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18 credits · Self-paced

Generative AI Prompt Engineering

Design, test and ship production-grade prompts for LLMs.

A hands-on programme on prompt design, evaluation, RAG, tool use, agents, safety and prompt-ops — using GPT, Claude, Gemini and open-source models.

Available in your language:

Curriculum

  1. 01How LLMs Work — a Practitioner View25 min+

    How LLMs Work — a Practitioner View

    Module of "Generative AI Prompt Engineering" — Phoenix Learning Cloud

    Overview

    This module gives you a rigorous, globally benchmarked treatment of How LLMs Work — a Practitioner View as it applies to Generative AI Prompt Engineering. Content is aligned to leading international standards and current industry practice (ISO, IEEE, PMBOK, CFA Institute, FATF, NIST, OECD, WHO, IFRS, GDPR, ITIL 4, CEFR and equivalent frameworks where relevant), and structured around Bloom's taxonomy so that you move from understanding to application, analysis and evaluation.

    Learning Outcomes

    By the end of this module you will be able to:

    1. Explain the core concepts, terminology and history underpinning How LLMs Work — a Practitioner View in the context of Generative AI Prompt Engineering.
    2. Apply recognised international frameworks, standards and best practices to real-world problems in this area.
    3. Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
    4. Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
    5. Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.

    Topics Covered

    • Foundational concepts, vocabulary and historical evolution of How LLMs Work — a Practitioner View.
    • Global frameworks, regulations and reference architectures relevant to Generative AI Prompt Engineering.
    • Key roles, responsibilities and stakeholder maps.
    • Processes, workflows and decision points, illustrated with annotated diagrams.
    • Tools, platforms and methods currently used by leading organisations.
    • Metrics, KPIs and quality criteria used to measure success.
    • Common failure modes, anti-patterns and mitigation strategies.
    • Cross-cutting concerns: ethics, security, privacy, accessibility, DEI and sustainability.
    • Emerging trends (AI, automation, regulation, geopolitics) and how they reshape practice.

    Global Standards & References

    • ISO / IEC standards relevant to the topic (e.g. ISO 9001, ISO 27001, ISO 31000, ISO 20000, ISO 14001 as applicable).
    • Sector bodies: PMI (PMBOK 7), CFA Institute, ACCA, IIA, FATF, NIST, ENISA, WHO, IFRS Foundation, OECD, UN SDGs, ITIL 4, TOGAF, IEEE, W3C, CEFR.
    • Landmark legislation and guidance: GDPR, UK Data Protection Act, HIPAA, SOX, Basel III/IV, MiFID II, EU AI Act, DORA.
    • Recognised textbooks, whitepapers and peer-reviewed journals cited in each lesson video.

    Activities & Practical Work

    • Guided walkthrough of a real-world scenario using a downloadable template.
    • Case study analysis with structured questions and a marking rubric.
    • Hands-on lab or workshop task producing a portfolio artefact (plan, model, code, policy, or design).
    • Peer discussion prompt in the Phoenix community for cross-industry perspectives.
    • Reflection journal to convert new knowledge into personal action.

    Assessment

    • Knowledge check quiz (10 questions, 70% pass mark, unlimited retakes).
    • Applied assignment graded against a competency rubric (submit for instructor or peer review).
    • Contribution to the module discussion counts toward the participation grade.
    • Successful completion contributes credits toward your Phoenix Learning Cloud certificate for Generative AI Prompt Engineering, which is QR-verifiable and issued upon passing the end-of-course assessment.

    Estimated Effort

    Approximately 3–5 hours of study, plus 1–2 hours of practical work. All content is available in your chosen platform language and can be resumed at any time from My Learning.

    Next Steps

    Complete the quiz, submit the applied assignment, and continue to the next module. Struggling with a concept? Ask the built-in AI Tutor or post in the community — instructors respond within one business day.

