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Introduction

Overview of Artificial Intelligence (AI)

• Machine learning systems

Exploring Applications for AI

• AI in the corporate context

Learning About the Technology of AI

• Underfit and overfit, classification, and regularization
• Multi-layer perception (MLP) and deep learning
• Convolutional and recurrent neural networks

Assessing Strategic Approaches

• Commissioning or procurement (build or buy?)
• AI maturity models for your organization

Working With Data in Your Organization

• Data readiness evaluation
• Word embeddings
• Training with artificial data

Assessing AI Project Selection

• Key criteria for project selection

Managing an AI Project

• Machine learning versus deep learning
• Project management (lifecycle, timescales, methodology)
• Operations, maintenance, and risk management

Gathering Feedback

• Implementing feedback methods (surveys, interviews, etc.)
• Key stakeholders who will provide feedback
• Analyzing results

Summary and Next Steps