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AI+ Everyone
AI+ Everyone™ is a rapid introduction to artificial intelligence designed for all professionals with no technical background required. The course provides a clear, engaging overview of what AI is, how it works, where it is used, and the impact it is having on industries, jobs, and society.
Participants explore core AI concepts, real-world applications, emerging technologies such as generative AI, ethical considerations, and practical steps to begin adopting AI confidently and responsibly.
By the end of the programme, learners gain the foundational literacy needed to understand AI’s opportunities, challenges, and risks—and how to navigate an AI-driven future.
What You Will Learn
1. Introduction to Artificial Intelligence
Begin with a clear explanation of what AI is and what it is not. Topics include:
How intelligent machines are designed and used in everyday life
The differences between Narrow AI and General AI
Major milestones in AI development—from the Turing Test to neural networks
The rise, fall and resurgence of AI, including the “AI Winter”
Common myths and misconceptions about AI capabilities and limitations
This module builds a strong conceptual foundation and helps participants understand where AI is—and is not—changing the world.
2. AI Technologies Explained
A guided tour of the technologies that make modern AI possible, including:
Machine learning (supervised and unsupervised) with real-world examples
Neural networks and the basics of deep learning
CNNs, RNNs and Transformers—explained simply
Everyday uses of AI such as recommendation systems, speech recognition, and image analysis
The role of data and why it matters for accuracy and fairness
The module includes a hands-on interactive exercise using a simple AI tool (e.g., TensorFlow Playground) to let participants experiment with model behaviour.
3. AI in Action: Real-World Applications
Explore how AI is transforming industries through case studies, including:
Smart speakers and how voice recognition works
Self-driving cars and the ethics of autonomous decision-making
Healthcare applications such as diagnostics, personalised medicine and patient monitoring
Opportunities, limitations and future trends within each sector
This module helps demystify how AI systems are built and applied beyond consumer tools.
4. Understanding the AI Project Workflow
Gain a practical, non-technical overview of how AI projects are developed and deployed:
How organisations define problems appropriate for AI
How data is gathered, prepared and evaluated
Choosing and training a model
Integrating AI into existing processes and systems
Monitoring, maintaining and improving AI solutions over time
Case studies illustrating each stage of the workflow
This equips learners with the vocabulary and awareness needed to collaborate effectively in AI-enabled environments.
5. Ethics and the Social Implications of AI
Develop an understanding of the risks and responsibilities associated with AI, including:
Recognising and mitigating bias in AI systems
The impact of AI on privacy and data security
Responsible AI principles: transparency, accountability, fairness and ethical use
How AI affects jobs, society, and global challenges
Regulatory considerations and emerging standards for ethical AI
Participants learn how to evaluate AI solutions critically and responsibly.
6. Introduction to Generative AI
Discover how generative AI models work and where they are used, with topics including:
The difference between generative AI and traditional AI
GANs, VAEs and Transformer-based models explained simply
Real-world applications in art, music, writing, design and innovation
Human–AI collaboration in creative processes
Intellectual property, authorship and ethical concerns surrounding AI-generated content
This module gives participants a clear understanding of how tools like ChatGPT and image generators achieve their results.
7. Preparing for an AI-Driven Future
A forward-looking module exploring:
How AI will reshape industries and the employment landscape
Skills needed for the future, including digital literacy and critical thinking
Lifelong learning strategies to stay relevant
Real-world case studies of individuals and organisations adapting successfully
8. Getting Started with AI
The course concludes with practical guidance on how to begin adopting AI in your personal or organisational context:
Assessing AI readiness
Choosing the right types of AI projects
Forming effective AI teams and deciding whether to buy or build
Recommended resources, courses and communities for further learning
Grants and funding opportunities for AI innovation initiatives
Typical completion time
1 day / 8 hours
Self-paced online learning with videos, podcasts, practical lab activities and Q&A tutor chat.
Coaching option
Includes 2 × 45 minutes live coaching sessions with our AI Certs Certified Trainers to fully prepare student for the certification exam.
