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Course Outline

Introduction

Overview of Artificial Intelligence (AI)

  • Machine learning systems.

Exploring Applications of AI

  • AI in the corporate context.

Understanding AI Technology

  • Concepts of underfitting and overfitting, classification, and regularization.
  • Multi-layer perception (MLP) and deep learning.
  • Convolutional and recurrent neural networks.

Assessing Strategic Approaches

  • Deciding between commissioning or procurement (build vs. buy).
  • AI maturity models for your organization.

Working with Data in Your Organization

  • Evaluating data readiness.
  • Word embeddings.
  • Training with artificial data.

Assessing AI Project Selection

  • Key criteria for selecting projects.

Managing an AI Project

  • Differences between machine learning and deep learning.
  • Project management aspects (lifecycle, timelines, methodology).
  • Operations, maintenance, and risk management.

Gathering Feedback

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

Summary and Next Steps

Requirements

  • No prerequisites required.

Audience

  • Business leaders.
  • Project managers.
 14 Hours

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