The content of this Pathway has been agreed by ODAG Consultants Ltd. This is the only Digital Degree Apprenticeship Pathway for the Digital Technology sector approved for use in Wales that is eligible for Medr funding
Learning Programme Content
The Learning Programme provision shall comprise of three mandatory elements:
- Qualifications,
- Essential Skills
- On/off the job training
The total minimum credit value required for the:
Level 6: Applied Software Engineering Apprenticeship is 360 credits.
Level 6: Applied Data Science Apprenticeship is 360 credits.
Level 6: Applied Cyber Security Management Apprenticeship is 360 credits.
Entry requirements
General Entry Requirements for - Level 6 Degree – Applied Software Engineering/Applied Data Science/Applied Cyber Security Management
The Digital Degree Apprenticeship pathway at Level 6 is primarily suitable for applicants who have either completed “A” levels appropriate for university entrance, or who may have already completed a related apprenticeship at Levels 3, 4 or 5.
Please note: Applicants for this apprenticeship pathway are likely to be 19+ years.
Processes exist to make sure that applicants with relevant prior knowledge, qualifications and/or experience are not disadvantaged by having to repeat learning. Colleges and universities will be able to advise on the current rules for accrediting prior learning and recognising prior experience.
Apprenticeship pathway learning programme(s)
Level 6: Applied Software Engineering Degree Apprenticeship
Level 6: Applied Software Engineering Degree Apprenticeship Qualifications
Participants must achieve one of the following combined qualifications below.
| BSc (Hons) Computing (Software Engineering) | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| University of Wales Trinity Saint David | n/a | 360 | 3600 | Combined | English Only |
| BSc (Hons) in Applied Software Engineering | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| Swansea University | n/a | 360 | 3600 | Combined | English Only |
| The Open University | n/a | 360 | 3600 | Combined | English Only |
| Cardiff Metropolitan University | n/a | 360 | 3600 | Combined | English Only |
| Cardiff University | n/a | 360 | 3600 | Combined | English Only |
| Bangor University | n/a | 360 | 3600 | Combined | English Only |
| BSc (Hons) Computing | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| Wrexham Glyndwr University | n/a | 360 | 3600 | Combined | English Only |
| BSc (Hons) in Digital and Technology Solutions (Software Engineering) | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| University of South Wales | n/a | 360 | 3600 | Combined | English Only |
| BSc (Hons) Cloud Software Development | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| University of Wales Trinity Saint David | n/a | 360 | 3600 | Combined | English Only |
| BSc (Hons) Cloud Computing | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| University of Wales Trinity Saint David | n/a | 360 | 3600 | Combined | English Only |
Please see Annex 1 for the relationship between the competence and knowledge units within the combined qualification.
Essential Skills Wales (ESW)
| Level 6: Applied Software Engineering Degree Apprenticeship | Level | Minimum Credit Value |
|---|---|---|
| Communication | 2 | 6 |
| Application of number | 2 | 6 |
| Digital literacy | 2 | 6 |
Essential Skills Wales qualifications assessment languages are English-Welsh
On/Off the Job training
| Pathway | Minimum On the Job Training Hours | Minimum Off the Job Training Hours |
|---|---|---|
| Level 6: Applied Software Engineering Degree Apprenticeship | 500 | 900 |
On/Off the Job Qualification details (Minimum Credit & Hours)
360 credits for competence and knowledge
The total amount of learning hours which includes both on and off-the-job training for the Applied Software Engineering Degree Apprenticeship is 1400.
Pathway duration approximately 36 months
On/Off the Job Essential Skills details (Minimum Credit & Hours)
- 6 credits / 60 GLH Level 2 Essential Skills Wales Communication
- 6 credits / 60 GLH Level 2 Essential Skills Wales Application of Number
- 6 credits / 60 GLH Level 2 Essential Skills Wales Digital Literacy
Level 6: Applied Data Science Degree Apprenticeship
Level 6: Applied Data Science Degree Apprenticeship Qualifications
Participants must achieve one of the following combined qualifications below.
| BSc (Hons) Computing (Data and Information Systems) | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| University of Wales Trinity Saint David | n/a | 360 | 3600 | Combined | English Only |
| BSc (Hons) Applied Data Science | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| Cardiff Metropolitan University | n/a | 360 | 3600 | Combined | English Only |
| Bangor University | n/a | 360 | 3600 | Combined | English Only |
| BSc (Hons) in Digital and Technology Solutions (Data Science) | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| University of South Wales | n/a | 360 | 3600 | Combined | English Only |
Please see Annex 2 for the relationship between the competence and knowledge units within the combined qualification.
