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Course Outline
Introduction
Foundations of Artificial Intelligence (AI)
- Machine learning architectures
Exploring AI Applications
- AI in the enterprise environment
Understanding AI Technologies
- Underfitting, overfitting, classification, and regularization
- Multi-layer perceptrons (MLP) and deep learning
- Convolutional and recurrent neural networks
Evaluating Strategic Approaches
- Build vs. buy: Commissioning and procurement strategies
- AI maturity models for your organization
Utilizing Organizational Data
- Assessing data readiness
- Word embeddings
- Training using synthetic data
Selecting AI Projects
- Key criteria for project selection
Managing AI Projects
- Machine learning versus deep learning
- Project management frameworks (lifecycle, timelines, methodologies)
- Operations, maintenance, and risk management
Collecting Feedback
- Implementing feedback mechanisms (surveys, interviews, etc.)
- Identifying key stakeholders for feedback
- Analyzing outcomes
Conclusion and Next Steps
Requirements
- No prior experience or prerequisites are necessary.
Target Audience
- Business leaders
- Project managers
14 Hours
