The 4 Best AWS Machine Learning Courses and Online Training for 2021 – Solutions Review

The Best AWS Machine Learning Courses

The Best AWS Machine Learning Courses

Solutions Review editors compiled this list of the best AWS machine learning courses and online training to use when growing your skills.

The first major cloud computing provider, Amazon Web Services (AWS) combines over 100 distinct services that cover a wide breadth of cloud capabilities. AWS focuses heavily on infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) offerings, with an emphasis on providing virtual infrastructures and development tools, including storage, computing, database, mobility, and management services. AWS makes use of virtual machines, which Amazon calls instances, that can be specifically configured in regard to computing, storage, and memory needed for the applications developed on it.

The Best AWS Machine Learning Courses

TITLE: Getting Started with AWS Machine Learning

OUR TAKE: Instructed by Blaine Sundrud, this AWS machine learning course shows you how to build, train, and deploy a model using Amazon SageMaker with built-in algorithms and Jupyter Notebook instance.

Platform: Coursera

Description: This course will teach you how to get started with AWS Machine Learning. Key topics include: Machine Learning on AWS, Computer Vision on AWS, and Natural Language Processing (NLP) on AWS. Each topic consists of several modules deep-diving into variety of ML concepts, AWS services as well as insights from experts to put the concepts into practice.

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TITLE: Exploratory Data Analysis with AWS Machine Learning

OUR TAKE: This course will teach you how to do exploratory data analysis and leverage relevant AWS services. This is a beginner-level tutorial that will provide you with the skills needed to achieve the AWS Machine Learning specialty certification.

Platform: Pluralsight

Description: In this course, you’ll learn how to analyze, visualize, preprocess and feature engineer datasets to make them ready for subsequent machine learning steps. You’ll also learn how to prepare your data for the machine learning pipeline by doing preprocessing and feature engineering.

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TITLE: Fundamentals of Machine Learning on AWS

OUR TAKE: This intermediate-level training taught by software developer Amber Israelsen will lay the foundation for the AWS Machine Learning Specialty certification. It was most recently updated in June 2020 and offers more than 2 hours of instruction.

Platform: Pluralsight

Description: First, you’ll explore what ML is and how it relates to artificial intelligence and deep learning. Next, you’ll learn how to identify and frame opportunities for machine learning. Then, you’ll discover the end-to-end machine learning process: fetching, cleaning, and preparing data, training and evaluating models, and deploying and monitoring models.

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TITLE: Become a Machine Learning Engineer Nanodegree

OUR TAKE: Intended for students who already have knowledge of machine learning algorithms, this training teaches you advanced techniques like how to package and deploy models. This training takes an estimated 3 months of time to complete.

Platform: Udacity

Description: Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application and evaluate the performance of your models. A/B test models and learn how to update the models as you gather more data, an important skill in industry.

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NOW READ: The Best AWS

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Tim is Solutions Review’s Editorial Director and leads coverage on big data, business intelligence, and data analytics. A 2017 and 2018 Most Influential Business Journalist and 2021 “Who’s Who” in data management and data integration, Tim is a recognized influencer and thought leader in enterprise business software. Reach him via tking at solutionsreview dot com.
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