5 credits · Self-paced
Applied Generative AI for Professionals
Ship AI features responsibly
Hands-on with LLMs, RAG, evaluation and guardrails for real business use cases.
Curriculum
01Foundations of Generative AI & LLMs45 min+
Foundations of Generative AI & LLMs
Module of "Applied Generative AI for Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Foundations of Generative AI & LLMs as it applies to Applied Generative AI for Professionals. 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:
- Explain the core concepts, terminology and history underpinning Foundations of Generative AI & LLMs in the context of Applied Generative AI for Professionals.
- Apply recognised international frameworks, standards and best practices to real-world problems in this area.
- Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
- Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
- Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.
Topics Covered
- Foundational concepts, vocabulary and historical evolution of Foundations of Generative AI & LLMs.
- Global frameworks, regulations and reference architectures relevant to Applied Generative AI for Professionals.
- 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 Applied Generative AI for Professionals, 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.
02Prompt Engineering Patterns45 min+
Prompt Engineering Patterns
Module of "Applied Generative AI for Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Prompt Engineering Patterns as it applies to Applied Generative AI for Professionals. 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:
- Explain the core concepts, terminology and history underpinning Prompt Engineering Patterns in the context of Applied Generative AI for Professionals.
- Apply recognised international frameworks, standards and best practices to real-world problems in this area.
- Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
- Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
- Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.
Topics Covered
- Foundational concepts, vocabulary and historical evolution of Prompt Engineering Patterns.
- Global frameworks, regulations and reference architectures relevant to Applied Generative AI for Professionals.
- 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 Applied Generative AI for Professionals, 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.
03Retrieval-Augmented Generation (RAG)45 min+
Retrieval-Augmented Generation (RAG)
Module of "Applied Generative AI for Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Retrieval-Augmented Generation (RAG) as it applies to Applied Generative AI for Professionals. 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:
- Explain the core concepts, terminology and history underpinning Retrieval-Augmented Generation (RAG) in the context of Applied Generative AI for Professionals.
- Apply recognised international frameworks, standards and best practices to real-world problems in this area.
- Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
- Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
- 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 Applied Generative AI for Professionals.
- 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 Applied Generative AI for Professionals, 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.
04Fine-Tuning & Model Adaptation45 min+
Fine-Tuning & Model Adaptation
Module of "Applied Generative AI for Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Fine-Tuning & Model Adaptation as it applies to Applied Generative AI for Professionals. 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:
- Explain the core concepts, terminology and history underpinning Fine-Tuning & Model Adaptation in the context of Applied Generative AI for Professionals.
- Apply recognised international frameworks, standards and best practices to real-world problems in this area.
- Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
- Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
- Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.
Topics Covered
- Foundational concepts, vocabulary and historical evolution of Fine-Tuning & Model Adaptation.
- Global frameworks, regulations and reference architectures relevant to Applied Generative AI for Professionals.
- 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 Applied Generative AI for Professionals, 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.
05Multimodal AI (Vision, Audio, Video)45 min+
Multimodal AI (Vision, Audio, Video)
Module of "Applied Generative AI for Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Multimodal AI (Vision, Audio, Video) as it applies to Applied Generative AI for Professionals. 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:
- Explain the core concepts, terminology and history underpinning Multimodal AI (Vision, Audio, Video) in the context of Applied Generative AI for Professionals.
- Apply recognised international frameworks, standards and best practices to real-world problems in this area.
- Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
- Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
- Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.
Topics Covered
- Foundational concepts, vocabulary and historical evolution of Multimodal AI (Vision, Audio, Video).
- Global frameworks, regulations and reference architectures relevant to Applied Generative AI for Professionals.
- 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 Applied Generative AI for Professionals, 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.
06AI Agents & Tool Use45 min+
AI Agents & Tool Use
Module of "Applied Generative AI for Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of AI Agents & Tool Use as it applies to Applied Generative AI for Professionals. 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:
- Explain the core concepts, terminology and history underpinning AI Agents & Tool Use in the context of Applied Generative AI for Professionals.
- Apply recognised international frameworks, standards and best practices to real-world problems in this area.
- Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
- Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
- Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.
Topics Covered
- Foundational concepts, vocabulary and historical evolution of AI Agents & Tool Use.
- Global frameworks, regulations and reference architectures relevant to Applied Generative AI for Professionals.
- 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 Applied Generative AI for Professionals, 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.
07Evaluation, Safety & Guardrails45 min+
Evaluation, Safety & Guardrails
Module of "Applied Generative AI for Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Evaluation, Safety & Guardrails as it applies to Applied Generative AI for Professionals. 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:
- Explain the core concepts, terminology and history underpinning Evaluation, Safety & Guardrails in the context of Applied Generative AI for Professionals.
- Apply recognised international frameworks, standards and best practices to real-world problems in this area.
- Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
- Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
- Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.
Topics Covered
- Foundational concepts, vocabulary and historical evolution of Evaluation, Safety & Guardrails.
- Global frameworks, regulations and reference architectures relevant to Applied Generative AI for Professionals.
- 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 Applied Generative AI for Professionals, 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.
08Responsible AI & Governance45 min+
Responsible AI & Governance
Module of "Applied Generative AI for Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Responsible AI & Governance as it applies to Applied Generative AI for Professionals. 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:
- Explain the core concepts, terminology and history underpinning Responsible AI & Governance in the context of Applied Generative AI for Professionals.
- Apply recognised international frameworks, standards and best practices to real-world problems in this area.
- Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
- Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
- Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.
Topics Covered
- Foundational concepts, vocabulary and historical evolution of Responsible AI & Governance.
- Global frameworks, regulations and reference architectures relevant to Applied Generative AI for Professionals.
- 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 Applied Generative AI for Professionals, 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.
09Deploying GenAI in the Enterprise45 min+
Deploying GenAI in the Enterprise
Module of "Applied Generative AI for Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Deploying GenAI in the Enterprise as it applies to Applied Generative AI for Professionals. 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:
- Explain the core concepts, terminology and history underpinning Deploying GenAI in the Enterprise in the context of Applied Generative AI for Professionals.
- Apply recognised international frameworks, standards and best practices to real-world problems in this area.
- Analyse case studies drawn from Europe, North America, the Middle East, Africa and Asia-Pacific to identify what works, what fails, and why.
- Design a defensible plan, artefact or decision using the tools, templates and checklists introduced in the module.
- Evaluate your work against ethical, legal, security, sustainability and inclusion criteria.
Topics Covered
- Foundational concepts, vocabulary and historical evolution of Deploying GenAI in the Enterprise.
- Global frameworks, regulations and reference architectures relevant to Applied Generative AI for Professionals.
- 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 Applied Generative AI for Professionals, 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.