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Online Postgraduate Certificate in Strategic Technology Innovation

Structure

The online Postgraduate Certificate in Strategic Technology Innovation programme consists of four modules. The first module takes ten weeks to complete and the subsequent modules take eight weeks to complete.

Modules

  1. Managing the Technology Enterprise
  2. Strategic Technology Management
  3. Technology Innovation and Change Management

Objective

To lay the foundation for successful study, and introduce strategic considerations of the role of IT within an organisation. As a student, you will have the opportunity to gain skills to lead IT more effectively and also to investigate the various functions of an IT organisation and the best ways to perform these functions.

Description

This module is designed to introduce students to the online learning environment and a wide range of strategic considerations associated with software acquisition and deployment, and the management of information systems projects. The module considers the role of software within organisations from the human, social, knowledge and business perspectives. In the context of software acquisition, the module examines a range of processes from off-the-shelf acquisition to bespoke software development including various software lifecycles. Once acquired, software needs to be maintained and evolved, and so the module also examines theories and methods for achieving this.

Curriculum

  • Participating in the global classroom, navigating the classroom, understanding module requirements
  • Evaluating the work of others, academic integrity and Harvard Referencing
  • The value of IT
  • IT strategy implementation: the technology road map and tactical planning
  • IT governance: budgeting and IT portfolio management
  • Acquiring software: outsourcing, vendor and contract management
  • Operations and IT capabilities
  • The role of IT with respect to compliance, privacy and legal considerations
  • Managing and developing IT capabilities, managing risk and change
  • IT innovation and emerging technologies

Duration:

10 weeks

Objective:

To provide comprehensive understanding of the techniques and challenges of technology innovation and change management – including the management of organisational resources and environments outside of the IT domain. As a student, you will have the opportunity to gain the knowledge and skills to assess and implement change in a controlled manner that aligns with organisational needs and objectives.

Description:

This module will provide students with a comprehensive understanding of how technology becomes an enabler for business and how IT strategies support organisational goals to help to create a sustained competitive advantage in business. More specifically, the module will provide students with the ability to critically evaluate IT strategies and to understand how to deploy such strategies in the context of systems and/or business applications within the IT industry.

Curriculum

  • Critical introduction and overview of major IT issues that need to be considered to support organisational goals
  • The role of IT in organisations and the role of the Chief Information Officer (CIO) and IT managers in the context of IT strategies in organisations, IT maturity models used to assess or benchmark an organisation’s IT capability so as to improve the IT services that businesses provide
  • IT alignment models used to understand the level of integration across business strategy, IT strategy, business infrastructure and IT infrastructure
  • IT governance, defining and implementing an infrastructure strategy that will support enterprise goals
  • Strategy mapping, using IT planning models to link corporate objectives with the IT strategies required to realise these objectives
  • Using IT to support business, the strategic use of IT resources
  • Measuring the value of the connection between IT and business, and the performance of the efforts that deliver this value

Duration:

8 weeks

Objective

To build a detailed and practical foundation relating to the techniques and challenges of technology innovation and change management. As a student, you will have the opportunity to gain the knowledge and skills for the management of resources, the use of new IT innovations and how to implement change in a controlled manner to meet organisational needs and objectives.

Description

This module will provide students with a comprehensive understanding of change models and the impact of change through technology innovation, adoption and implementation. Students will have the opportunity to gain advanced knowledge and skills to manage the design and use of technology to promote growth, innovation and change within organisations. The module will also provide students with a comprehensive understanding of how innovation can act as a change enabler and the importance of building readiness for change within organisations.

Curriculum

  • Critical introduction to innovation and diffusion: theories and concepts, strategic adoption of Information Systems and Technology
  • Knowledge management and technology innovation
  • Change management models and frameworks for Information Technology
  • Leading IT innovation and change: understanding the internal and external environments of organisations and their impact on IT innovation and change
  • Innovating with social media
  • Innovating with big data and cloud computing
  • Managing IT change in global organisations within the context of complex political and structural environments
  • Using IT standards and governance to impact the innovation and change process

Duration:

8 weeks

Elective Modules

  1. Applied Cryptography
  2. Big Data
  3. Cloud Computing
  4. Cyber Crime Prevention and Protection
  5. Cyber Forensics
  6. Data Mining
  7. Data Visualisation and Warehousing
  8. Predictive Analytics for Decision Making
  9. Professional Issues in Computing
  10. Security Engineering and Compliance
  11. Security Risk Management

Objective

To provide insights into cryptographic algorithms and protocols, including a detailed understanding of symmetric key encryption algorithms, hash function algorithms, public key cryptography algorithms and key agreement protocols. You will have the opportunity gain an in-depth understanding of attacks, vulnerabilities and of quantum computing techniques, as well as experience to apply cryptographic algorithms and protocols to solve security issues.