  2. 02Prompt Patterns & Techniques25 min+

    Prompt Patterns & Techniques

    Module of "Generative AI Prompt Engineering" — Phoenix Learning Cloud

    Overview

    This module gives you a rigorous, globally benchmarked treatment of Prompt Patterns & Techniques as it applies to Generative AI Prompt Engineering. Content is aligned to leading international standards and current industry practice (ISO, IEEE, PMBOK, CFA Institute, FATF, NIST, OECD, WHO, IFRS, GDPR, ITIL 4, CEFR and equivalent frameworks where relevant), and structured around Bloom's taxonomy so that you move from understanding to application, analysis and evaluation.

    Learning Outcomes

    By the end of this module you will be able to:

    1. Explain the core concepts, terminology and history underpinning Prompt Patterns & Techniques in the context of Generative AI Prompt Engineering.
    2. Apply recognised international frameworks, standards and best practices to real-world problems in this area.
    3. Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
    4. Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
    5. Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.

    Topics Covered

    • Foundational concepts, vocabulary and historical evolution of Prompt Patterns & Techniques.
    • Global frameworks, regulations and reference architectures relevant to Generative AI Prompt Engineering.
    • Key roles, responsibilities and stakeholder maps.
    • Processes, workflows and decision points, illustrated with annotated diagrams.
    • Tools, platforms and methods currently used by leading organisations.
    • Metrics, KPIs and quality criteria used to measure success.
    • Common failure modes, anti-patterns and mitigation strategies.
    • Cross-cutting concerns: ethics, security, privacy, accessibility, DEI and sustainability.
    • Emerging trends (AI, automation, regulation, geopolitics) and how they reshape practice.

    Global Standards & References

    • ISO / IEC standards relevant to the topic (e.g. ISO 9001, ISO 27001, ISO 31000, ISO 20000, ISO 14001 as applicable).
    • Sector bodies: PMI (PMBOK 7), CFA Institute, ACCA, IIA, FATF, NIST, ENISA, WHO, IFRS Foundation, OECD, UN SDGs, ITIL 4, TOGAF, IEEE, W3C, CEFR.
    • Landmark legislation and guidance: GDPR, UK Data Protection Act, HIPAA, SOX, Basel III/IV, MiFID II, EU AI Act, DORA.
    • Recognised textbooks, whitepapers and peer-reviewed journals cited in each lesson video.

    Activities & Practical Work

    • Guided walkthrough of a real-world scenario using a downloadable template.
    • Case study analysis with structured questions and a marking rubric.
    • Hands-on lab or workshop task producing a portfolio artefact (plan, model, code, policy, or design).
    • Peer discussion prompt in the Phoenix community for cross-industry perspectives.
    • Reflection journal to convert new knowledge into personal action.

    Assessment

    • Knowledge check quiz (10 questions, 70% pass mark, unlimited retakes).
    • Applied assignment graded against a competency rubric (submit for instructor or peer review).
    • Contribution to the module discussion counts toward the participation grade.
    • Successful completion contributes credits toward your Phoenix Learning Cloud certificate for Generative AI Prompt Engineering, which is QR-verifiable and issued upon passing the end-of-course assessment.

    Estimated Effort

    Approximately 3–5 hours of study, plus 1–2 hours of practical work. All content is available in your chosen platform language and can be resumed at any time from My Learning.

    Next Steps

    Complete the quiz, submit the applied assignment, and continue to the next module. Struggling with a concept? Ask the built-in AI Tutor or post in the community — instructors respond within one business day.

  3. 03Structured Outputs & Function Calling25 min+

    Structured Outputs & Function Calling

    Module of "Generative AI Prompt Engineering" — Phoenix Learning Cloud

    Overview

    This module gives you a rigorous, globally benchmarked treatment of Structured Outputs & Function Calling as it applies to Generative AI Prompt Engineering. Content is aligned to leading international standards and current industry practice (ISO, IEEE, PMBOK, CFA Institute, FATF, NIST, OECD, WHO, IFRS, GDPR, ITIL 4, CEFR and equivalent frameworks where relevant), and structured around Bloom's taxonomy so that you move from understanding to application, analysis and evaluation.

    Learning Outcomes

    By the end of this module you will be able to:

    1. Explain the core concepts, terminology and history underpinning Structured Outputs & Function Calling in the context of Generative AI Prompt Engineering.
    2. Apply recognised international frameworks, standards and best practices to real-world problems in this area.
    3. Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
    4. Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
    5. Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.

