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. Machine learning involves studying computer algorithms that improve automatically through experience.
With this in mind, we’ve compiled this list of the best AWS machine learning courses and online training to consider if you’re looking to grow your cloud artificial intelligence and automation skills for work or play. This is not an exhaustive list, but one that features the best AWS machine learning courses and training from trusted online platforms. This list of the best AWS machine learning courses below includes links to the modules and our take on each.
The Best AWS Machine Learning Courses
OUR TAKE: Navigating to this link will bring you to Amazon’s machine learning training portal, which features numerous ways to advance your skills and knowledge by learning from AWS experts.
Platform: Amazon Web Services
Description: Learn how to apply machine learning (ML), artificial intelligence (AI), and deep learning (DL) to your business, unlocking new insights and value. Explore real-world examples and labs based on problems we’ve solved at Amazon using ML. Access 65+ digital courses (many of them free).GO TO TRAINING
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.
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.GO TO TRAINING
OUR TAKE: This edX training module shows you how to integrate machine learning into your apps with training from AWS experts and without a data science background. It takes an estimated 4 weeks to complete.
Description: This course will teach application developers how to use Amazon SageMaker to simplify the integration of machine learning into their applications. Key topics include an overview of Machine Learning and problems it can help solve, using a Jupyter Notebook to train a model based on SageMaker’s built-in algorithms and, using SageMaker to publish the validated model.GO TO TRAINING
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.
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.GO TO TRAINING
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.
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.GO TO TRAINING
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.
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.GO TO TRAINING
OUR TAKE: This certification prep course is taught by Frank Kane, who spent nine years working at Amazon itself in the field of machine learning. It includes 10 hours of on-demand video, 2 articles, and a practice test.
Description: In addition to the 9-hour video course, a 30-minute quick assessment practice exam is included that consists of the same topics and style as the real exam. You’ll also get four hands-on labs that allow you to practice what you’ve learned, and gain valuable experience in model tuning, feature engineering, and data engineering.GO TO TRAINING
OUR TAKE: With nearly 2,700 reviews, this popular training will help you gain first-hand experience on how to train, optimize, deploy, and integrate machine learning in the AWS cloud.
Description: This course is designed for anyone who is interested in AWS cloud-based machine learning and data science. Learners should have familiarity with Python, an AWS account, basic knowledge of Pandas, Numpy, and Matplotlib. The ideal student for this course is willing to learn and participate in the course Q&A forum when help is needed.GO TO TRAINING
OUR TAKE: This AWS machine learning exam course features 17 hours of on-demand video, 13 downloadable resources, and 26 articles. This is a bestseller with 4.6 stars and more than 800 reviews.
Description: With over 500 slides and over 50 practice questions, this course is by far the most comprehensive course on the market that provides students with the foundational knowledge to pass the AWS Machine Learning Certification exam like a pro! This course covers the most important concepts without any fillers or irrelevant information.GO TO TRAINING
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