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Duration 14 hours
Course Outline
Introduction
Fundamentals of Artificial Intelligence (AI)
- Machine learning frameworks
Exploring Practical AI Applications
- Implementing AI in a corporate environment
Understanding AI Technology
- Concepts of underfitting, overfitting, classification, and regularization
- Multi-layer perceptrons (MLP) and deep learning architectures
- Convolutional and recurrent neural networks
Evaluating Strategic Methodologies
- Decisions on commissioning or procurement (build vs. buy)
- AI maturity models applicable to your organization
Leveraging Organizational Data
- Assessing data readiness
- Word embedding techniques
- Utilizing synthetic data for training
Criteria for AI Project Selection
- Essential factors in choosing AI projects
Overseeing AI Projects
- Distinctions between machine learning and deep learning
- Project management essentials (lifecycle, timelines, methodologies)
- Operational maintenance and risk mitigation strategies
Collecting and Integrating Feedback
- Deploying feedback mechanisms (surveys, interviews, etc.)
- Identifying key stakeholders for feedback input
- Interpreting and analyzing feedback results
Conclusion and Path Forward
Requirements
- No prior experience or prerequisites are necessary.
Target Audience
- Executive business leaders
- Project managers
