Developing Generative Artificial Intelligence Solutions

via AWS Skill Builder

Overview

In this course, you will explore the generative artificial intelligence (generative AI) application lifecycle, which includes the following:

Defining a business use case
Selecting a foundation model (FM)
Improving the performance of an FM
Evaluating the performance of an FM
Deployment and its impact on business objectives

This course is a primer to generative AI courses, which dive deeper into concepts related to customizing an FM using prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning.

Course level: Fundamental
Duration: 1 hour

Activities

This course includes interactive elements, videos, text instruction, and illustrative graphics.

Course objectives

In this course, you will learn how to do the following:

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.

Intended audience

This course is intended for the following:

Individuals interested in machine learning and artificial intelligence, independent of a specific job role

Prerequisites

Developing Generative AI Solutions is part of a series that facilitates a foundation on artificial intelligence, machine learning, and generative AI. If you have not done so already, it is recommended that you complete these two courses: