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Course Outline
Introduction
Overview of Artificial Intelligence (AI)
- Machine learning systems.
Exploring AI Applications
- AI within a corporate context.
Understanding the Technology Behind AI
- Underfitting and overfitting, classification, and regularization.
- Multi-layer perception (MLP) and deep learning.
- Convolutional and recurrent neural networks.
Evaluating Strategic Approaches
- Commissioning or procurement (build vs. buy decision).
- AI maturity models for your organization.
Utilizing Data Within Your Organization
- Assessing data readiness.
- Word embeddings.
- Training with synthetic data.
Assessing AI Project Selection
- Key criteria for selecting projects.
Managing AI Projects
- Machine learning versus deep learning.
- Project management (lifecycle, timelines, and methodology).
- Operations, maintenance, and risk management.
Collecting Feedback
- Implementing feedback mechanisms (surveys, interviews, etc.).
- Identifying key stakeholders who will provide feedback.
- Analyzing the results.
Summary and Next Steps
Requirements
- No prior prerequisites are necessary.
Target Audience
- Business leaders.
- Project managers.
14 Hours
