课程: Advanced AI Analytics on AWS: Amazon Bedrock, Q, SageMaker Data Wrangler, and QuickSight

Course introduction and overview

课程: Advanced AI Analytics on AWS: Amazon Bedrock, Q, SageMaker Data Wrangler, and QuickSight

开始一个月试用 购买团队方案

Course introduction and overview

“

- Hi, my name is Noah Gift and I'm the founder of Pragmatic AI Labs. In this course, we cover analytics with AI on AWS, and it's a very exciting course, not because AI is magical, but because AI has an enhancement towards traditional analytics pipelines. A few of the things that we talk about include the foundational security models of AWS, some of the core services for AI, including Amazon Q, Amazon Bedrock, Data Wrangler, and also services like QuickSight that allows you to do ad hoc business intelligence. What we discover when we're doing things with AI is that it's really an enhancement of what's already there, so it's as good as what you already have. If you have existing processes that are good at deriving insights or you have strong methodologies and software engineering and you want to do profiling for costs, this is where AI comes into play and saves you time. One of the things that was covered in this exam that was really interesting is that we were able to build out a prototype that showed that we could save 10 times the cost. And after we were doing the benchmark, we took that benchmark data, threw it into the Bedrock ecosystem, and told it to build a visualization and describe exactly what we accomplished. So that's what I would describe as enhancement of something that is already doing a great job. So we already have software journey best practices. We already have analytics best practices, but the cherry on top of the Sunday is to take the new Gen AI tools and enhance what we already have. So that's really the lesson for this particular course, is that build a strong foundation, and with AI, you can take it to the next level.

内容