The AWS Certified Machine Learning Consultant

Machine Learning

If you are thinking about hiring or becoming a machine learning consultant understanding the AWS Machine Learning Speciality certificate is the perfect start.

Hiring managers should get an overview of what they can expect from a certified consultant. Consultant should get an understanding of what they should know to pass the exam. Let’s start!

AWS Machine Learning and AI services

The number of services and functions that AWS provides is unparalleled in the current cloud landscape. Presenting every aspect in detail was already done by Amazon. My goal is to provide a short summary of every exam relevant services and references for deep dive. My hope is that you would find it helpful to get a holistic view on the platform.

Using a series of blog posts I will cover all four domains of the AWS Machine Learning Speciality (MLS-C01) exam. I have structured the content into eight separate posts. These posts can be consumed as a stand-alone material. If you are not preparing for the MLS-C01 exam you may still find the topics interesting:

AWS Machine Learning Speciality Introduction

If you know the difference between recall and precision, AWS Batch and Glue or AWS Lex and AWS Polly then read on!

I have recently passed the AWS Machine Learning Speciality (MLS-C01) exam. In these posts I would like to share my experience and preparation notes. Understanding all these content benefits you and me the first and any subsequent times you want to pass the exam after the three years expiration time.

You may use this as a starting point to collect the domains where you need further knowledge. It also worth having a look just a night before the exam to check if you’ve learned all topics and to cache my exam tips 😉 In general the exam is one of the more expensive ones, it currently costs 300 USD. This is a lot of money to give it away hastily, even for a good earning machine learning consultant. I would suggest to give at least two months of purely exam preparation time, given that you are familiar with Machine Learning and AWS. I strongly advise you to take the official practice exam as well, it costs only 40 USD and it gives you good feedback on your progress.

Tip: pass a cheaper exam, like Solutions Architect – Associate for 150 USD and use the 50% discount awarded for the Machine Learning Speciality. You will have two certificates for the same money. If you do not pass the Solution Architect, it’s probably too early for the Machine Learning exam and you ‚only‘ lost 150 USD not 300 USD.

Bonus: you will get a free practice exam after a successful certification, you can use it to avoid paying the 40 USD.

During this time of Corona it’s very convenient to prepare and take the exam online. You can find the official website here and you can sign up for an AWS Certificate account here. You will be using your amazon.com account not your AWS. The reason for this is: AWS accounts are more technical in a sense of being related to a company or a specific project. You may lose access to them at some point. On the other hand amazon.com account represents you permanently.

Tipp: have the exam in the morning, somewhere between 9-10 AM. You can concentrate better, it’s maybe easier to arrange a quiet room and you are over it earlier 🙂

Tipp: book the exam well in advance: one or two weeks should do it. This enables you to freely choose a time slot and gives you enough push to focus on the final preparation.

I believe that only a very few machine learning consultant might actually have worked with all the required technologies and models in the real word. Chances are that you, just like me, will be not familiar with all of the required material. The following list will help you choose the best learning platform for your situation (not affiliate links).

AWS official training

https://aws.amazon.com/training/learning-paths/machine-learning/

This will suggest specific courses like:

Pros:

  • High quality material and training, content will be correct.
  • You will find courses for all domains
  • Fast and focused.

Cons:

  • Very expensive.
  • You might need to take days off.

AWS official documentation

Don’t laugh, hear me out! I’m not gonna say you should read all AWS the documentation. Even tough some employer of machine learning consultants would expect you to know everything by heart. Unfortunately, reading those 1000s of page would not even be enough, since you will be tested on many non-AWS topics as well.

Often you might be missing only few technologies. In this situation the simples solution is to check out the documentation. Unfortunately, there is no one singe page that would reference everything you need to know. I will give you many links later on which you could use to start browsing specific topics.

Pros:

  • High quality material, content will be correct.
  • Cheap.

Cons:

  • Time consuming.
  • For experts only to close the last gaps.

AWS practice

When you are already familiar with many AWS services, you do not need anyone to explain to you one more. You can just try it out. Almost all of the technologies will be covered by the free tier. You should definitely have AWS SageMaker hands-on experience for this exam.

Pros:

  • Best way to learn is by doing.
  • Cheap (for learning you do not need huge instances).

Cons:

  • Time consuming.

Coursera

Coursera is a great platform to learn from top Universities and Lecturers. They have a few great courses on the subject:

Pros:

  • Specially excellent in the non-AWS topics.
  • Online, learn when you have time.
  • Many courses are completely free.

Cons:

  • Not 100% focused on the exam.
  • Does not cover all AWS topics.

Udemy

Udemy is another great platform, which enables non-academic people and companies to share their courses. These are focused on specific subjects, rather than being very general. This is probably the best source if you are strictly focused on the exam and you are not that familiar with Machine Learning or AWS.

Pros:

  • Strong focus on the exam material.
  • Online, learn when you have time.
  • Practice exams are available.
  • Discounts are available.

Cons:

  • It does not give you much more than what is needed for the exam, which is still a lot.
  • It’s expensive unless you get a discount.
  • Some material are of lower quality, especially in the practice exams. Always check the comments and ratings!

I will close this post with the four knowledge domains from the official exam guide:

Domain 1: Data Engineering
1.1 Create data repositories for machine learning.
1.2 Identify and implement a data-ingestion solution.
1.3 Identify and implement a data-transformation solution.

Domain 2: Exploratory Data Analysis
2.1 Sanitize and prepare data for modeling.
2.2 Perform feature engineering.
2.3 Analyze and visualize data for machine learning.

Domain 3: Modeling
3.1 Frame business problems as machine learning problems.
3.2 Select the appropriate model(s) for a given machine learning problem.
3.3 Train machine learning models.
3.4 Perform hyperparameter optimization.
3.5 Evaluate machine learning models.

Domain 4: Machine Learning Implementation and Operations
4.1 Build machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance.
4.2 Recommend and implement the appropriate machine learning services and features for a given problem.
4.3 Apply basic AWS security practices to machine learning solutions.
4.4 Deploy and operationalize machine learning solutions.

Conclusion

This post introduced the AWS Machine Learning Speciality certificate. It is a good instrument for managers to filter the crowd of machine learning consultants out there. For machine learning consultants it is a good tool to stand out of the crowd.

In the next post I will present the first technical topic on data engineering for AWS Data Engineering Consultants. See you there!

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