Course Summary

Mastering the generative AI application lifecycle is essential for organizations or individuals seeking to unlock the potential of cutting-edge AI capabilities. By understanding the full generative AI application lifecycle, from defining a use case to deployment, teams can build robust and trustworthy generative AI systems. You have completed the following learning objectives and are now equipped with the understanding necessary to develop generative AI solutions.

Learning objectives completed

• Identify selection criteria to choose pre-trained models.
• Define Retrieval Augmented Generation (RAG) and describe its business application.
• Explain the cost trade-offs of various approaches to foundation model customization.
• Understand the role of agents in multi-step tasks.
• Understand approaches to evaluate foundation model performance.
• Identify relevant metrics to assess foundation model performance.

For additional references and resources, move on to the next lesson.