AWS AI Practitioner: Design Factors for Applications Using Foundation Models

Skillsoft issued completion badges are earned based on viewing the percentage required or receiving a passing score when assessment is required. An AI foundation model is a large-scale ML model trained on huge volumes of data that can perform a wide range of tasks. These models can be fine-tuned for specific applications with minimal additional training. In this course, explore design considerations for applications using foundation models at AWS, including identifying selection criteria for pre-trained models and the effect of inference parameters on model responses. Next, learn about Retrieval-Augmented Generation (RAG) and its business applications and AWS services for storing embeddings within vector databases. Finally, examine the cost tradeoffs of various approaches to foundation model customization and the role of agents in multi-step tasks. This course is part of a collection that prepares you for the AIF-C01: AWS Certified AI Practitioner exam.