Here are 7 free courses on AI recently released by Amazon.
In this course, you will learn the principles, techniques, and best practices for designing effective prompts.
This course introduces the basics of prompt engineering and progresses to advanced prompt techniques.
You will also learn how to guard against prompt misuse and how to mitigate bias when interacting with FMs.
𝐓𝐨𝐩𝐢𝐜𝐬:
With Amazon SageMaker Data Wrangler and Amazon SageMaker Autopilot, data and research analysts can prepare data, train, and deploy machine learning (ML) models with minimal coding.
You will learn to build ML models for tabular and time series data without deep knowledge of ML. You will also review the best practices for using SageMaker Data Wrangler and SageMaker Autopilot.
After completing this course, you will be able to build ML models to support proofs of concept (POCs). You will also be able to assist data scientists with potential ML model candidates to solve business problems.
𝐓𝐨𝐩𝐢𝐜𝐬:
This learning plan is designed to introduce generative AI to software developers interested in leveraging large language models without fine-tuning.
The digital training included in this learning plan will provide an overview of generative AI, planning a generative AI project, getting started with Amazon Bedrock, the foundations of prompt engineering, and the architecture patterns to build generative AI applications using Amazon Bedrock and Langchain.
𝐓𝐨𝐩𝐢𝐜𝐬:
This Learning Plan is designed to help Data Scientists and Developers integrate machine learning (ML) and artificial intelligence (AI) into tools and applications.
The digital training included in this Learning Plan will expose you to the broadest and deepest set of machine learning services and supporting cloud infrastructure.
This Learning Plan can also help prepare you for the AWS Certified Machine Learning – Specialty certification exam.
𝐓𝐨𝐩𝐢𝐜𝐬:
Amazon SageMaker helps data scientists prepare, build, train, deploy, and monitor machine learning (ML) models.
SageMaker brings together a broad set of capabilities, including access to distributed training libraries, open source models, and foundation models (FMs).
This course introduces experienced data scientists to the challenges of building language models and the different storage, ingestion, and training options to process a large text corpus.
The course also discusses the challenges of deploying large models and customizing foundational models for generative artificial intelligence (generative AI) tasks using Amazon SageMaker Jumpstart.
𝐓𝐨𝐩𝐢𝐜𝐬:
Amazon Transcribe is a fully managed artificial intelligence (AI) service that helps you convert speech to text using automatic speech recognition (ASR) technology.
In this Getting Started course, you will learn about the benefits, features, typical use cases, technical concepts, and costs of Amazon Transcribe.
You will review an architecture for a transcription solution using Amazon Transcribe that you can further adapt to your use case.
Through a guided tutorial consisting of narrated video, step-by-step instructions, and transcripts, you will also try real-time and batch transcription in your own Amazon Web Services (AWS) account.
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A Learning Plan pulls together training content for a particular role or solution, and organizes those assets from foundational to advanced. Use Learning Plans as a starting point to discover training that matters to you.
This learning plan is designed to introduce generative AI to the business and technical decision makers.
The digital training included in this learning plan will provide an overview of generative AI, and the approach to plan a generative AI project and to build a generative AI-ready organization.
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