AI use cases and applications
Course Summary
What you can now do
The story: Back to the hardware store owner. They now know what the power tool is used for, when a hand tool is better, which jobs need which attachment, what the tool does well and where it's dangerous, how to pick a model, and how to tell whether it paid off.
In AI/AWS terms: The course covered:
- Real-world AI applications and use cases across industries.
- When AI and ML are not appropriate: simple rules or computations will do.
- Supervised, unsupervised, and reinforcement learning use cases.
- Capabilities and challenges of generative AI.
- Factors for selecting a generative AI model.
- Business metrics for generative AI applications.
For the exam: Be ready to match a scenario to a learning technique, a challenge to its mitigation, and a use case to its business metric.