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Starts 9 July 2025 07:59
Ends 9 July 2025

Developing Generative Artificial Intelligence Solutions
479 Courses
Not Specified
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All Levels
Progress at your own speed
Free
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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:
- Fundamentals of Machine Learning and Artificial Intelligence
- Exploring Artificial Intelligence Use Cases and Applications
Course outline
Section 1
- Lesson 1:
How to Use This Course
Section 2:
Introduction
- Lesson 2:
Course Overview
- Lesson 3:
Generative AI Application Lifecycle
Section 3:
Defining the Use Case
- Lesson 4:
Defining a Use Case
Section 4:
Selecting a Foundation Model
- Lesson 5:
Selecting an FM
- Lesson 6:
Knowledge Check
Section 5:
Improving Performance
- Lesson 7:
Improving the Performance of an FM
- Lesson 8:
Knowledge Check
Section 6:
Evaluating Results
- Lesson 9:
Evaluating an FM
- Lesson 10:
Knowledge Check
Section 7:
Deployment
- Lesson 11:
Deploying the Application
Section 8:
Conclusion
- Lesson 12:
Course Summary
- Lesson 13:
Resources
- Lesson 14:
Contact Us
University:
AWS Skill Builder