Essential Skills Wales (ESW)
| Level 6: Applied Data Science Degree Apprenticeship | Level | Minimum Credit Value |
|---|---|---|
| Communication | 2 | 6 |
| Application of number | 2 | 6 |
| Digital literacy | 2 | 6 |
Essential Skills Wales qualifications assessment languages are English-Welsh
On/Off the Job training
| Pathway | Minimum On the Job Training Hours | Minimum Off the Job Training Hours |
|---|---|---|
| Level 6: Applied Data Science Degree Apprenticeship | 500 | 900 |
On/Off the Job Qualification details (Minimum Credit & Hours)
360 credits for competence and knowledge
The total amount of learning hours which includes both on and off-the-job training for the Applied Data Science Degree Apprenticeship is 1400.
Pathway duration approximately 36 months
On/Off the Job Essential Skills details (Minimum Credit & Hours)
- 6 credits / 60 GLH Level 2 Essential Skills Wales Communication
- 6 credits / 60 GLH Level 2 Essential Skills Wales Application of Number
- 6 credits / 60 GLH Level 2 Essential Skills Wales Digital Literacy
Level 6: Applied Cyber Security Management
Level 6: Applied Cyber Security Management Qualifications
Participants must achieve one of the following combined qualifications below.
| BSc (Hons) Computing (Computer Networks & Cyber Security) | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| University of Wales Trinity Saint David | n/a | 360 | 3600 | Combined | English only |
| BSc (Hons) Cyber Security | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| Glyndwr University | n/a | 360 | 3600 | Combined | English Only |
| BSc (Hons) Applied Cyber Security | |||||
|---|---|---|---|---|---|
| Awarding Body | Qualification No. | Credit Value | Total Qualification Time | Combined / Competence / Knowledge | Qualification Assessment Lanaguage(s) |
| Cardiff Metropolitan University | n/a | 360 | 3600 | Combined | English only |
| Bangor University | n/a | 360 | 3600 | Combined | English only |
Please see Annex 3 for the relationship between the competence and knowledge units within the combined qualification.
Essential Skills Wales (ESW)
| Level 6: Applied Cyber Security Management | Level | Minimum Credit Value |
|---|---|---|
| Communication | 2 | 6 |
| Application of number | 2 | 6 |
| Digital literacy | 2 | 6 |
Essential Skills Wales qualifications assessment languages are English-Welsh
On/Off the Job training
| Pathway | Minimum On the Job Training Hours | Minimum Off the Job Training Hours |
|---|---|---|
| Level 6: Applied Cyber Security Management | 500 | 900 |
On/Off the Job Qualification details (Minimum Credit & Hours)
360 credits for competence and knowledge (Combined).
The total amount of learning hours which includes both on and off-the-job training for the Applied Cyber Security Management Degree Apprenticeship is 1400.
Pathway duration approximately 36 months.
On/Off the Job Essential Skills details (Minimum Credit & Hours)
- 6 credits / 60 GLH Level 2 Essential Skills Wales Communication
- 6 credits / 60 GLH Level 2 Essential Skills Wales Application of Number
- 6 credits / 60 GLH Level 2 Essential Skills Wales Digital Literacy
Other additional requirements
Applicants for this apprenticeship pathway are likely to be 19+ years.
Progression
Progression from the Level 6 Degree Apprenticeship – Applied Software Engineering
Progression from this pathway for those who have completed a degree apprenticeship in Applied Software Engineering (Level 6):
- employment as a software engineer in the job roles stated in this framework or similar job roles
- Masters Degrees in the relevant specialism.
Progression from the Level 6 Degree Apprenticeship –Applied Data Science
Progression from this pathway for those who have completed a degree apprenticeship in Applied Data Science (Level 6):
- employment as a data scientist in the job roles stated in this framework or similar job roles
- Masters Degrees in the relevant specialism.
Progression from the Level 6 Degree Apprenticeship – Applied Cyber Security Management
Progression from this pathway for those who have completed a degree apprenticeship in Applied Cyber Security (Level 6):
- employment as a cyber-security analyst in the job roles stated in this framework or similar job roles
- Masters Degrees in the relevant specialism.