AI+ Everyone™ is a rapid introduction to artificial intelligence designed for all professionals with no technical background required. The course provides a clear, engaging overview of what AI is, how it works, where it is used, and the impact it is having on industries, jobs, and society.
Participants explore core AI concepts, real-world applications, emerging technologies such as generative AI, ethical considerations, and practical steps to begin adopting AI confidently and responsibly.
By the end of the programme, learners gain the foundational literacy needed to understand AI’s opportunities, challenges, and risks—and how to navigate an AI-driven future.
What You Will Learn
1. Introduction to Artificial Intelligence
Begin with a clear explanation of what AI is and what it is not. Topics include:
How intelligent machines are designed and used in everyday life
The differences between Narrow AI and General AI
Major milestones in AI development—from the Turing Test to neural networks
The rise, fall and resurgence of AI, including the “AI Winter”
Common myths and misconceptions about AI capabilities and limitations
This module builds a strong conceptual foundation and helps participants understand where AI is—and is not—changing the world.
2. AI Technologies Explained
A guided tour of the technologies that make modern AI possible, including:
Machine learning (supervised and unsupervised) with real-world examples
Neural networks and the basics of deep learning
CNNs, RNNs and Transformers—explained simply
Everyday uses of AI such as recommendation systems, speech recognition, and image analysis
The role of data and why it matters for accuracy and fairness
The module includes a hands-on interactive exercise using a simple AI tool (e.g., TensorFlow Playground) to let participants experiment with model behaviour.
3. AI in Action: Real-World Applications
Explore how AI is transforming industries through case studies, including:
Smart speakers and how voice recognition works
Self-driving cars and the ethics of autonomous decision-making
Healthcare applications such as diagnostics, personalised medicine and patient monitoring
Opportunities, limitations and future trends within each sector
This module helps demystify how AI systems are built and applied beyond consumer tools.
4. Understanding the AI Project Workflow
Gain a practical, non-technical overview of how AI projects are developed and deployed:
How organisations define problems appropriate for AI
How data is gathered, prepared and evaluated
Choosing and training a model
Integrating AI into existing processes and systems
Monitoring, maintaining and improving AI solutions over time
Case studies illustrating each stage of the workflow
This equips learners with the vocabulary and awareness needed to collaborate effectively in AI-enabled environments.
5. Ethics and the Social Implications of AI
Develop an understanding of the risks and responsibilities associated with AI, including:
Recognising and mitigating bias in AI systems
The impact of AI on privacy and data security
Responsible AI principles: transparency, accountability, fairness and ethical use
How AI affects jobs, society, and global challenges
Regulatory considerations and emerging standards for ethical AI
Participants learn how to evaluate AI solutions critically and responsibly.
6. Introduction to Generative AI
Discover how generative AI models work and where they are used, with topics including:
The difference between generative AI and traditional AI
GANs, VAEs and Transformer-based models explained simply
Real-world applications in art, music, writing, design and innovation
Human–AI collaboration in creative processes
Intellectual property, authorship and ethical concerns surrounding AI-generated content
This module gives participants a clear understanding of how tools like ChatGPT and image generators achieve their results.
7. Preparing for an AI-Driven Future
A forward-looking module exploring:
How AI will reshape industries and the employment landscape
Skills needed for the future, including digital literacy and critical thinking
Lifelong learning strategies to stay relevant
Real-world case studies of individuals and organisations adapting successfully
8. Getting Started with AI
The course concludes with practical guidance on how to begin adopting AI in your personal or organisational context:
Assessing AI readiness
Choosing the right types of AI projects
Forming effective AI teams and deciding whether to buy or build
Recommended resources, courses and communities for further learning
Grants and funding opportunities for AI innovation initiatives
Typical completion time
1 day / 8 hours
Self-paced online learning with videos, podcasts, practical lab activities and Q&A tutor chat.
Coaching option
Includes 2 × 45 minutes live coaching sessions with our AI Certs Certified Trainers to fully prepare student for the certification exam.