Course Outline

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 Conclusion

Requirements

  • Familiarity with programming
  • Basic understanding of algorithms

Audience

  • Business leaders
  • Project managers
 7 Hours

Testimonials (5)

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