Equality and diversity
It is important that Apprenticeship Pathways are inclusive and can demonstrate an active approach to identifying and removing barriers to entry and progression. Pathways should advance equality of opportunity between persons who share protected characteristics and those persons who do not as identified in the Equality Act 2010.
The Protected characteristics identified in the Equality Act are age, disability, gender re-assignment, race, religion or belief, sex, sexual orientation, pregnancy and maternity. Marriage and civil partnership is also included although only in respect of the requirement to eliminate discrimination in employment.
Training providers and employers must also comply with the other duty under the Equality Act 2010 to ensure that applicants are not discriminated against in terms of entry to the industry based upon those nine protected characteristics.
Digital Degree Apprenticeship Framework offers no barriers to entry and is intended to accommodate all learners regardless of their gender, age, disability, religious beliefs, or ethnic origins. The learning content required for the off-the-job learning can be delivered in a number of different learning styles to accommodate learner requirements.
Apprenticeships are seen as a vital route to encourage and facilitate a greater diversity of individuals into the industry. Employers and training providers are encouraged to offer additional support and mentoring to ensure that apprentices complete their training.
The following sections are included to identify current workforce demographics. (Data refers to the UK as a whole and to the IT & Telecoms sectors).
Gender Equality
Gender imbalance remains a significant issue for the IT & Telecoms sector. Considering IT & Telecoms professional job roles across all sectors, there has been a drop of female representation from 22% in 2001 to 18% in 2011. This compares to the overall UK workforce being 48% female.
As is the case in industry, gender imbalance is prevalent across IT-related courses, and this is worsening over time throughout the education system. 15% of applicants to Computing degree courses are female and the proportion of females who sat the 2013 Computing A-Level is 6.5%, 1.3 percentage points lower than in 2012.
This under-representation of women across the whole IT & Telecoms sector has a number of causes. These include:
- lack of awareness (by both individuals and career advisors) of the broad range of career opportunities available
- confusion in school teaching of ICT between IT User and IT professional roles.
Age of Workforce
Analysis of the period 2001-2011 shows a changing trend in the age profile of IT & Telecoms professionals. The proportion of people aged 16-29 has dropped from 33% in 2001 to 19% in 2011.
The average age of IT & Telecoms professionals working in the UK is estimated to be 39 years old, compared with 41 years old for workers more generally. Just under one half (47%) of IT & Telecoms professionals are aged 40 or above and less than one in five (19%) are in the 16-29 age bracket.
A key contributory factor to this changing dynamic in IT & Telecoms is the effect of globalisation. The maintenance of strong apprenticeship programmes in the sector will be vital to ensure that this trend can be halted or reversed in the coming years, thereby ensuring that the sector has the pipeline of skilled professionals that it requires to move into higher level job roles in 5-10 years’ time.
Ethnicity and Disability
The Information and communication technologies industry is one of the most ethnically diverse industries in the UK, with 13% of the workforce (an increase from 8% of the workforce in 2002) Black, Asian and Minority Ethnic compared to 9% across the whole economy.
There is significant provision for individuals with disabilities throughout the IT & Telecoms sector with many, varied opportunities for rewarding careers at all levels. This in turn means that apprenticeships are available in a wide range of areas for those with differing levels of disability.
Employment responsibilities and rights
Employment Responsibilities and Rights (ERR) is no longer compulsory. But it is recommended that all apprentices receive a company induction programme.
Responsibilities
It is the responsibility of the Training Provider and Employer to ensure that the requirements of this pathway are delivered in accordance with the Welsh Government/Medr Apprenticeships Guidance.
Further information may be obtained from: Medr
Annex 1 - Level 6: Applied Software Engineering
Relationship between competence and knowledge qualifications
This is a combined degree qualification that delivers both the knowledge and competence requirements with minimum of 360 credits as set out in the Digital and Engineering and Advanced Manufacturing degree apprenticeship learning and skills pathway outcomes specification, March 2019.
Applied Software Engineering Degree Apprenticeship Framework High Level Skills and Knowledge Skills
A degree apprenticeship Software Engineering graduate is able to:
1. Develop the knowledge, skills, and professional competences to operate in a professional software engineering environment, through developing a professional approach to:
- Technical software development and integration
- Collaboration and teamwork
- Delivery focus, including project task estimating and tracking project progress
- Presentation and communication
2. Design appropriate software solutions in relevant contemporary application contexts/domains and architectural considerations using contemporary software development approaches that deliver business value and meet customer requirements.
