| Introduction | - |
| Unit 1 |
Introduction |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |