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Course Outline

Introduction

General Overview of Artificial Intelligence (AI)

  • Machine learning systems

Examination of AI Applications

  • AI in the corporate environment

Understanding AI Technology Fundamentals

  • Underfitting, overfitting, classification, and regularization
  • Multi-layer perceptron (MLP) and deep learning
  • Convolutional and recurrent neural networks

Evaluation of Strategic Approaches

  • Acquisition or development (build or buy) considerations
  • AI maturity models for the organization

Data Management Within the Organization

  • Data readiness assessment
  • Word embeddings
  • Training with synthetic data

Evaluation of AI Project Selection

  • Key criteria for project selection

AI Project Administration

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

Collection of Feedback

  • Implementation of feedback mechanisms (surveys, interviews, etc.)
  • Key stakeholders providing feedback
  • Analysis of outcomes

Summary and Future Actions

Requirements

  • No prerequisites required

Intended Audience

  • Business leaders
  • Project managers
 7 Hours

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