Description

This module provides students with a critical understanding of how to use cryptographic algorithms and protocols to solve practical security problems (such as confidentiality, integrity and authenticity). As a student, the module also allows you to acquire a systematic understanding of open-source tools to build secure applications, and to learn how best to apply such tools.

Curriculum

  • Introduction to classical cryptography
  • Block ciphers, symmetric key encryption and secure hash functions
  • Public key cryptographic encryption and signature schemes
  • PKCS: Public Key Cryptography Standards
  • Elliptic Curve cryptography
  • Quantum computing and quantum cryptography
  • Key agreement, identification, and zero knowledge
  • Password authentication, identity based cryptography, and other advanced topics.

Duration:

8 weeks

Objective

To provide a comprehensive understanding of big data tools and techniques as well as a critical understanding of an open source software framework for distributed data storage and processing. You will have the opportunity to gain a practical understanding of the issues related to the integration and deployment of big data management systems in the context of enterprise deployment.

Description

This module provides students with detailed knowledge of big data tools and techniques, and big data management frameworks that can be used to support advanced analytics. This module will consider big data management frameworks in general, but with a focus on the Hadoop open-source data storage and processing platform and its underpinning sub-systems. It also provides detailed awareness of how big data systems support data-driven decision making.

Curriculum

  • Introduction to big data and Apache Hadoop, terminology and basic concepts
  • Big data ecosystems and the big data landscape, the six Vs of big data
  • Components of the Hadoop stack, attributes and uses of MapReduce, the Hadoop Distributed File System (HDFS) and Yarn, installing Hadoop and running ‘large dataset programs’ with Hadoop
  • Modelling and managing big data, Big Data Management Systems (BDMS) and practical work with Cloudera Data Management Virtual Machine
  • Big data integration and processing; configuring and working with BDMS schemes, including further work with the Cloudera Virtual Machine
  • Data frames and document oriented big data systems, predictive analytics with Pandas Dataframes, MongoDB, Splunk and Datameer
  • Big data processing pipelines and graph analytics, distributed processing with Apache Spark components (Spark core, pipelines, transformation engines, SparkSQL and Spark GraphX)
  • Big data enterprise deployment, integration and security issues

Duration:

8 weeks

Objective

To provide a comprehensive overview of cloud architecture models and guidance for building cloud-based services and applications. You will be introduced to cloud industry standardisation, middleware platforms and cloud provider platforms, as well as to all the possibilities that cloud computing has unleashed.

Description

Cloud computing is an important new paradigm in information technology that provides a basis for a new wave of technology developments. Cloud computing embodies advances in computing, networking, and storage technologies which individually and collectively include major hardware and software breakthroughs. These include computer virtualisation, distributed and replicated storage, and software-based networking. Cloud computing motivates further technology advancement and changes how modern IT infrastructures are built and evolved. There is a growing demand for specialists with strong technical background and deep knowledge of cloud computing technologies.

Curriculum

  • Cloud computing foundation
  • Cloud architectures and cloud platforms
  • Cloud Infrastructure as a Service (IaaS)
  • Cloud Platform as a Service (PaaS)
  • Cloud Software as a Service (SaaS) and application clouds
  • Cloud security, data protection and privacy, access control and identity management
  • Cloud construction, cloud interoperability, migration enterprise infrastructure to clouds
  • Cloud infrastructure management, system/service compliance and assurance

Duration:

8 weeks

Objective

To provide a systematic understanding of the tools and techniques that can be deployed for cybercrime prevention by developing a broad understanding of the information security management landscape. You have the opportunity to develop practical skills to deploy the tools and techniques of cybercrime prevention, in both commercial and non-commercial settings, through the use of ‘ethical hacking’.

Description

This module provides students with a comprehensive understanding of the tools that can be used to prevent and mitigate against cybercrime – including the deployment of cybercrime prevention strategies for application in the workplace by considering the motivations behind cybercrime. Students have the opportunity to build an ‘ethical hacking’ environment with which to experiment and test their skills.

