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Course Outline
Introduction
Module 1: Foundations of artificial intelligence
- Defines AI and machine learning, presents an overview of the different types of AI systems and their use cases, and positions AI models in the broader socio-cultural context. At the end of this module you will be able to;
- Describe and explain the differences among types of AI systems.
- Describe and explain the AI technology stack.
- Describe and explain AI and the evolution of data science.
Module 2: AI impacts on people and responsible AI principles
- Outlines the core risks and harms posed by AI systems, the characteristics of trustworthy AI systems, and the principles essential to responsible and ethical AI. At the end of this module you will be able to;
- Describe and explain the core risks and harms posed by AI systems.
- Describe and explain the characteristics of trustworthy AI systems.
Module 3: AI development life cycle
- Describes the AI development life cycle and the broad context in which AI risks are managed. At the end of this module you will be able to;
- Describe and explain the similarities and differences among existing and emerging ethical guidance on AI.
- Describe and explain the existing laws that interact with AI use.
- Describe and explain key GDPR intersections.
- Describe and explain liability reform.
Module 4: Implementing responsible AI governance and risk management
- Explains how major AI stakeholders collaborate in a layered approach to manage AI risks while acknowledging AI systems’ potential societal benefits. At the end of this module you will be able to;
- Describe and explain the requirements of the EU AI Act.
- Describe and explain other emerging global laws.
- Describe and explain the similarities and differences among the major risk management frameworks and standards.
Module 5: Implementing AI projects and systems
- Outlines mapping, planning and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems after deployment. At the end of this module you will be able to;
- Describe and explain the key steps in the AI system planning phase.
- Describe and explain the key steps in the AI system design phase.
- Describe and explain the key steps in the AI system development phase.
- Describe and explain the key steps in the AI system implementation phase.
Module 6: Current laws that apply to AI systems
- Surveys the existing laws that govern the use of AI, outlines key GDPR intersections, and provides awareness of liability reform. At the end of this module you will be able to;
- Ensure interoperability of AI risk management with other operational risk strategies
- Integrate AI governance principles into the company.
- Establish an AI governance infrastructure.
- Map, plan and scope the AI project.
- Test and validate the AI system during development.
- Manage and monitor AI systems after deployment.
Module 7: Existing and emerging AI laws and standards
- Describes global AI-specific laws and the major frameworks and standards that exemplify how AI systems can be responsibly governed. At the end of this module you will be able to;
- Gain an awareness of legal issues.
- Gain an awareness of user concerns.
- Gain an awareness of AI auditing and accountability issues.
Module 8: Ongoing AI issues and concerns
- Presents current discussions and ideas about AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability issues.
Summary and Next Step
Requirements
There are no prerequisites for this course.
Who Should Train?
We must continue to build and refine the governance processes through which trustworthy AI will emerge and we must invest in the people who will build ethical and responsible AI. Those who work in compliance, privacy, security, risk management, legal, HR and governance together with data scientists, AI project managers, business analysts, AI product owners, model ops teams and others must be prepared to tackle the expanded equities at issue in AI governance.
Including any professionals tasked with developing AI governance and risk management in their operations, and anyone pursuing IAPP Artificial Intelligence Governance Professional (AIGP) certification.
28 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from £7600 online delivery, based on a group of 2 delegates, £2400 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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