Google Gemini Models

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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