate specific knowledge in media cloud applications and the challenges that are associated with making such applications available to the end-users via cloud technology

b) Understand the principles of cloud computing technology, media cloud applications, and the associated challenges

c) Understand media cloud networking and related topics

d) Understand privacy and security issues in media cloud services

e) Understand media cloud case studies and business models

f) Identify the requirements pertaining to the media applications used in cloud services

g) Understand design cloud computing architectures

h) Apply gained academic knowledge and experience in real world scenarios

Delivery Period

Semester 2

Teaching and Learning

Guided independent study (120 hours)

Lectures (26 hours)

Tutorials (4 hours)

Assessment

Final exam (70%)

Final coursework report (30%)

Mobile Broadband and Wireless Networks

Module Description

This module aims to provide the students with the latest mobile broadband and wireless communication technologies, including their network architectures and radio interface protocols, targeting the rapidly evolving mobile broadband communications and providing an exciting education and knowledge in the latest technologies being employed and developed.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Understand essential mobile broadband and wireless networks topics: mobile broadband radio access, wireless propagation models, network architecture, radio interface architecture, Radio Resource Management (RRM) algorithms, scheduling algorithms for multimedia delivery, heterogeneous networks(HetNets), fixed/mobile relays, femto cells, e-MBMS, and wireless video communications techniques

b) Understand 3GPP LTE/LTE-Advanced, propagation models, network architecture, radio interface architecture, Radio Resource Management (RRM) algorithms, scheduling algorithms for multimedia delivery, heterogeneous networks (HetNets), fixed/mobile relays, femto cells, e-MBMS, and wireless video communications techniques

c) Understand mobile broadband network architecture, radio interface protocol stacks, system performance, and data rates

d) Critically analyse and reflect on the associated limitations, the problems of current networks are facing due channel variations and relate some possible solutions

e) Design radio resource management algorithms, media applications delivery techniques over mobile broadband networks

f) Synthesise solutions to the straining of cellular networks as the point-to-point radio link approaches its theoretical limits

g) Apply their communication networks knowledge when working in industry

h) Analyse communication networks related problems and deal with their possible solutions

i) Apply the required knowledge and skills in the latest mobile broadband and wireless networks technologies

j) Present themselves competitively R&D jobs in the telecommunications sector in general, especially in the mobile broadband and wireless communications sector

Modular Weight

15 Credits

Delivery Period

Semester 1

Teaching and Learning

Guided independent study (120 hours)

Lectures (26 hours)

Tutorials (4 hours)

Assessment

Final exam (70%)

Final coursework report (30%)

Network Security

Module Description

This module covers the main concepts and technical details of network security properties, mechanisms, protocols and applications that are widely in use.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Demonstrate knowledge of main concepts related to the network security properties, mechanisms, protocols, and applications that are widely in use in today’s communication systems and networks, and be able to relate their knowledge to network security issues in real-world scenarios

b) Understand the principles of security in computer networks, concepts, models and architectures of available network security mechanisms

c) Understand the security in the Internet and web-based applications

d) Analyse detailed concepts pertaining to the network security architectures and their use

e) Recognise limitations, and design possible solutions for existing problems in web-based applications, common security architectures & APIs

f) Demonstrate gained experience in the Internet security and security concept in web-based applications, common security architectures & APIs

Modular Weight

15 Credits

Delivery Period

Semester 2

Teaching and Learning

Guided independent study (120 hours)

Lectures (26 hours)

Tutorial (4 hours)

Assessment

Final Coursework Report (30%)

Exam (70%)

Digital Forensics

Module Aims:

The aims of this module are to:

  • Develop students’ knowledge and understanding of the methodologies and processes required for the digital investigation involved aftermath of cyber attacks and cybercrimes.

Intended Learning Outcomes:

On completion of this module students should be able to:

Develop a critical understanding of the main concepts related to Forensics Analysis, Electronic Discovery, Crime Reconstruction, and Intrusion Investigation.

Knowledge and Understanding

  • Examine soundness and fundamentals of forensics analysis, scientific methods, data abstraction layers, evidence dynamics, and identity of source

  • Understand the investigative methodologies, applying scientific methods for digital investigation, data gathering and observation, and crime reconstruction

  • Study about digital evidence collection, data processing and electronic discovery

  • Understand the methodologies associated with intrusion investigation, attribute tracking, and IDS alerts

Modular Weight

15 Credits

Delivery Period

Semester 2

Teaching and Learning

Guided independent study 120 hours Lecture 26 hours Tutorial 4 hours

Assessment

Final Coursework Report 40%
Coursework presentation 10% Exam 50%

Advanced Big Data Analytics

Module Aims

The aims of this module are to: - Introduce the concept of Big Data systems and the challenges posed by such systems - Introduce the requirement of advanced analytics, processing techniques and architectural solutions to tackle the problems encountered

Intended Learning Outcomes:

On completion of this module students should be able to:

Knowledge and Understanding

  • Describe the theoretical background of big data, and recognise the need for big data analytics

  • Have a critical awareness of machine learning algorithms for data analytics in big data systems

  • Describe distributed architectures of big data systems including database technologies used in industrial big data systems

  • Understand signal processing techniques for big data systems with advanced matrix manipulation

  • Appreciate various visualisation tools and techniques

Modular Weight

15 Credits

Delivery Period

Semester 2

Teaching and Learning

Guided independent study 120 hours Lecture 24 hours Tutorial 6 hours

Assessment

Coursework 35% Presentation and Q&A 15% Exam 50%

Second subject modules

Choose one module only

Design Thinking

Module Description

This module will enhance students’ ability to use design approaches and tools for identifying and implementing human-centred innovation opportunities. Students are expected to deploy knowledge learned in this module into the parallel Collaborative Project module.

Intended Learning Outcomes

This module will introduce students to a systematic design-based approach aimed at identifying and implementing user-centred innovation opportunities.

Modular Weight

15 Credits

Delivery Period

Semester 1

Teaching and Learning

Guided independent study (108 hours)

Supervised time in studio (30 hours)

Lectures (8 hours)

Tutorials (4 hours)

Assessment

Written report (80%)

Peer feedback (20%)

Principles of Entrepreneurship and Innovation Management

Module Description

The aims of this module are to equip students with an in depth knowledge of the innovation process, its importance to the economy and an understanding of all of the various factors affecting its success including intellectual property, funding and strategy. We will introduce the academic theories of entrepreneurship and analyse the personality traits and behaviours associated with entrepreneurs.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Understand innovation as a process

b) Understand the academic theories of entrepreneurship

c) Understand the factors influencing the success of organisations

d) Relate innovation theory to the performance of organisations

e) Use investigative and research skills

f) Demonstrate effective report writing skills

g) Demonstrate commercial awareness

Modular Weight

15 Credits

Delivery Period

Semester 1

Teaching and Learning

Guided independent study (123 hours)

Lectures (20 hours)

Tutorials (7 hours)

Assessment

Report (100%)

Sport Media and Marketing

Module Description

This module will cover the following topics: Main themes that underpin media and marketing, Evolution of media and marketing in a sport context, Practices and techniques for effective sport media and marketing, Types of media and marketing, Consumer and fan engagement

Intended Learning Outcomes

On completion of this module students should be able to:

a) Assess the major theories, principles, and concepts surrounding sport media and marketing;

b) Apply techniques and practices involved in conceptualising and developing a marketing plan;

c) Gather, analyse, and present sport media and marketing ideas and concepts;

d) Apply sport media and marketing principles that can be utilised in different sport environments;

e) Demonstrate initiative and personal responsibility;

f) Continue to learn independently and to develop professionally.

Modular Weight

15 Credits

Delivery Period

Semester 1

Teaching and Learning

Tutorial (10 hours)

Lecture (20 hours)

Guided independent study (120 hours)

Assessment

Sponsorship Pitch (40%)

Marketing Plan (60%)

The Key Topics in Media and Creative Industries

Module Description

The module will include the following topics: defining media and creative industries; ownership, concentration and control in media and creative industries; innovation and technological change; media and creative markets; business models in media and creative industries; copyright; global media cities; clustering of media and creative industries; media and cultural policy.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Understand how and why the media and creative industries have been defined;

b) Understand the importance of industrial structure in media and creative industries;

c) Understand the implications of innovation and technological change for media and creative industries;

d) Understand changing business models in media and creative industries;

e) Understand the importance of copyright and how this is affected by technological change;

f) Understand why media and creative industries cluster in particular spaces and cities;

g) Understand the globalisation of media and creative industries and understand media and cultural policy;

h) Systematically assess the implicit theoretical assumptions of contrasting perspectives;

i) Communicate effectively in speech and writing, with academic and non-academic audiences;

j) Engage in critical reasoning, debate and argumentation; and assess the empirical validity of competing perspectives;

k) Synthesise different sources of data and identify key arguments and issues at stake in particular fields of practice;

l) Understand the behaviour of firms in media and creative industries;

m) Understand emerging trends in media and creative industries and be able to use critical perspectives to analyse these emerging trends.

Modular Weight

15 Credits

Delivery Period

Semester 1

Teaching and Learning

Tutorial (2 hours)

Supervised time in studio/workshop (10 hours)

Lecture (18 hours)

Guided independent study (120 hours)

Assessment

Essay (100%)

Introduction to Diplomacy

Module Description

This module will include the following topics: The evolution of the International System, The evolution of the study of diplomacy: traditional approaches and debates; critical approaches and new debates, Elements of Diplomacy: practices, procedures and dynamics (including international protocol and etiquette; image projection, reputation management and nation branding), New dynamics and emergent trends in the practice of diplomacy in the face of global change (focusing on the post-Cold War and Post-9/11 era): heteropolarity, advances in science and technology, new forms of conflicts and threats, as well as new forms of interaction and dialogue, Diplomacy as interaction across fields and disciplines: media and diplomacy; digital technologies, statecraft and diplomacy; business/entrepreneurship and diplomacy; management culture/design and diplomacy, Intercultural awareness and dialogue, Normative and ethical dimensions.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Evaluate the historical evolution of the modern international system;

b) Critically evaluate the key concepts and theories of diplomacy;

c) Evaluate the role and behaviours of international organisations and states in the international system;

d) Evaluate the context of the present-day international political and economic relations within which diplomacy takes place;

e) Identify and assess the importance of such dynamics for their respective fields of study;

f) Construct reasoned arguments utilising concepts and approaches to the study of diplomacy;

g) Recognise established and emergent phenomena in the practice of diplomacy within the current global affairs;

h) Creatively and critically evaluate the possibilities of various intersections between diplomatic practice and the objectives and modes of delivery in their respective fields;

i) Gather and organise evidence, data and information from a variety of secondary and primary sources;

j) Develop research and presentation skills;

k) Develop a cross-disciplinary and collaborative research and learning ethos.

Modular Weight

15 Credits

Delivery Period

Semester 1

Teaching and Learning

Lecture (30 hours)

Guided independent study (120 hours)

Assessment

Business Model Development

Module Description

Elements for this business model include: The essentials of business planning, Market analysis and research, Risk analysis, Strategy and positioning finance, marketing, competitor analysis, supply chain analysis, staffing, legal (including IP), governance, value proposition and executive summary.

Intended Learning Outcomes

On completion of this module students should be able to:

a) Critically reflect on and provide well-grounded analysis of the elements of a business model which contribute to business success;

b) Analyze the elements that constitute a business model;

c) Provide critical assessment of a potential product or service;

d) Provide strategic positioning of a novel business idea;

e) Evaluate and critically determine the likely commercial opportunities and risks for the business model in an intended commercial environment;

f) Identify key commercial drivers in different business models;

g) Evaluate business model elements required for financial success given an intended commercial environment;

h) Apply critical analysis to the development of a business plan from a generated idea;

i) Interpret complex commercial environments;

j) Demonstrate effective communication to persuade and influence stakeholders;

k) Evaluate business need for expert intervention;

l) Demonstrate effective report writing skills;

m) Demonstrate good oral communication and presentation skills;

n) Demonstrate a positive attitude towards a commercial opportunity.

Modular Weight

15 Credits

Delivery Period

Semester 1

Teaching and Learning

Practical classes and workshops (3 hours)

Tutorial (9 hours)

Lecture (18 hours)

Guided independent study (120 hours)

Assessment

Coursework (50%)

Presentation (50%)


Share this page: