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
Keywords
- Gen AI
- Generative AI