    Topics Covered

    • Foundational concepts, vocabulary and historical evolution of Structured Outputs & Function Calling.
    • Global frameworks, regulations and reference architectures relevant to Generative AI Prompt Engineering.
    • Key roles, responsibilities and stakeholder maps.
    • Processes, workflows and decision points, illustrated with annotated diagrams.
    • Tools, platforms and methods currently used by leading organisations.
    • Metrics, KPIs and quality criteria used to measure success.
    • Common failure modes, anti-patterns and mitigation strategies.
    • Cross-cutting concerns: ethics, security, privacy, accessibility, DEI and sustainability.
    • Emerging trends (AI, automation, regulation, geopolitics) and how they reshape practice.

    Global Standards & References

    • ISO / IEC standards relevant to the topic (e.g. ISO 9001, ISO 27001, ISO 31000, ISO 20000, ISO 14001 as applicable).
    • Sector bodies: PMI (PMBOK 7), CFA Institute, ACCA, IIA, FATF, NIST, ENISA, WHO, IFRS Foundation, OECD, UN SDGs, ITIL 4, TOGAF, IEEE, W3C, CEFR.
    • Landmark legislation and guidance: GDPR, UK Data Protection Act, HIPAA, SOX, Basel III/IV, MiFID II, EU AI Act, DORA.
    • Recognised textbooks, whitepapers and peer-reviewed journals cited in each lesson video.

    Activities & Practical Work

    • Guided walkthrough of a real-world scenario using a downloadable template.
    • Case study analysis with structured questions and a marking rubric.
    • Hands-on lab or workshop task producing a portfolio artefact (plan, model, code, policy, or design).
    • Peer discussion prompt in the Phoenix community for cross-industry perspectives.
    • Reflection journal to convert new knowledge into personal action.

    Assessment

    • Knowledge check quiz (10 questions, 70% pass mark, unlimited retakes).
    • Applied assignment graded against a competency rubric (submit for instructor or peer review).
    • Contribution to the module discussion counts toward the participation grade.
    • Successful completion contributes credits toward your Phoenix Learning Cloud certificate for Generative AI Prompt Engineering, which is QR-verifiable and issued upon passing the end-of-course assessment.

    Estimated Effort

    Approximately 3–5 hours of study, plus 1–2 hours of practical work. All content is available in your chosen platform language and can be resumed at any time from My Learning.

    Next Steps

    Complete the quiz, submit the applied assignment, and continue to the next module. Struggling with a concept? Ask the built-in AI Tutor or post in the community — instructors respond within one business day.

  4. 04Retrieval-Augmented Generation (RAG)30 min+

    Retrieval-Augmented Generation (RAG)

    Module of "Generative AI Prompt Engineering" — Phoenix Learning Cloud

    Overview

    This module gives you a rigorous, globally benchmarked treatment of Retrieval-Augmented Generation (RAG) as it applies to Generative AI Prompt Engineering. Content is aligned to leading international standards and current industry practice (ISO, IEEE, PMBOK, CFA Institute, FATF, NIST, OECD, WHO, IFRS, GDPR, ITIL 4, CEFR and equivalent frameworks where relevant), and structured around Bloom's taxonomy so that you move from understanding to application, analysis and evaluation.

    Learning Outcomes

    By the end of this module you will be able to:

    1. Explain the core concepts, terminology and history underpinning Retrieval-Augmented Generation (RAG) in the context of Generative AI Prompt Engineering.
    2. Apply recognised international frameworks, standards and best practices to real-world problems in this area.
    3. Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
    4. Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
    5. Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.

    Topics Covered

    • Foundational concepts, vocabulary and historical evolution of Retrieval-Augmented Generation (RAG).
    • Global frameworks, regulations and reference architectures relevant to Generative AI Prompt Engineering.
    • Key roles, responsibilities and stakeholder maps.
    • Processes, workflows and decision points, illustrated with annotated diagrams.
    • Tools, platforms and methods currently used by leading organisations.
    • Metrics, KPIs and quality criteria used to measure success.
    • Common failure modes, anti-patterns and mitigation strategies.
    • Cross-cutting concerns: ethics, security, privacy, accessibility, DEI and sustainability.
    • Emerging trends (AI, automation, regulation, geopolitics) and how they reshape practice.

    Global Standards & References

    • ISO / IEC standards relevant to the topic (e.g. ISO 9001, ISO 27001, ISO 31000, ISO 20000, ISO 14001 as applicable).
    • Sector bodies: PMI (PMBOK 7), CFA Institute, ACCA, IIA, FATF, NIST, ENISA, WHO, IFRS Foundation, OECD, UN SDGs, ITIL 4, TOGAF, IEEE, W3C, CEFR.
    • Landmark legislation and guidance: GDPR, UK Data Protection Act, HIPAA, SOX, Basel III/IV, MiFID II, EU AI Act, DORA.
    • Recognised textbooks, whitepapers and peer-reviewed journals cited in each lesson video.

    Activities & Practical Work

    • Guided walkthrough of a real-world scenario using a downloadable template.
    • Case study analysis with structured questions and a marking rubric.
    • Hands-on lab or workshop task producing a portfolio artefact (plan, model, code, policy, or design).
    • Peer discussion prompt in the Phoenix community for cross-industry perspectives.
    • Reflection journal to convert new knowledge into personal action.

    Assessment

    • Knowledge check quiz (10 questions, 70% pass mark, unlimited retakes).
    • Applied assignment graded against a competency rubric (submit for instructor or peer review).
    • Contribution to the module discussion counts toward the participation grade.
    • Successful completion contributes credits toward your Phoenix Learning Cloud certificate for Generative AI Prompt Engineering, which is QR-verifiable and issued upon passing the end-of-course assessment.

    Estimated Effort

    Approximately 3–5 hours of study, plus 1–2 hours of practical work. All content is available in your chosen platform language and can be resumed at any time from My Learning.

    Next Steps

    Complete the quiz, submit the applied assignment, and continue to the next module. Struggling with a concept? Ask the built-in AI Tutor or post in the community — instructors respond within one business day.

  5. 05Agents & Tool Use30 min+

    Agents & Tool Use

    Module of "Generative AI Prompt Engineering" — Phoenix Learning Cloud

    Overview

    This module gives you a rigorous, globally benchmarked treatment of Agents & Tool Use as it applies to Generative AI Prompt Engineering. Content is aligned to leading international standards and current industry practice (ISO, IEEE, PMBOK, CFA Institute, FATF, NIST, OECD, WHO, IFRS, GDPR, ITIL 4, CEFR and equivalent frameworks where relevant), and structured around Bloom's taxonomy so that you move from understanding to application, analysis and evaluation.

    Learning Outcomes

    By the end of this module you will be able to:

    1. Explain the core concepts, terminology and history underpinning Agents & Tool Use in the context of Generative AI Prompt Engineering.
    2. Apply recognised international frameworks, standards and best practices to real-world problems in this area.
    3. Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
    4. Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
    5. Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.

    Topics Covered

    • Foundational concepts, vocabulary and historical evolution of Agents & Tool Use.
    • Global frameworks, regulations and reference architectures relevant to Generative AI Prompt Engineering.
    • Key roles, responsibilities and stakeholder maps.
    • Processes, workflows and decision points, illustrated with annotated diagrams.
    • Tools, platforms and methods currently used by leading organisations.
    • Metrics, KPIs and quality criteria used to measure success.
    • Common failure modes, anti-patterns and mitigation strategies.
    • Cross-cutting concerns: ethics, security, privacy, accessibility, DEI and sustainability.
    • Emerging trends (AI, automation, regulation, geopolitics) and how they reshape practice.

