Understanding the Main Categories of AI

You cannot view this unit as you're not logged in yet.

Module 1

Introduction

Unit 1

Introduction

Module 2

The Evolution of Artificial Intelligence

Unit 1

Understanding the Historical Development of AI

Unit 2

The Origins of Artificial Intelligence

Unit 3

Symbolic AI and Expert Systems

Unit 4

The AI Winters and Periods of Stagnation

Unit 5

The Rise of Machine Learning

Unit 6

Deep Learning and the Modern AI Revolution

Unit 7

The Emergence of Generative AI

Unit 8

Current Trends and Future Directions

Unit 9

Module summary

Module 3

The AI Technology Landscape

Unit 1

Understanding the Main Categories of AI

Unit 2

Rule-Based Systems

Unit 3

Machine Learning Systems

Unit 4

Deep Learning Systems

Unit 5

Generative AI

Unit 6

Reinforcement Learning

Unit 7

Multi-Agent Systems

Unit 8

Robotics and Embodied AI

Unit 9

Hybrid AI Systems

Unit 10

Module Summary

Module 4

Machine Learning Fundamentals

Unit 1

How Machines Learn

Unit 2

Supervised Learning

Unit 3

Unsupervised Learning

Unit 4

Semi-Supervised Learning

Unit 5

Reinforcement Learning

Unit 6

Training, Validation and Testing

Unit 7

Datasets and Data Quality

Unit 8

Model Performance and Evaluation

Unit 9

Module Summary

Module 5

Deep Learning and Neural Networks

Unit 1

The Foundations of Modern AI

Unit 2

Artificial Neural Networks

Unit 3

Deep Neural Networks

Unit 4

Computer Vision Systems

Unit 5

Speech Recognition Technologies

Unit 6

Pattern Recognition Capabilities

Unit 7

Strengths and Limitations of Deep Learning

Unit 8

Computational Requirements

Unit 9

Module Summary

Module 6

Generative AI and Large Language Models

Unit 1

Understanding the Technology Behind ChatGPT and Similar Systems

Unit 2

What is Generative AI?

Unit 3

Foundation Models

Unit 4

Large Language Models (LLMs)

Unit 5

Transformers and Attention Mechanisms

Unit 6

Prompting and Context Windows

Unit 7

Fine-Tuning and Customisation

Unit 8

Multimodal AI Systems

Unit 9

Current Limitations and Challenges

Unit 10

Module Summary

Module 7

AI Agents and Autonomous Systems

Unit 1

The Next Evolution of Artificial Intelligence

Unit 2

What are AI Agents?

Unit 3

Agentic AI Architectures

Unit 4

Goal-Oriented Autonomous Systems

Unit 5

Planning and Reasoning Capabilities

Unit 6

Multi-Agent Collaboration

Unit 7

Human-AI Workflows

Unit 8

Agent Ecosystems and Orchestration

Unit 9

Future Implications for Public Administration

Unit 10

Module Summary

Module 8

Computer Vision, Speech and Multimodal AI

Unit 1

AI Beyond Text

Unit 2

Image Recognition Systems

Unit 3

Object Detection Technologies

Unit 4

Facial Recognition Capabilities

Unit 5

Video Analysis

Unit 6

Speech Recognition and Transcription

Unit 7

Speech Synthesis and Voice Generation

Unit 8

Multimodal AI Models

Unit 9

Public Sector Applications

Unit 10

Module Summary

Module 9

Robotics and Physical AI

Unit 1

AI in the Physical World

Unit 2

Industrial Robotics

Unit 3

Service Robots

Unit 4

Autonomous Vehicles

Unit 5

Drones and Autonomous Systems

Unit 6

Physical AI Architectures

Unit 7

Human-Robot Interaction

Unit 8

Smart Infrastructure and Robotics

Unit 9

Future Public Sector Applications

Unit 10

Module Summary

Module 10

Foundation Models and AI Platforms

Unit 1

Understanding the New AI Infrastructure

Unit 2

Foundation Models Explained

Unit 3

Open-Source vs Proprietary Models

Unit 4

Model Ecosystems

Unit 5

AI-as-a-Service Platforms

Unit 6

Cloud AI Infrastructures

Unit 7

Sovereign AI Initiatives

Unit 8

European AI Ecosystems

Unit 9

Strategic Implications for Institutions

Unit 10

Module Summary

Module 11

Comparing Major AI Models and Providers

Unit 1

Navigating the AI Marketplace

Unit 2

OpenAI Models

Unit 3

Anthropic Models

Unit 4

Google Gemini Models

Unit 5

Meta Llama Models

Unit 6

Mistral AI Models

Unit 7

European AI Initiatives

Unit 8

Strengths, Weaknesses and Use Cases

Unit 9

Choosing the Right Model for Organisational Needs

Unit 10

Module Summary

Module 12

Emerging AI Technologies

Unit 1

What Comes After Generative AI?

