AWS Machine Learning Certification Prerequisites

AWS Machine Learning Certificate Prerequisites
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Meet the prerequisite to be proficient

It is incredible that you intend to acquire your Amazon Web Services or AWS certification. Today, it is one of the lucrative certifications in the IT sector, and its market will boom and grow further in the next decade or so, given the rising popularity of cloud computing skills.


So, regardless of whether you wish to acquire cloud skills to kickstart a career or switch careers, there are some AWS machine learning certification prerequisites you must be well-versed with. Once you fulfill these primary needs, you can proceed towards actually acquiring the certification.


Amazon Web Services is the prototype for all the accreditations. Its distinguishable scope-oriented exams and certifications enjoy massive popularity for their precision and state-of-the-art medium for assessing Cloud Computing skills. The Amazon Web Services Certifications have four steps:


  1. Foundational-level certifications
  2. Associate-level certifications
  3. Professional-level certifications
  4. Specialty certifications


In this guide, we will not get into either, but the detail on all the prerequisites you must be well-acquainted with before you commence your journey into this life-changing career.

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What are The Prerequisites for AWS Certification?

If you wish to acquire AWS machine learning certification, there are some prerequisites that you need to fulfil for machine learning. Below, we will address them:


1. Experience

The course will benefit professionals who get into data science or development. Hence, one of the most preliminary prerequisite is a minimum of two years of experience in – architecting, developing, or working with deep learning or machine learning workloads in the AWS Cloud. You can take up a basic level course and then try your hands in the playfield.


Here are the courses that can help you acquire this information:


a. Professional Certificate in Deep Learning – Offered by IBM – [edX] – It is a vast seven-month course. You can spend at least two to four hours every week to get well-acquainted with Deep learning that will be instrumental when you proceed on your AWS certification journey.

b. Machine Learning A-Z™: Hands-On Python & R In Data Science – [Udemy] – If you want to understand the machine learning workloads, there cannot be a better pick than this Udemy class. It comprises 44 hours of on-demand video and quizzes, activities, and exercises, all of which can get you well-acquainted with the subject.


2. Amazon Web Services Account

You cannot excel or bag your certification unless you have hands-on experience working and implementing all your comprehended theoretical concepts. To practice what you learn, you need a platform. For this, one of the most inevitable AWS machine learning prerequisites is an AWS account.

Here is the course that can help you get started with the AWS account for the first time:


a. Absolute Beginners Introduction to Amazon Web Services (AWS) – [Udemy]– You can use the below-listed course to know how to start your AWS account and practice what you learn. The class will also familiarize you with the fundamentals of AWS. Once you finish the training, nobody will call you a beginner in AWS. It is a short session with 3 hours of on-demand video.


3. Machine Learning Basics

Machine learning is a vital skill for every aspiring data scientist or analyst. Typically, it will benefit people who wish to convert a massive chunk of raw data and giveaway predictions or trends analyzing it. You cannot complete your AWS machine learning certification if you do not familiarize yourself with the basics. Hence, it is another necessary prerequisite for AWS machine learning.
Here is the class that can give you all the fundamental knowledge you need on the subject:

a. Machine Learning Fundamentals – UC San Diego edX

4. Algorithm

While the above session will give you an instrumental knowledge of machine learning, that’s not all that can streamline your journey into acquiring the AWS machine learning certification. So, beyond elementary knowledge, you must also be acquainted with machine learning algorithms.


Several algorithms upgrade the machines and make them powerful enough to perform surgeries, play chess, and get more personal. Data scientists can employ these machine learning algorithms to solve complex real-world problems. However, please remember that these algorithms are self-modifying and update over time.


So, beyond the top machine learning algorithms, you must dig further and adopt new algorithms over time. Knowledge of these can help you express the intuition behind them.


5. Pandas, Numpy, and Matplotlib

You cannot excel in your machine learning certification if you do not have elementary knowledge of Pandas, Numpy, and Matplotlib.


Here are some classes that can help you get your basics sorted:


a. Data Analysis with Pandas and Python – [Udemy]– It is a bestselling course suitable for students with a prior experience with Python and data types. This class can teach data analysis using Pandas, one of the imperative AWS machine learning certification prerequisites. This 21.5 hours of on-demand video has many coding exercises to give you theoretical and fundamental clarity.

b. Python for Data Analysis: Pandas & NumPy – Offered by Coursera Project Network – [Coursera] – If you do not want to take two individual courses but get your basics sorted, opt for this combined class. It educates you on Pandas, and NumPy basics, and can be a fresh start into the fundamentals. It is suited for beginners and is a free two-hour class that gives you enough knowledge to clear your AWS ML certification.

c. Matplotlib Intro with Python – [Udemy] – It is a short introductory class that introduces you to Matplotlib and assumes no former knowledge except Python experience. You can take this one-hour class to learn data visualization and plotting with Matplotlib.


6. Hyperparameter optimization

Next, prerequisite for AWS machine learning you need is experience conducting the basic hyperparameter optimization. You should know how to pick the best hyperparameters and better the working of your machine learning models.


A class that can help you with all is:

a. Hyperparameter Optimization for Machine Learning – [Udemy] It is a bestselling course on Udemy that assumes former knowledge of NumPy and Pandas, but if you have followed the above five prerequisites, following this class should not be challenging for you. The session has 10 hours of on-demand video with hands-on Python code examples that you can employ for practice and reference.


7. Frameworks

Further, you must also have experience and knowledge of Deep learning and Machine learning frameworks as AWS machine learning certification prerequisites.


a. The 11 deep learning frameworks you should know in 2022 are:

  • Keras
  • Theano
  • Deeplearning 4j (DL4J)
  • Caffe
  • Chainer
  • Microsoft
  • Sonnet
  • MxNet
  • Swift for TensorFlow
  • Gluon
  • ONNX


b. Machine Learning frameworks you should know in 2022 are:

  • Shogun
  • Sci-Kit Learn
  • Apache MXNet
  • H2O
  • Apple’s Core ML


c. Combined frameworks you must know are:

You can find individual or combined classes to study their theoretical and practical aspects.


8. Machine Learning best practices

Lastly, you must also understand the best practices in machine learning operation, deployment, and model training.


One best class for this is:

a. Deployment of Machine Learning Models – [Udemy]– It is a 10-hour of on-demand video that helps you build machine learning model APIs and deploy models into the cloud, something that will help you with your AWS ML certification.


9. General prerequisites for AWS Certification

Beyond the AWS machine learning certification prerequisites we stated, you should also have:

  • Associate-level knowledge of AWS services such as EC2
  • Dedication and time to learn
  • Patience and passion for acquiring this new skill
  • A computer and an internet connection


Related Prerequisites Guide: Machine Learning and AI | Machine Learning in Python | Stanford Machine Learning


Frequently Asked Questions

Ques 1. Does AWS require coding?

Ans. No, you do not need coding for AWS.


Ques 2. Can I take up the exam without any formal knowledge of ML or experience?

Ans. Unfortunately, you cannot take the AWS machine learning certification exam without prior knowledge or experience with machine learning.


Ques 3. How much time should I dedicate to exam prep?

Ans. Once you have completed all the elementary training, you should dedicate at least four weeks to explicit exam preparation. It won’t be easy, but it isn’t impossible to ace the exam with the mandatory preparation and understanding.


Ques 4. How is this certification helpful?

Ans. There are many perks of holding the AWS machine learning certification.

  1. It validates your ability to train, build, and deploy machine learning models with the AWS cloud.
  2. It provides you with global popularity for your experience, information, and skills.
  3. You will be eligible for some of the top-paying data-tech jobs globally.
  4. It adds a credential to your CV, helping you stand out from competitors.
  5. You can pursue your career as an AWS engineer.

Final Word
You know your goal! You are now aware of the AWS machine learning prerequisites. Now, it is time to acquire the knowledge and build your skills to excel in your career. You can use our suggested resources and prepare for the certification!


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