    Global Standards & References

    • ISO / IEC standards relevant to the topic (e.g. ISO 9001, ISO 27001, ISO 31000, ISO 20000, ISO 14001 as applicable).
    • Sector bodies: PMI (PMBOK 7), CFA Institute, ACCA, IIA, FATF, NIST, ENISA, WHO, IFRS Foundation, OECD, UN SDGs, ITIL 4, TOGAF, IEEE, W3C, CEFR.
    • Landmark legislation and guidance: GDPR, UK Data Protection Act, HIPAA, SOX, Basel III/IV, MiFID II, EU AI Act, DORA.
    • Recognised textbooks, whitepapers and peer-reviewed journals cited in each lesson video.

    Activities & Practical Work

    • Guided walkthrough of a real-world scenario using a downloadable template.
    • Case study analysis with structured questions and a marking rubric.
    • Hands-on lab or workshop task producing a portfolio artefact (plan, model, code, policy, or design).
    • Peer discussion prompt in the Phoenix community for cross-industry perspectives.
    • Reflection journal to convert new knowledge into personal action.

    Assessment

    • Knowledge check quiz (10 questions, 70% pass mark, unlimited retakes).
    • Applied assignment graded against a competency rubric (submit for instructor or peer review).
    • Contribution to the module discussion counts toward the participation grade.
    • Successful completion contributes credits toward your Phoenix Learning Cloud certificate for Generative AI Prompt Engineering, which is QR-verifiable and issued upon passing the end-of-course assessment.

    Estimated Effort

    Approximately 3–5 hours of study, plus 1–2 hours of practical work. All content is available in your chosen platform language and can be resumed at any time from My Learning.

    Next Steps

    Complete the quiz, submit the applied assignment, and continue to the next module. Struggling with a concept? Ask the built-in AI Tutor or post in the community — instructors respond within one business day.

  6. 06Evaluation, Testing & Prompt-Ops25 min+

    Evaluation, Testing & Prompt-Ops

    Module of "Generative AI Prompt Engineering" — Phoenix Learning Cloud

    Overview

    This module gives you a rigorous, globally benchmarked treatment of Evaluation, Testing & Prompt-Ops as it applies to Generative AI Prompt Engineering. Content is aligned to leading international standards and current industry practice (ISO, IEEE, PMBOK, CFA Institute, FATF, NIST, OECD, WHO, IFRS, GDPR, ITIL 4, CEFR and equivalent frameworks where relevant), and structured around Bloom's taxonomy so that you move from understanding to application, analysis and evaluation.

    Learning Outcomes

    By the end of this module you will be able to:

    1. Explain the core concepts, terminology and history underpinning Evaluation, Testing & Prompt-Ops in the context of Generative AI Prompt Engineering.
    2. Apply recognised international frameworks, standards and best practices to real-world problems in this area.
    3. Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
    4. Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
    5. Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.

    Topics Covered

    • Foundational concepts, vocabulary and historical evolution of Evaluation, Testing & Prompt-Ops.
    • Global frameworks, regulations and reference architectures relevant to Generative AI Prompt Engineering.
    • Key roles, responsibilities and stakeholder maps.
    • Processes, workflows and decision points, illustrated with annotated diagrams.
    • Tools, platforms and methods currently used by leading organisations.
    • Metrics, KPIs and quality criteria used to measure success.
    • Common failure modes, anti-patterns and mitigation strategies.
    • Cross-cutting concerns: ethics, security, privacy, accessibility, DEI and sustainability.
    • Emerging trends (AI, automation, regulation, geopolitics) and how they reshape practice.

    Global Standards & References

    • ISO / IEC standards relevant to the topic (e.g. ISO 9001, ISO 27001, ISO 31000, ISO 20000, ISO 14001 as applicable).
    • Sector bodies: PMI (PMBOK 7), CFA Institute, ACCA, IIA, FATF, NIST, ENISA, WHO, IFRS Foundation, OECD, UN SDGs, ITIL 4, TOGAF, IEEE, W3C, CEFR.
    • Landmark legislation and guidance: GDPR, UK Data Protection Act, HIPAA, SOX, Basel III/IV, MiFID II, EU AI Act, DORA.
    • Recognised textbooks, whitepapers and peer-reviewed journals cited in each lesson video.

    Activities & Practical Work

    • Guided walkthrough of a real-world scenario using a downloadable template.
    • Case study analysis with structured questions and a marking rubric.
    • Hands-on lab or workshop task producing a portfolio artefact (plan, model, code, policy, or design).
    • Peer discussion prompt in the Phoenix community for cross-industry perspectives.
    • Reflection journal to convert new knowledge into personal action.

    Assessment

    • Knowledge check quiz (10 questions, 70% pass mark, unlimited retakes).
    • Applied assignment graded against a competency rubric (submit for instructor or peer review).
    • Contribution to the module discussion counts toward the participation grade.
    • Successful completion contributes credits toward your Phoenix Learning Cloud certificate for Generative AI Prompt Engineering, which is QR-verifiable and issued upon passing the end-of-course assessment.

    Estimated Effort

    Approximately 3–5 hours of study, plus 1–2 hours of practical work. All content is available in your chosen platform language and can be resumed at any time from My Learning.

    Next Steps

    Complete the quiz, submit the applied assignment, and continue to the next module. Struggling with a concept? Ask the built-in AI Tutor or post in the community — instructors respond within one business day.

  7. 07Safety, Guardrails & Red-teaming25 min+

    Safety, Guardrails & Red-teaming

    Module of "Generative AI Prompt Engineering" — Phoenix Learning Cloud

    Overview

    This module gives you a rigorous, globally benchmarked treatment of Safety, Guardrails & Red-teaming as it applies to Generative AI Prompt Engineering. Content is aligned to leading international standards and current industry practice (ISO, IEEE, PMBOK, CFA Institute, FATF, NIST, OECD, WHO, IFRS, GDPR, ITIL 4, CEFR and equivalent frameworks where relevant), and structured around Bloom's taxonomy so that you move from understanding to application, analysis and evaluation.

    Learning Outcomes

    By the end of this module you will be able to:

    1. Explain the core concepts, terminology and history underpinning Safety, Guardrails & Red-teaming in the context of Generative AI Prompt Engineering.
    2. Apply recognised international frameworks, standards and best practices to real-world problems in this area.
    3. Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
    4. Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
    5. Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.

    Topics Covered

    • Foundational concepts, vocabulary and historical evolution of Safety, Guardrails & Red-teaming.
    • Global frameworks, regulations and reference architectures relevant to Generative AI Prompt Engineering.
    • Key roles, responsibilities and stakeholder maps.
    • Processes, workflows and decision points, illustrated with annotated diagrams.
    • Tools, platforms and methods currently used by leading organisations.
    • Metrics, KPIs and quality criteria used to measure success.
    • Common failure modes, anti-patterns and mitigation strategies.
    • Cross-cutting concerns: ethics, security, privacy, accessibility, DEI and sustainability.
    • Emerging trends (AI, automation, regulation, geopolitics) and how they reshape practice.

    Global Standards & References

    • ISO / IEC standards relevant to the topic (e.g. ISO 9001, ISO 27001, ISO 31000, ISO 20000, ISO 14001 as applicable).
    • Sector bodies: PMI (PMBOK 7), CFA Institute, ACCA, IIA, FATF, NIST, ENISA, WHO, IFRS Foundation, OECD, UN SDGs, ITIL 4, TOGAF, IEEE, W3C, CEFR.
    • Landmark legislation and guidance: GDPR, UK Data Protection Act, HIPAA, SOX, Basel III/IV, MiFID II, EU AI Act, DORA.
    • Recognised textbooks, whitepapers and peer-reviewed journals cited in each lesson video.

    Activities & Practical Work

    • Guided walkthrough of a real-world scenario using a downloadable template.
    • Case study analysis with structured questions and a marking rubric.
    • Hands-on lab or workshop task producing a portfolio artefact (plan, model, code, policy, or design).
    • Peer discussion prompt in the Phoenix community for cross-industry perspectives.
    • Reflection journal to convert new knowledge into personal action.

    Assessment

    • Knowledge check quiz (10 questions, 70% pass mark, unlimited retakes).
    • Applied assignment graded against a competency rubric (submit for instructor or peer review).
    • Contribution to the module discussion counts toward the participation grade.
    • Successful completion contributes credits toward your Phoenix Learning Cloud certificate for Generative AI Prompt Engineering, which is QR-verifiable and issued upon passing the end-of-course assessment.

