AI use cases and applications
Introduction
This course covers where AI, ML, and generative AI are used in practice, and how to choose and measure them.
What you should be able to do after this course
- Recognize real-world AI applications and the business needs they address.
- Tell when AI and ML are not the right solution.
- Match use cases to supervised, unsupervised, and reinforcement learning.
- Name the capabilities and challenges of generative AI.
- Choose a generative AI model using the right selection factors.
- Pick business metrics that show whether a generative AI application is working.
AI helps across industries such as manufacturing, healthcare, education, retail, life sciences, transportation, and media. Typical uses include summarization, code generation, content creation, chatbots, virtual assistants, anomaly detection, and contact center analytics.