Unit 2

Reasoning Models

Unit 3

World Models

Unit 4

Scientific AI

Unit 5

AI for Discovery and Innovation

Unit 6

AI for Simulation and Forecasting

Unit 7

Embodied Intelligence

Unit 8

Autonomous Research Systems

Unit 9

Artificial General Intelligence (AGI) Debates

Unit 10

Module Summary

Module 13

Understanding AI Limitations

Unit 1

What AI Cannot Yet Do

Unit 2

Hallucinations and Reliability Challenges

Unit 3

Context Limitations

Unit 4

Causality Versus Correlation

Unit 5

Lack of True Understanding

Unit 6

Bias and Fairness Issues

Unit 7

Security Vulnerabilities

Unit 8

Dependence on Data Quality

Unit 9

Human Oversight Requirements

Unit 10

Module Summary

Module 14

Building an AI Strategy for Public Institutions

Unit 1

From Technology Awareness to Strategic Adoption

Unit 2

Understanding Organisational AI Maturity

Unit 3

Identifying AI Opportunities

Unit 4

Build vs Buy Decisions

Unit 5

Selecting AI Technologies

Unit 6

Governance Considerations

Unit 7

Workforce Implications

Unit 8

Capability Development

Unit 9

Future-Proofing Public Institutions

Unit 10

Module Summary

Module 15

The Future AI Landscape

Unit 1

Scenarios for the Next Decade

Unit 2

AI and the Future of Work

Unit 3

AI and Public Administration

Unit 4

AI and Democratic Governance

Unit 5

Regulatory Evolution

Unit 6

European AI Sovereignty

Unit 7

Future Technological Trajectories

Unit 8

Strategic Implications for Public Leaders

Unit 9

Module Summary

Module 16

The Rise of Open-Source AI

Unit 1

Understanding Open AI Ecosystems

Unit 2

The Philosophy of Open-Source AI

Unit 3

Open Models Versus Proprietary Models

Unit 4

Benefits of Open Ecosystems

Unit 5

Transparency and Auditability

Unit 6

Innovation Through Community Collaboration

Unit 7

Challenges and Risks of Open Models

Unit 8

The Future of Open Source AI Development

Unit 9

Module Summary

Module 17

Major Open-Source AI Models

Unit 1

Exploring the Leading Open AI Platforms

Unit 2

Meta Llama Ecosystem

Unit 3

Mistral AI and European Open Models

Unit 4

DeepSeek Open Models

Unit 5

Qwen Open Models

Unit 6

BLOOM and BigScience

Unit 7

Open-Source Multimodal Systems

Unit 8

Comparative Strengths and Limitations

Unit 9

Module Summary

Module 18

China AI Strategy and Ecosystem

Unit 1

Artificial Intelligence as a National Strategic Priority

Unit 2

China's National AI Development Strategy

Unit 3

Government Support and Industrial Policy

Unit 4

AI as a Geopolitical Capability

Unit 5

The Chinese AI Innovation Ecosystem

Unit 6

Digital Infrastructure and AI Investment

Unit 7

AI and Technological Sovereignty

Unit 8

Strategic Competition and Cooperation

Unit 9

Module Summary

Module 19

Leading Chinese AI Models

Unit 1

Understanding China's AI Champions

Unit 2

DeepSeek Models

Unit 3

Alibaba Qwen Models

Unit 4

Baidu ERNIE Models

Unit 5

Tencent Hunyuan Models

Unit 6

Moonshot AI (Kimi)

Unit 7

Zhipu AI (GLM Models)

Unit 8

ByteDance AI Initiatives

Unit 9

Comparative Performance and Positioning

Unit 10

Module Summary

Module 20

AI Ecosystems Beyond China

Unit 1

Emerging Asian AI Innovation Hubs

Unit 2

Japan's AI Ecosystem

Unit 3

South Korea's AI Initiatives

Unit 4

Singapore as an AI Innovation Centre

Unit 5

India's AI Strategy and Development

Unit 6

Taiwan and Semiconductor Leadership

Unit 7

Regional Collaboration Initiatives

Unit 8

Future Asian AI Trajectories

Unit 9

Module Summary

Module 21

Open-Source AI and Digital Sovereignty

Unit 1

Strategic Independence in the AI Era

Unit 2

Why Sovereign AI Matters

Unit 3

Open-Source Models as Sovereignty Tools

Unit 4

Data Sovereignty Considerations

Unit 5

Public Sector Deployment Models

Unit 6

Local Hosting Versus Cloud Dependence

Unit 7

Strategic Resilience and Redundancy

Unit 8

Building National and Regional AI Capabilities

Unit 9

Module Summary

Module 22

Security, Governance and Risk Considerations

Unit 1

Evaluating Open and Global AI Systems

Unit 2

Security Implications of Open Models

Unit 3

Supply Chain Risks

Unit 4

Trust and Verification Challenges

Unit 5

Model Provenance and Transparency

Unit 6

Compliance with European Regulations

Unit 7

Risk Assessment Frameworks

Unit 8

Governance Requirements

Unit 9

Module Summary

Module 23

Strategic Choices for Public Institutions

Unit 1

Selecting AI Ecosystems for Long-Term Success

Unit 2

Open Versus Proprietary Strategies

Unit 3

Multi-Model Architectures

Unit 4

Vendor Diversification

Unit 5

Balancing Innovation and Control

Unit 6

Cost and Infrastructure Considerations

Unit 7

Sovereignty and Procurement Decisions

Unit 8

Designing Resilient AI Ecosystems

Unit 9

Module Summary

Module 24

Conclusion

Unit 1

End of Programme