    Estimated Effort

    Approximately 3–5 hours of study, plus 1–2 hours of practical work. All content is available in your chosen platform language and can be resumed at any time from My Learning.

    Next Steps

    Complete the quiz, submit the applied assignment, and continue to the next module. Struggling with a concept? Ask the built-in AI Tutor or post in the community — instructors respond within one business day.

  8. 08Capstone: Ship a Production Prompt System35 min+

    Capstone: Ship a Production Prompt System

    Module of "Generative AI Prompt Engineering" — Phoenix Learning Cloud

    Overview

    This module gives you a rigorous, globally benchmarked treatment of Capstone: Ship a Production Prompt System as it applies to Generative AI Prompt Engineering. Content is aligned to leading international standards and current industry practice (ISO, IEEE, PMBOK, CFA Institute, FATF, NIST, OECD, WHO, IFRS, GDPR, ITIL 4, CEFR and equivalent frameworks where relevant), and structured around Bloom's taxonomy so that you move from understanding to application, analysis and evaluation.

    Learning Outcomes

    By the end of this module you will be able to:

    1. Explain the core concepts, terminology and history underpinning Capstone: Ship a Production Prompt System in the context of Generative AI Prompt Engineering.
    2. Apply recognised international frameworks, standards and best practices to real-world problems in this area.
    3. Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
    4. Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
    5. Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.

    Topics Covered

    • Foundational concepts, vocabulary and historical evolution of Capstone: Ship a Production Prompt System.
    • Global frameworks, regulations and reference architectures relevant to Generative AI Prompt Engineering.
    • Key roles, responsibilities and stakeholder maps.
    • Processes, workflows and decision points, illustrated with annotated diagrams.
    • Tools, platforms and methods currently used by leading organisations.
    • Metrics, KPIs and quality criteria used to measure success.
    • Common failure modes, anti-patterns and mitigation strategies.
    • Cross-cutting concerns: ethics, security, privacy, accessibility, DEI and sustainability.
    • Emerging trends (AI, automation, regulation, geopolitics) and how they reshape practice.

    Global Standards & References

    • ISO / IEC standards relevant to the topic (e.g. ISO 9001, ISO 27001, ISO 31000, ISO 20000, ISO 14001 as applicable).
    • Sector bodies: PMI (PMBOK 7), CFA Institute, ACCA, IIA, FATF, NIST, ENISA, WHO, IFRS Foundation, OECD, UN SDGs, ITIL 4, TOGAF, IEEE, W3C, CEFR.
    • Landmark legislation and guidance: GDPR, UK Data Protection Act, HIPAA, SOX, Basel III/IV, MiFID II, EU AI Act, DORA.
    • Recognised textbooks, whitepapers and peer-reviewed journals cited in each lesson video.

    Activities & Practical Work

    • Guided walkthrough of a real-world scenario using a downloadable template.
    • Case study analysis with structured questions and a marking rubric.
    • Hands-on lab or workshop task producing a portfolio artefact (plan, model, code, policy, or design).
    • Peer discussion prompt in the Phoenix community for cross-industry perspectives.
    • Reflection journal to convert new knowledge into personal action.

    Assessment

    • Knowledge check quiz (10 questions, 70% pass mark, unlimited retakes).
    • Applied assignment graded against a competency rubric (submit for instructor or peer review).
    • Contribution to the module discussion counts toward the participation grade.
    • Successful completion contributes credits toward your Phoenix Learning Cloud certificate for Generative AI Prompt Engineering, which is QR-verifiable and issued upon passing the end-of-course assessment.

    Estimated Effort

    Approximately 3–5 hours of study, plus 1–2 hours of practical work. All content is available in your chosen platform language and can be resumed at any time from My Learning.

    Next Steps

    Complete the quiz, submit the applied assignment, and continue to the next module. Struggling with a concept? Ask the built-in AI Tutor or post in the community — instructors respond within one business day.