AWS Automation: AWS Machine Learning Tutorial Online Training

Machine learning is a game-changing technology that fundamentally transforms the way we process and analyze data. With machine learning, organizations and teams can uncover deeper insights, make better predictions and automate decision-making processes – all faster than ever before. But honestly, the thing that makes learning machine learning worth it is that it's really, really cool. Facial detection, text extraction, voiceover integration? It's all incredible and worth it just for curiosity's sake, much less all the business value and career opportunities.

It doesn't take very long to learn the basics of how AWS machine learning tools work – you could finish this tutorial in one day. But this course introduces AWS machine learning tools like Amazon Rekognition, Amazon Transcribe and Amazon Polly. It's what you take away from this course about ML tools and the AWS cloud that will help you go on and integrate Amazon's other AI/ML services into your portfolio – tools like SageMaker JumpStart or Bedrock.

Although it's not intended as a complete certification prep, this machine learning tutorial can help you start preparing for the AWS Certified Machine Learning Specialty certification, which validates expertise with building, training, tuning and deploying machine learning models on AWS. The ML Specialty cert costs $300 and has no prerequisites; it's meant for professionals with at least two years of hands-on experience with ML and deep learning workloads.

Yes, the AWS Certified Machine Learning Specialty is good for three years. All AWS certifications are valid for three years from the date they're earned. If you want to maintain an active status on your AWS certification, you'll need to retake the exam for the cert within that three window. AWS doesn't currently accept any other continuing education credit or certification from external providers for recertification.

Learning AWS machine learning tools should start on a foundation of familiarity with cloud computing and the AWS cloud specifically. From there, a video-based course like this one can help expose you to the basic operation of AWS machine learning tools. But really learning the tools and services themselves takes hands-on practice and experience, which you can get in virtual simulations or practice environments.