20 credits · Self-paced
Generative AI for Manufacturing Professionals
Applying LLMs and generative AI across the factory value chain
A specialist programme for manufacturing leaders on applying generative AI across design, planning, quality, maintenance and workforce productivity. Includes governance, safety and adoption playbooks.
Curriculum
01Module 1 — Generative AI foundations for industry30 min+
Module 1 — Generative AI foundations for industry
Module of "Generative AI for Manufacturing Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Module 1 — Generative AI foundations for industry as it applies to Generative AI for Manufacturing 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 Module 1 — Generative AI foundations for industry in the context of Generative AI for Manufacturing 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 Module 1 — Generative AI foundations for industry.
- Global frameworks, regulations and reference architectures relevant to Generative AI for Manufacturing 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 Generative AI for Manufacturing 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.
02Module 2 — LLMs, RAG and copilots explained30 min+
Module 2 — LLMs, RAG and copilots explained
Module of "Generative AI for Manufacturing Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Module 2 — LLMs, RAG and copilots explained as it applies to Generative AI for Manufacturing 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 Module 2 — LLMs, RAG and copilots explained in the context of Generative AI for Manufacturing 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 Module 2 — LLMs, RAG and copilots explained.
- Global frameworks, regulations and reference architectures relevant to Generative AI for Manufacturing 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 Generative AI for Manufacturing 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.
03Module 3 — Generative design and CAD acceleration30 min+
Module 3 — Generative design and CAD acceleration
Module of "Generative AI for Manufacturing Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Module 3 — Generative design and CAD acceleration as it applies to Generative AI for Manufacturing 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 Module 3 — Generative design and CAD acceleration in the context of Generative AI for Manufacturing 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 Module 3 — Generative design and CAD acceleration.
- Global frameworks, regulations and reference architectures relevant to Generative AI for Manufacturing 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 Generative AI for Manufacturing 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.
04Module 4 — AI in production planning & scheduling30 min+
Module 4 — AI in production planning & scheduling
Module of "Generative AI for Manufacturing Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Module 4 — AI in production planning & scheduling as it applies to Generative AI for Manufacturing 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 Module 4 — AI in production planning & scheduling in the context of Generative AI for Manufacturing 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 Module 4 — AI in production planning & scheduling.
- Global frameworks, regulations and reference architectures relevant to Generative AI for Manufacturing 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 Generative AI for Manufacturing 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.
05Module 5 — Quality inspection with vision models30 min+
Module 5 — Quality inspection with vision models
Module of "Generative AI for Manufacturing Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Module 5 — Quality inspection with vision models as it applies to Generative AI for Manufacturing 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 Module 5 — Quality inspection with vision models in the context of Generative AI for Manufacturing 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 Module 5 — Quality inspection with vision models.
- Global frameworks, regulations and reference architectures relevant to Generative AI for Manufacturing 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 Generative AI for Manufacturing 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.
06Module 6 — Predictive maintenance and anomaly detection30 min+
Module 6 — Predictive maintenance and anomaly detection
Module of "Generative AI for Manufacturing Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Module 6 — Predictive maintenance and anomaly detection as it applies to Generative AI for Manufacturing 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 Module 6 — Predictive maintenance and anomaly detection in the context of Generative AI for Manufacturing 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 Module 6 — Predictive maintenance and anomaly detection.
- Global frameworks, regulations and reference architectures relevant to Generative AI for Manufacturing 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 Generative AI for Manufacturing 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.
07Module 7 — AI copilots for shopfloor workers30 min+
Module 7 — AI copilots for shopfloor workers
Module of "Generative AI for Manufacturing Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Module 7 — AI copilots for shopfloor workers as it applies to Generative AI for Manufacturing 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 Module 7 — AI copilots for shopfloor workers in the context of Generative AI for Manufacturing 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 Module 7 — AI copilots for shopfloor workers.
- Global frameworks, regulations and reference architectures relevant to Generative AI for Manufacturing 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 Generative AI for Manufacturing 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.
08Module 8 — Supply chain and procurement use cases30 min+
Module 8 — Supply chain and procurement use cases
Module of "Generative AI for Manufacturing Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Module 8 — Supply chain and procurement use cases as it applies to Generative AI for Manufacturing 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 Module 8 — Supply chain and procurement use cases in the context of Generative AI for Manufacturing 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 Module 8 — Supply chain and procurement use cases.
- Global frameworks, regulations and reference architectures relevant to Generative AI for Manufacturing 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 Generative AI for Manufacturing 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.
09Module 9 — Data readiness and MLOps in manufacturing30 min+
Module 9 — Data readiness and MLOps in manufacturing
Module of "Generative AI for Manufacturing Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Module 9 — Data readiness and MLOps in manufacturing as it applies to Generative AI for Manufacturing 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 Module 9 — Data readiness and MLOps in manufacturing in the context of Generative AI for Manufacturing 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 Module 9 — Data readiness and MLOps in manufacturing.
- Global frameworks, regulations and reference architectures relevant to Generative AI for Manufacturing 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 Generative AI for Manufacturing 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.
10Module 10 — AI governance, safety and adoption30 min+
Module 10 — AI governance, safety and adoption
Module of "Generative AI for Manufacturing Professionals" — Phoenix Learning Cloud
Overview
This module gives you a rigorous, globally benchmarked treatment of Module 10 — AI governance, safety and adoption as it applies to Generative AI for Manufacturing 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 Module 10 — AI governance, safety and adoption in the context of Generative AI for Manufacturing 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 Module 10 — AI governance, safety and adoption.
- Global frameworks, regulations and reference architectures relevant to Generative AI for Manufacturing 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 Generative AI for Manufacturing 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.