Generative AI for Cloud Practitioners
Published by Pearson
Learn how to implement generative AI solutions in the cloud
- Get an objective examination of generative AI and how it relates to your work as a cloud practitioner
- Explore real-world use cases as well as anti-patterns
- Understand how various AI products can be installed locally, on a virtual machine, in a container, or as a managed service
- Follow hands-on demos highlighting how to use AI as standalone tools or as part of an application infrastructure
Generative AI is rapidly changing the role of a cloud practitioner. The evolving group of technologies can be very challenging to keep track of and knowing when and how to use these technologies – not to mention how they are appropriate for a workload - can seem daunting.
Generative AI for Cloud Practitioners is built to give you the context you need to start incorporating AI into your work. Best-selling author and trainer Chad Smith will discuss generative AI in the context of application workloads and as tools to be used by developers, DevOps professionals, data analysts, and others. He will also dig into the tradeoffs you need to consider when deploying AI solutions directly on infrastructure resources or in a cloud environment. Throughout the course, Chad will use real-world scenarios and requirements so you can see how to apply what you learn to your own work.
What you’ll learn and how you can apply it
- Introductory concepts of generative AI, including Large Language Models (LLMs), Foundation Models, and Retrieval-Augmented Generation (RAG), so you can install and configure software locally, as containers, or using managed services.
- An understanding of the maturity of LLMs, Foundation Model, and RAGs so you can determine which of these can be used legitimately in current environments.
- How to identify the appropriate generative AI infrastructure so you can better attend to cost and performance requirements
This live event is for you because...
- You are a technology professional who wants to keep your skills relevant in a dynamic job environment
- You want to learn how to apply generative AI concepts to cloud technologies
Prerequisites
- Basic understanding of virtual machines and containers
- Entry-level knowledge of programming languages such as JavaScript or Python
Course Set-up
Recommended Preparation
- Watch: Cloud Essentials by Chad Smith: https://learning.oreilly.com/course/cloud-essentials/9780138297640/
- Watch: Google Cloud Essentials by Dan Sullivan: https://learning.oreilly.com/course/google-cloud-essentials/9780138174255/
Recommended Follow-up
- Listen: AI Unveiled by Sinan Ozdemir
- Read: Quick Start Guide to Large Language Models by Sinan Ozdemir
- Attend: Hands-on AWS Operations with ChatGPT by Chad Smith
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Generative AI Introduction (20 mins)
Foundation Models (60 mins)
- Foundation Model Architecture
- Foundation Model Tradeoffs
- Demo: Foundation Model Download and Prompt (local)
- Demo: Foundation Model Service (Python/Amazon Bedrock)
- Q&A
Break (10 mins)
Large Language Models (LLMs) (60 mins)
- LLM Architecture
- LLM Tradeoffs
- Demo: AWS Codewhisperer (local)
- Demo: Bert Chat (local using GPT4All)
- Demo: Image Generation (JavaScript/Amazon EC2/Amazon Titan)
- Q&A
Break (10 mins)
Retrieval-Augmented Generation (RAG) (60 mins)
- RAG Architecture
- RAG Tradeoffs
- Demo: RAG (local using GPT4All)
- Demo: RAG (JupyterHub Docker container/Amazon Titan)
- Q&A
Q&A (10 mins)
Course Wrap-up (10 mins)
Your Instructor
Chad Smith
Chad Smith is a technology professional, author and trainer focused on cloud infrastructure and management. He is the Principal Cloud Architect at Brightkey.cloud and has a wealth of personal real-world experience in cloud adoption, infrastructure design, operations and security. Chad holds current AWS certifications in Architecture, SysOps, Security, Networking and Databases and is also certified in CompTIA Cloud+.