3. Appreciate the full stack approach to software development including front end usability, middle and back end data systems needs are met.
4. Build and test software solutions for a range of application contexts/domains using contemporary development approaches, understanding how to apply contemporary approaches such as Agile, DevOps, continuous integration.
5. Implement approaches to software testing including unit testing, and process based approaches such as behaviour driven or test-driven development (BDD or TDD).
6. Create relevant software documentation using contemporary practices such as the creation of ‘living’ documentation.
7. Apply new models, techniques, and technologies as they emerge and appreciate the necessity of such continuing professional development.
8. Embed relevant cyber security resilience requirements through defensive programming approaches throughout the secure software development life cycle.
9. Design, develop and deploy cloud based applications, applying such as scaling/performance and the use of virtual machines (VMs) vs Web Applications.
10. Be fluent in at least one relevant industry-standard programming language according to employer needs, and capable of performing tasks at any relevant level of the technical stack in which they reside.
Knowledge
A degree apprenticeship Software Engineering graduate should know and understand:
1. Current theories, models, and techniques for software engineering problem identification and analysis, software design, development, implementation, verification, and documentation and how to apply these.
2. The range of industry standards and regulation relating to software development, including GDPR.
3. How to implement privacy by design.
4. How to analyse customer requirements and prioritise and apply these to develop software products, making them scalable, robust and secure.
5. How to keep up to date with technical and methodological developments in software engineering practice.
6. The range of industry standard tools such as IDEs, configuration management and source control etc. and how to apply them.
7. The full stack environment, and the range of different activities and roles that support development, including:
- Systems infrastructure (hardware, OS and dependencies)
- Creating, manipulating, and querying databases
- API / back-end code
- Front-end design (UX/ UI) and code.
8. The techniques that can be implemented to mitigate against cyber security threats and the main sources of industry research for cyber security threats to applications (e.g. OWASP top ten application security risks).
9. The principles of current software patterns and how to apply them.
10. Current industry regulation, including privacy by design and GDPR.
11. How to document, build, deploy and maintain software products and services, supporting real users.
12. How to implement software testing using unit testing to review, debug and test code to identify and fix bugs and defects and contemporary process based approaches such as behaviour driven or test-driven development (BDD or TDD).
13. The importance of applying negotiation, effective work habits, leadership, and good communication with stakeholders in a typical software development business environment.
14. That user experience and the full user journey, including all touchpoints where a user interacts with the software system or product are important inputs into the software design development process.
15. The fundamentals of cloud environment and services such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).
16. How to create and link datasets to applications and apply database design considerations such as indexing, locking, sequencing, security, transactional, clustering, etc.
17. How to communicate technical software development ideas to a range of audiences, verbally and in writing.
18. How to apply project delivery techniques appropriate to software engineering projects such as estimation, reviewing delivery plans and monitoring development progress.
19. The implementation of relevant contemporary software architectures, including service oriented architecture (SOA) and micro services architecture.
Applied Software Engineering Low Level Learning and Skills Outcomes
Learning and Skills Topics for Software Engineering
1. Business
1.1 Business functions, behaviours, ethics and courtesies
1.2 Business strategy and management
1.3 Business information security.
2. Technology
2.1 Software Development Essentials
2.2 Data and Algorithms
2.3 Software Modelling & Analysis
2.4 Software Architecture
2.5 Software Requirements Management
2.6 Software Design
2.7 Software Verification and Testing
2.8 Software Development Process
2.9 Software Development in Context
2.10 Software Configuration and Release Management
2.11 Software Deployment
2.12 Software Maintenance
2.13 Software Quality
2.14 Data Modelling, Database Development and Data Analysis
2.15 Software Security.
3. Defensive Programming / Software Security
3.1. The critical web application security risks
3.2. Secure coding practices
3.3. Coding frameworks and their benefits.
4. Personal and Inter-Personal
4.1 Communications
4.2 Personal attributes
4.3 Professional attributes
4.4 Project responsibilities
4.5 Team working.
Annex 2 - Level 6: Applied Data Science
Relationship between competence and knowledge qualifications
This is a combined degree qualification that delivers both the knowledge and competence requirements with minimum of 360 credits as set out in the Applied Data Science degree apprenticeship framework specification.
