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Understanding the Technology Behind ChatGPT and Similar Systems

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Understanding Artificial Intelligence Ecosystems and Technologies
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
Questions & Assistance

If you have any question or need any help with the course, please write your course instructor:
David Gonzalez
david.gonzalez@idhus.org

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“You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.”

– R. Buckminster Fuller