Learn how to implement machine learning operations into your business, discover the scope of what ML can achieve—and the challenges that it can present.
AI and the Future of Work: Workflows and Modern Tools for Tech Leaders
Overview
Syllabus
Introduction
- Welcome
- Why is this important?
- Data versioning and management
- Experiment tracking and management
- Model monitoring and performance evaluation
- AutoML
- Automated pipelines
- Explainability and interpretability of models
- Model deployment and serving
- Tools for working with LLMs
- Assessing and upskilling existing teams
- Navigating the hybrid skill set landscape
- Creating an environment for experimentation
- Emerging trends in how you build AI
- Challenges and opportunities for organizations
- Recap of key takeaways
- Actionable insights for implementing best practices
Taught by
Kristen Kehrer
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