Curriculum

  • Critical overview of cybercrime prevention terminology and the legal aspects involved
  • Information Security Management, Security Auditing, Monitoring, Ethical hacking and Penetration Testing
  • Building of an ethical hacking environment (laboratory) to allow experimentation with hacking techniques and comprehensive understanding of these techniques can be gained
  • Ethical hacking in a number of contexts such as: wireless communication: WiFi, Protocol access, Operating Systems, the ’Secure Sockets Layer‘ access point cloning, router attacks, SQL injection and the building of key loggers
  • Techniques, tools and processes for cybercrime prevention in a variety of domains such as: desktop applications, wireless access points smartphones and Bluetooth connections
  • Comprehensive understanding of the security challenges of emerging computing environments.

Duration:

8 weeks

Objective

To provide detailed knowledge in the practice of extracting evidence from computers and digital storage media.

Description

This modules provides students with the knowledge to identify, extract, document, interpret and preserve computer media as digital evidence, as well understanding of how to analyse the root cause of security breaches. The module covers issues such as crypto-literacy, data hiding and hostile code.

Curriculum

  • Digital evidence, computer crime, technology and law
  • The investigative process, reconstruction and modus operandi
  • Applying forensic science to computers
  • Investigating windows computers and network forensics
  • Investigating Unix systems, Macintosh systems and handheld devices
  • Network Forensics I
  • Network Forensics II
  • Computer crime investigation and career development

Duration:

8 weeks

Objective

To provide a detailed, critical understanding of the concepts of data mining, the end-to end data mining process and the ability to deploy appropriate tools and techniques in line with organisational and business requirements. As a student, you will have the opportunity to gain experience in implementing data mining algorithms and evaluating their performance.

Description

This module provides students with an in-depth understanding of the concepts of data mining, including the end-to-end process and major data mining tools and techniques in common use. As a student, you will have the opportunity to apply such tools and techniques to a variety of example data sets so as to gain vital insights into their operation, and when and where these tools can best be applied. You will also have the opportunity, using the 'R' programming language, to implement several different kinds of data mining algorithms to gain a comprehensive understanding of their operation.

Curriculum

  • Data Mining concepts, including: the end-to-end Data Mining process, different types of data that can be used in this process, problems that may be encountered and methods for dealing with these problems
  • Decision Tree extraction algorithms and their implementations, coupled with a critical analysis of the advantages and disadvantages of a range of Decision Tree induction techniques
  • Association Pattern mining algorithms and their implementations together with a critical comparison of Association Rules and those extracted by Decision Tree induction algorithms
  • Cluster analysis algorithms, including the use of Self Organising Maps and the use of Neural Networks for mining data clusters
  • Mining Data Streams, including: the detection of Concept drift and how best to deal with Volume, Velocity and Veracity (VVV) problems associated with Data Streams
  • Mining text data, including a critical comparison of different Document Similarity detection techniques
  • A critical comparison of web mining techniques, including Crawlers
  • A comprehensive analysis of social network mining techniques for extracting useful knowledge from social networks, and for visualising the relationships in social networks; concluding with material on how to match Data Mining algorithms with problems.

Duration:

8 weeks

Objective

To provide a detailed understanding of the concepts and challenges of creating data warehouses. You will have an opportunity to create a data warehouse using open source technologies and free public data sets. You will also be introduced to why data visualisation is important and how to communicate these insights to tell a ‘data story’.

Description

This module introduces students to the concept and challenges of creating data warehouses and how data visualisation tools can be used to ‘tell a story’. As a student, you will have the opportunity to gain practical experience of how to create data warehouses using data from multiple sources. The module will also introduce best practices in data visualisation and data storytelling, using state-of-the-art data visualisation technology.

The module is intended to help you understand the approaches and benefits of data warehousing, and show you how to quickly gain and communicate insights into the data stored in data warehouses using data visualisation techniques.

Curriculum

  • Review of the rational for, and benefits of, data warehousing, common challenges (integration, data cleansing) and different architectures (transactional, dimensional), the business case for data warehousing
  • Design of relational databases (normalising vs. de-normalising, defining dimensions and facts) using public data sources and an open source database platform
  • Data accuracy and data cleansing, defining rules for data warehousing
  • Loading data into a data warehouse and ensuring that relevant business case objectives are met
  • Benefits of visualisation and data storytelling, best practice for visualisation, how to avoid common mistakes and exploration of a selected data visualisation system
  • The process of building visualisations to answer common business questions illustrated using the visualisation system introduced in earlier in the module
  • Combining visualisations into a single dashboard to "tell a story" and provide insights, concerning data stored in a data warehouse and appropriate conclusions drawn
  • Expanding and building on existing insights by adding trends and forecasts; comparison with other types of data analysis, such as predictive and prescriptive data analytics.