Applied Data Science Degree Apprenticeship Framework High Level Skills and Knowledge
Skills
A degree apprenticeship Data Science graduate is able to:
1. Develop the knowledge, skills, and professional competences to operate in a professional data science environment, through developing a professional approach to:
- Technical data engineering, data analytics and data science
- Collaboration and teamwork
- Data project delivery
- Presentation and communication
2. Identify and clarify problems an organisation faces, and reformulate them into Data Science problems. Devise solutions and make decisions in context by seeking feedback from stakeholders. Apply scientific methods through experiment design, measurement, hypothesis testing and delivery of results. Collaborate with colleagues to gather requirements.
3. Perform data engineering: create and handle datasets for analysis. Use tools and techniques to source, access, explore, profile, pipeline, combine, transform and store data, and apply governance (quality control, security, privacy) to data.
4. Identify and use an appropriate range of programming languages and tools for data manipulation, analysis, visualisation, and system integration. Select appropriate data structures and algorithms for the problem. Develop reproducible analysis and robust code, working in accordance with software development standards, including security, accessibility, code quality and version control.
5. Use analysis and models to inform and improve organisational outcomes, building models and validating results with statistical testing: perform statistical analysis, feature selection and engineering, machine learning, optimisation, and simulations, using the appropriate techniques for the problem.
6. Implement data solutions, using relevant software engineering architectures and design patterns. Evaluate Cloud vs. on premise deployment. Assess value for money and Return on Investment. Scale a system up/out.
7. Find, present, communicate and disseminate outputs effectively and with high impact through creative storytelling, tailoring the message for the audience. Use the best mediumfor each audience, such as technical writing, reporting and dashboards. Visualise data to tell compelling and actionable narratives relevant for organisation goals.
8. Develop and maintain collaborative relationships at strategic and operational levels, using methods of organisational empathy (human, organisation and technical) and build relationships through active listening and trust development.
9. Use project delivery techniques and tools appropriate to their Data Science project and organisation. Plan, organise and manage resources to successfully run a small Data Science project, achieve organisational goals and enable effective change.
Knowledge
A degree apprenticeship Data Science graduate should understand:
1. The context of Data Science and the Data Science community in relation to computer science, statistics and software engineering. How differing schools of thought in these disciplines have driven new approaches to data systems.
2. How Data Science operates within the context of data governance, data security, and communications. How Data Science can be applied to improve an organisation’s processes, operations and outputs. How data and analysis may exhibit biases and prejudice. Howethics and current privacy legislation affect Data Science work.
3. How data can be used systematically in an organisation, including:
3.1 Data processing and storage, including on premise and cloud technologies.
3.2 Database systems including relational, data warehousing & online analytical processing, and “NoSQL” approaches; the pros and cons of each approach.
3.3 Data-driven decision making and the good use of evidence and analytics in making choices and decisions.
4. How to design, implement and optimise analytical algorithms – as prototypes and at production scale – using:
4.1 Statistical and mathematical models and methods.
4.2 Advanced analytics and machine learning techniques, simulations and optimisation.
4.3 Applications such as computer vision and Natural Language Processing.
4.4 An awareness of the computing and organisational resource constraints and trade-offs involved in selecting models, algorithms and tools.
4.5 Development standards, including programming practice, testing, source control.
5. The data landscape: how to critically analyse, interpret and evaluate complex information from diverse datasets:
5.1 Sources of data including but not exclusive to files, operational systems, databases,web services, open data, government data, news and social media.
5.2 Data formats, structures and data delivery methods including “unstructured”data.
5.3 Common patterns in real-world data.
Applied Data Science Degree Apprenticeship Framework Topics and Low Level Outcomes
Learning and Skills Topics for Applied Data Science
1. Business
1.1. Business functions, behaviours, ethics, and courtesies
1.2. Business strategy and management
1.3. Business information security.
2. Data Science Techniques
2.1 Data problem analysis and hypothesis
2.2 Statistical analysis
2.3 Data engineering
2.4 Data programming
2.5 Data analysis
2.6 Applied machine learning
2.7 Data visualisation, presentation and communication
2.8 Data ethics.
3. Personal and interpersonal29
3.1. Communications
3.2. Personal attributes
3.3. Professional attributes
3.4 Project responsibilities
3.5. Team working
Annex 3 - Level 6: Applied Cyber Security Management
Relationship between competence and knowledge qualifications
This is a combined degree qualification that delivers both the knowledge and competence requirements with minimum of 360 credits as set out in the Applied Cyber Security Management degree apprenticeship framework specification.
Applied Cyber Security Degree Apprenticeship Framework High Level Skills and Knowledge
Skills
A Cyber Security degree apprenticeship graduate is able to:
1. Develop the knowledge, skills, and professional competences to operate in a professional cyber security environment, through developing a professional approach to:
- Information security governance, risk management, security program development and management, and security incident management
- Collaboration and teamwork
- Cyber security project delivery
- Presentation and communication.
2. Assist in developing and implementing an information security strategy aligned with business goals and objectives. Identify drivers affecting the enterprise. Develop business cases justifying investment in information security. Identify legal and regulatory requirements.
3. Identify, analyse and evaluate security threats and hazards to a digital business system or service using relevant external sources of threat intelligence or advice.
4. Establish a process for information asset classification and ownership. Implement a systematic and structured information risk assessment process. Ensure that business impact assessments are conducted periodically. Ensure that threat and vulnerability evaluations are performed on an ongoing basis. Identify and evaluate information security controls and countermeasures. Identify the gap between current and desired risk levels to manage risk to an acceptable level. Report significant changes in information risk to appropriate levels of management.
5. Specify the activities to be performed within an information security program. Ensure alignment between the information security program and other assurance functions. Ensure the communication and maintenance of standards, procedures and other documentation that support information security policies. Monitor, measure, test and report on the effectiveness and efficiency of information security controls and compliance with information security policies.
6. Proactively identify, analyse, manage and respond effectively to unexpected security events that may adversely affect the enterprise’s information assets and/or its ability to operate.
Knowledge
A degree apprenticeship Cyber Security graduate should know and understand:
1. The foundations of cyber security, its significance to business and society, the theory and concepts such as; security, identity, confidentiality, integrity, availability, threat, vulnerability, risk, hazard and assurance, and how these relate to each other.
2. Understand the broad requirements for effective information security governance, the elements and actions required to develop an information security strategy and a plan of action to implement it.
3. Understand the nature of the information that is being protected to classify it and to identify the impact of such information being compromised.
4. The importance of risk management as a tool for meeting business needs and developing a security management program to support these needs while managing information risk to an acceptable level to meet the business and compliance requirements of the organisation.
5. The broad requirements and activities needed to create, manage and maintain a program to implement an information security strategy. The information security program may consist of a series of projects and initiatives to achieve the objectives the strategy is designed to address as well as ongoing management and administration.
6. How to implement cyber security incident response processes and follow these when an incident is identified.
7. Relevant laws and ethics – describe security standards, regulations and their consequences; the role of criminal and other law; key relevant features of UK and international law.
8. The existing threat landscape, trends and their significance, including how to apply relevant techniques for threat intelligence.
9. The need to embed cyber security resilience requirements throughout application and infrastructure development life cycles.
Applied Cyber Security Degree Apprenticeship Framework Topics and Low Level Outcomes Learning and Skills Topics for Applied Cyber Security
1. Business
1.1. Business functions, behaviours, ethics, and courtesies
1.2. Business strategy and management.
2. Security concepts and foundations
2.1 Cyber security concepts
2.2 Cyber security threats
2.3 Cyber security vulnerabilities
2.4 Insider threat analysis and management38
2.5 Information assurance
2.6 Cyber security culture
2.7 Cyber security awareness.
3. Information security governance
3.1. The legal, regulatory and compliance environment
3.2. The role of assurance in management of the secure enterprise
3.3. Security management standards and policies
3.4. Establish an information security strategy
3.5. Establish and maintain an information security governance framework
3.6. Integrate information security governance into enterprise governance
3.7. Establish and maintaining information security policies.
4. Information risk management and compliance
4.1. Risk modelling and analysis
4.2. Risk assessment
4.3. Applied risk management.
5. Information security program development and management
5.1. Implement and execute security programs
5.2. Integrate information security requirements into internal processes and 3rd party contracts
5.3. Monitor information security program metrics.
6. Incident investigation and management
6.1. Security monitoring, analysis and intrusion detection
6.2. Incident response management and handling
6.3. Digital forensics.
7. Personal and interpersonal
7.1. Communications
7.2. Personal attributes
7.3. Professional attributes
7.4. Project responsibilities
7.5. Team working