My experience grew in the area of designing ML-based systems from experimenting with ideas to publishing working systems, but I wanted to become the kind of engineer who works on powerful scalable platforms like AWS, and from this point I focused to deep dive into AWS services especially those cooperating with machine learning system lifecycle.
While I was doing my research I encountered a scholarship program offered by MCIT in Egypt, that aims to train 500 software engineers on AWS Certified Machine Learning Specialty to be certified specialists. I applied for it and after some selection phases I got the opportunity to be a Certified AWS ML Specialist and the challenge spark was ignited.
AWS offers many types of certificates for all career levels as families and one of this them is the "specialty" family which is my machine learning specialty certificate belongs to, and its goal is below according to the AWS certification website:
"The AWS Certified Machine Learning - Specialty certification is intended for individuals who perform a development or data science role. It validates a candidate's ability to design, implement, deploy, and maintain machine learning (ML) solutions for given business problems."
The exam certificate is valid for 3 years and to pass it must pass 75% of the exam 65 questions, which cover many areas in cloud architecture patterns, development, and services distributed across these domains:
This type of exam is different because it depends on many aspects represented in the chart below, and without one of them you will have to put in more effort to fill this gap.
ML Concepts is the science behind models or basic statistical approaches which are required to be aware of before doing the exam.
ML Experience is a hand-held experience in building systems and solving problems related to the machine learning life cycle.
AWS Experience is the experience that comes from working with AWS services whether there are ML-related services or general services that work in various domains, this type of experience will help a lot in moving the mindset towards cloud and AWS especially.
- Exam Readiness AWS Certified Machine Learning - Specialty
- "AWS Certified Machine Learning Specialty 2021 - Hands On!" by Frank Kane on Udemy (they promote a lot of discounts btw).
- AWS ML services mind map by Julien Simon.
- Exam topics dump questions.
- AWS documentations.
- "Amazon SageMaker Technical Deep Dive Series" by Emily Webber on YouTube.
- "AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide" Book By Somanath Nanda , Weslley Moura.
- Step #1: Study the AWS Exam Readiness by watching every domain video and doing the related quiz, then solve the "Additional Study Questions" module which is around 40 questions covers all domains, and gets an initial view on weak spots, I recommend keeping this score as a baseline score.
- Step #2: Watching the Udemy course, taking notes, and doing practice labs will give you experience with concepts and become more familiar with AWS services.
- Step #3: Reviewing the mind map helped a lot in connecting points together, organizing your memory, and answering some questions I had from the previous steps.
- Step #4 & #5 : Solving the dump questions was a very important step (a lot of exam questions are very similar to these types of questions), but the power of exam topics questions not in question itself but in the discussions under it, they have a lot of references to AWS documentation and answer points of view, reading these links will open your mind towards areas not viewed before, and knowing how others answer the questions will help you in defining keywords in the question that makes the difference in selecting the right answer. You can answer these questions multiple times but avoid memorizing them, but instead justifying the answer you selected.
- Step #6: Watching Sage Maker Deep Dive Series helps me to focus on the sage maker as a platform and what, when, and how to use its services, which is an important part of my exam preparation. But I'm not dedicated to it but just watching one or two videos besides going into Step #7.
- Step #7: Reading the AWS MLS Guide Book, has been a great experience because it's designed to be a summary with GitHub code snippets and questions after every chapter, which is to revise your concepts and make sure you are now familiar with every topic in it, without going into too many details. I highly recommend taking notes that would be great for revision on the day before an exam.
- Step #8 (optional): resolve the "Additional Study Questions" module in the exam readiness again, and compare it with the baseline score you get in Step #1. My score jumps from 60% to 94% and was an amazing feeling gives me more confidence in my skills.
I registered for my exam after preparing the studying plan and estimated time I need to be ready for the exam, or I thought I will be ready but actually being ready 100% is just a dream and if I tried to follow the ready state will reschedule the exam date one or two times, so my tip is preparing plan, estimating time, adapt with current deadline.
The day before the exam I used a summary for the points and modules I would need to review on the fly, like important formulas, and mind maps, because it would take a lot of time to revise every single point in the content.
I registered for my exam at the Global Knowledge testing center which is a certified center for Pearson VUE, that I preferred over an online one, and to avoid taking the risk of a dropped connection or other unexpected issues plus the pre-exam setup headache. The experience was great and exactly as I expected in the "What to expect when testing with Pearson VUE?" video. But for me the hardest thing I faced was sitting for 3 hours continuously, while I wasn't used to it.
Besides the value of the certificate, promoting career, and opening new job positions, AWS offers other great benefits such as:
Supporting for next challenge by having free practice exam voucher as well as a 50% discount on the next exam valid for next 3 years.
Engaging with the AWS Certified Community on LinkedIn, which helps in making new connections, interacting with peers, and learning from others who have validated their technical skills with AWS certifications.
Becoming a Subject Matter Expert by applying to the AWS SME program to help in deciding exam topics, developing questions, and determining passing scores.
So being certified with AWS, not just an exam and a certificate but it's a package and the relationship that started and will continue for a long time.
This journey was amazing and the experience and the value I got opened my horizons even more. I hope you've enjoyed reading this post and maybe even feel inspired to get AWS certified yourself (let me know if you are). It's not too late to make this one of your goals of the year!