AI and the Future of Work: Workflows and Modern Tools for Tech Leaders
1h 5mGeneral2024-01-12
Authors
Kristen Kehrer
Course details
“Putting machine learning into production" has a very different definition in 2023 than it did in 2013. The scope of what is possible to achieve with ML has increased significantly, and the associated challenges have grown proportionally. To effectively lead a data science team, you need to understand what you can feasibly expect them to achieve given the current state of ML, what challenges they will inevitably face, and how to navigate the modern ML ecosystem to provide them with support. In this course, instructor Kristen Kehrer teaches you all three. Learn how to streamline AI workflows with modern tools, manage AI projects and teams, collaborate with technical experts. Plus, develop future-proof leadership skills and keep abreast of the latest advancements, trends, and best practices.
Skills covered
Artificial Intelligence FoundationsLeadership SkillsArtificial Intelligence (AI)Leadership and ManagementOne-Off
Concepts
Introduction
- Welcome
- Why is this important
Streamlining AI Workflows with Modern Tools
- 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
Developing Future-Ready AI Skills
- 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
Conclusion
- Recap of key takeaways
- Actionable insights for implementing best practices