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Ever since ChatGPT was introduced in November 2022, technical terminology like large language model (LLM) and generative AI (GenAI) have entered the mainstream.
The AWS users had been incorporating GenAI technologies for several years before that. However, the commotion ChatGPT caused pushed Amazon to introduce some new GenAI services only a few months later.
For example, Amazon introduced several generative AI services in AWS in the first half of 2023. Specifically, Amazon Bedrock and Amazon CodeWhisperer.
Here’s an overview of some old and new GenAI tools in AWS.
AWS having so many GenAI tools requires some training to fully understand how they work. This especially applies to AmazonBedrock and Amazon CodeWhisperer, AWS’s newest tools.
To help you get started with these tools, I’ve selected several online courses.
1. Introducing Generative AI With AWS
Platform and link to the course: Udacity
Level: Beginner
Time to complete: 4 weeks
Price: $249 for a monthly subscription (assuming you can complete the course in 4 weeks)
Description: This course teaches you the evolution of AI and the fundamentals of AI, ML, and LLM. Then it goes on to show the real-world applications of GenAI, and, in the end, you’ll build a domain expert model with SageMaker. The skills you’ll gain include:
- GenAI fluency
- Basic supervised ML
- Prompt engineering
- Convolutional neural networks
The only prerequisite is Python basics.
2. Generative AI with Large Language Models
Platform and link to the course: Coursera
Level: Intermediate
Time to complete: 16 hours, 3 weeks at 5 hours/week
Price: $49
Description: In this course, you will first learn about GenAI use cases, project lifecycle, and model pre-training. In the second week, you will learn how to fine-tune and evaluate LLMs. The final week is all about reinforcement learning and LLM-powered applications.
For this course, you will need Python and ML basics, e.g., supervised & unsupervised learning, loss functions, and splitting data into training, validation, and test datasets.
3. Developing Generative AI Applications on AWS
Platform and link to the course: AWS Digital Classroom
Level: Expert
Time to complete: 2 days
Price: $449/year (access to the course with the annual subscription)
Description: This course will give you an overview of GenAI. You’ll learn how to plan GenAI projects, create prompts, and build AI applications using Amazon Bedrock and LangChain.
It’s recommended that you complete the AWS Technical Essentials course before this one and have intermediate-level Python.
4. Amazon Bedrock & AWS Generative AI – Beginner to Advanced
Platform and link to the course: Udemy
Level: Beginner to advanced
Time to complete: I didn’t find any information about duration, but the lectures are in total 11 hours.
Price: $17.99 at the time of writing; $54.99 is a full price
Description: For those who may find the course above difficult, this one is a good option to learn from the beginner to the advanced level about GenAI. The course starts with an overview of the basics of AI, ML, and neural networks, and also GenAI and foundation models (FM) concepts. After that, you’ll dive deep into Amazon Bedrock. This is followed by six use cases where you’ll get hands-on experience using AWS in the media and entertainment industry, text summarization, building a chatbot, HR Q&A, serverless e-learning app, and retail bank agent.
The following sections talk about the phases of a GenAI project. This is followed by one more example where you’ll learn how to generate code with CodeWhisperer. There are several sections that will teach you Python basics, AWS Lambda, and AWS API Gateway, in case you need that.
You don’t need any previous knowledge for this course.
5. Complete AWS Bedrock Generative AI Course + Projects
Platform and link to the course: Udemy
Level: Intermediate
Price: $17.99 at the time of writing; $94.99 is a full price
Time to complete: I didn’t find information about that, but the lectures are in total 3.5 hours.
Description: This course focuses even more on teaching you how to work in Amazon Bedrock. After learning the basics about AWS Bedrock, you will use it in several projects. These projects include code generation, summarizing meeting notes, using diffusion models for image creation, and evaluating LLM performance.
The course requires you to know basic Python.
6. Amazon Bedrock Masterclass: The Ultimate Generative AI Guide
Platform and link to the course: Udemy
Level: Intermediate
Price: $17.99 at the time of writing; $79.99 is a full price
Time to complete: There’s no information about that, but the lectures are in total 4 hours.
Description: This is another course that focuses on working with Bedrock. You’ll explore Bedrock’s capabilities, including working with Claude 3 Sonnet. The course will teach you how to work with Bedrock API (using Mistral) and how to build GenerativeAI applications with Bedrock.
To get the best from this course, you should know basic Python and have foundational understanding of AI and ML concepts.
7. Getting Started with Amazon CodeWhisperer
Platform and link to the course: Cloud Academy
Level: Beginner
Price: Free (7-day trial) or $39/month
Time to complete: 2.5 hours
Description: This course will introduce you to CodeWhisperer. You’ll learn how to improve IDE development using Amazon Q Developer and how to use CodeWhisperer for security scans, IaC support, customization, and command-line integration. Then, you’ll go to the practical section of the course, where you’ll apply your knowledge to working with AWS CodeWhisperer, Cloud9, and Lambda.
It’s recommended that you’re familiar with AWS Cloud9, AWS Lambda, Python, and JavaScript.
8. Amazon SageMaker Studio for Data Scientists
Platform and link to the course: Amazon
Level: Advanced
Price: $2,025
Time to complete: 3 days
Description: This course is provided by AWS experts. In three days, they will teach you how to set up and navigate Amazon SageMaker, use it for data processing, model development, deployment and inference, monitoring, and managing SageMaker’s resources and updates.
Prerequisites are a minimum of 1-year of experience in ML and deep learning fundamentals, i.e., ML frameworks, Python, building models, training, tuning, and deploying them. It’s recommended that all students take the AWS Technical Essentials course. Optionally, those less experienced should complete The Machine Learning Pipeline on AWS and Deep Learning on AWS courses.
Conclusion
These eight courses will give you a comprehensive knowledge of generative AI and how to use it in AWS. They are all relatively affordable courses, with the exception of the two Amazon’s I included. They are expensive, but worth it.
Many of these courses focus on the two latest GenAI tools in AWS: Bedrock and CodeWhisperer. You should, too, if you use the latest technology to your advantage.
Nate Rosidi is a data scientist and in product strategy. He’s also an adjunct professor teaching analytics, and is the founder of StrataScratch, a platform helping data scientists prepare for their interviews with real interview questions from top companies. Nate writes on the latest trends in the career market, gives interview advice, shares data science projects, and covers everything SQL.
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