How I prepared for AWS ML Specialty in 20 Hours and Cracked It
It is easy to get certified if you really want to
I am a great fan of how Tesla is executing the problem of gathering data from the fleet of cars to train their net in efforts to build FSD, hence the image.
Although Amazon recommends 1–2 years of experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud, before sitting for the exam. But, with the right mindset for preparation, anyone can ace the exam in much less time.
Do you really like ML?
If you don’t like Machine Learning, this story is not for you. But if you are new to ML and interested to learn, it will be useful.
I believe it becomes easy to learn a tool or concept when you really know the purpose of its existence or the impact of its existence. Knowing the purpose makes it clear and simple for you to map while you learn.
If ML is entirely new to you? Go, do your homework on:
- What is Machine Learning?
- What is a Distribution?
- What is a Model?
- Layman's understanding of steps to build an ML model?
- What was the bottleneck for ML Systems before Cloud?