Duration

8 weeks

Objective:

To provide a systematic understanding of key predictive analytics techniques and an understanding of the types of business problems predictive analytics can solve. You are provided with an opportunity to apply the tools and techniques learned throughout the module to typical business problems.

Description:

This module provides students with insight into how predictive analytics can be used to help organisations and their customers make better decisions. As a student, you will have the opportunity to gain a comprehensive understanding of how results from predictive analytics can be used by organisations to grow their customer base and run operations more efficiently. This module is oriented towards practical applications of predictive analytics.

Curriculum

  • Common predictive analytics techniques (e.g. logistic regression, classification trees, collaborative filtering) and model development best practices
  • The end-to-end process of predictive analytics in the context of commercial environments: (i) problem identification, (ii) data assessment, (iii) data preparation, (iv) model development, (v) model deployment and (vi) making insights available to decision makers
  • Application of predictive analytics scoring models I: customer acquisition. Use case on optimising direct marketing campaigns utilising lists of score prospects
  • Application of predictive analytics scoring models II: customer retention. Use case on decreasing customer churn
  • Application of predictive analytics scoring models III: operational efficiency. Use case of optimising collection agent’s time by prioritising outreach to ‘high risk customers’
  • Application of predictive analytics scoring models IV: recommended systems. Use case on product recommendations in an online store
  • End-to-end application of predictive analytics techniques in business environments

Duration:

8 weeks

Objective

To provide an opportunity to understand and evaluate the professional and ethical issues arising in the use, implementation, operation and monitoring of IT systems. You will also explore the legal and social issues that computing professionals may encounter and develop key management skills required for the effective utilisation and operation of IT.

Description

To function effectively, professional IT practitioners need not only the appropriate technical knowledge, skills and experience, but also a broad understanding of the context in which they operate. IT professionals must understand the relationship between technological change, society and the law, and the powerful role that computers and computer professionals play in a technological society. This module is designed to help you operate effectively in work and community situations, and to be aware of your environment.

Curriculum

  • Introduction to professional issues in computing
  • Professionalism in IT
  • Legal perspectives, privacy and data protection
  • Censorship and intellectual property in the context of IT
  • Security and cybercrime
  • IT investments, contracts and outsourcing
  • Elements of risk management
  • Social aspects of technology, emergence and convergence of technologies

Duration:

8 weeks

Objective

To provide in-depth understanding of information security concepts and models. You will have an opportunity to develop the skills to carry out security and risk assessments, to design and deploy security infrastructures, to write security/incident response polices and to conduct penetration testing.

Description

This module provides an insight into information security principles, security policy models/protocols, industry standards for security compliance and risk assessment. As a student, you will develop a critical understanding of how to use information security techniques to solve practical security problems. You will also have the opportunity to gain skills for designing/implementing security infrastructure and writing security/incident response polices. Through practical and hands-on project work, this module is designed to ensure you are ready to apply the knowledge gained in this module in your workplace.

Curriculum

  • Information security concepts such as confidentiality, integrity, authenticity and availability
  • Security models (such as privacy models and integrity models) and security policies in the context of cyber security
  • Network security, wireless security, mobile security, Internet of Things security and infrastructure security
  • Security compliance, industry standards and industry recognition
  • Risk analysis and risk assessment
  • Firewalls and intrusion detention systems
  • Software testing, security penetration testing, and quality assurance
  • Digital content protection in the context of cyber security compliance

Duration:

8 weeks

Objective

To provide theoretical and practical knowledge of, and insight into the formal, systemic approaches of Cyber Security Risk Management (CSRM). You will have the opportunity to gain practical skills in the application of the concepts, techniques and approaches of Security Risk Management in enterprises of all kinds.

Description

Threats to information security are becoming more sophisticated. Laws and regulations impose strict CSRM requirements on all enterprises to prevent, or at least limit, the potential of cyber-attacks. This module aims to provide the theoretical and practical knowledge to deliver a formal, systematic and in-depth approach to the application of the concepts, techniques, methods, approaches and processes of CSRM in a pragmatic manner and in the context of enterprises of all kinds.

Curriculum

  • The principles of security risk management
  • Security risk management models, roles and functions.
  • Strategic management planning and strategies, and the security management life cycle
  • Laws and regulatory requirements concerning cyber security, and security standards and controls
  • Security metrics and Key Performance Indicators (KPIs)
  • Physical security and environmental threats and contingency planning
  • Security training and awareness and the creation of a security staff training plan
  • The future of (cyber) security risk
  • Management, the potential impacts of evolving technologies

Duration:

8 weeks

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