November 18, 2021

I’ve been working on the AWS Certified Machine Learning – Specialty off and on for about a month or so.

In September, I passed the AWS Certified Cloud Practitioner certification, with the plan of moving right from that into the machine learning certification.

Next is the AWS ML ecosystem. I’ve used AWS at a very high level for a few years, but not with any types of ML workflows or tools.

  • Some of the concepts from the Cloud Practitioner were familiar, but it was good to better understand how I could start leveraging some of the data analysis tasks I do on my computer into the cloud.
  • I don’t necessarily do enough where I need the cloud architecture from a performance perspective, but I think it opens up a lot of possibilities in my workflow.
  • I have done a few machine learning courses online over the years. But I wanted to start to learn how I could do it with the AWS tools – which is probably how I would use it professionally if I were to start having to leverage machine within my day-to-day workflow (currently I don’t have to, but there are a lot of initiatives at my company that are shifting in that direction).

What I’ve done so far and what I’m doing next

  • I’ve completed most of Amazon’s Exam Readiness: AWS Certified Machine Learning – Specialty course to get a high-level overview of what I’ll be working with.
  • Then my plan is to follow with Amazon’s Machine Learning Learning Plan – that is, starting to actually put those tools into action. Then I’ll plan on taking the exam.
  • In the meanwhile I’ll be sharing some of my progress and maybe some of my workbooks that I’ll be putting together as I go through the process.