Machine Learning: Exam Preparation
Prepare for the AWS Certified Machine Learning – Specialty exam
This learning path is designed specifically for individuals preparing to take the AWS Certified Machine Learning – Specialty exam. In addition to these self-paced digital training courses, we recommend one or more years of hands-on experience using machine learning (ML) services on AWS.
Machine Learning Exam Basics
Explore the services for building, training, and deploying models at scale. Hear from Amazon’s own data scientists about how to consider ML business challenges and decisions.
Digital | 2 hours
Process Model: CRISP-DM on the AWS Stack
Walk through the CRISP-DM methodology and framework and then apply the model's six phases to your daily work.
Digital | 50 minutes
The Elements of Data Science
Learn to build and continuously improve machine learning models.
Digital | 8 hours
Storage Deep Dive Learning Path
Progress from the fundamentals to technical deep dives to advance your AWS storage expertise and help your organization migrate to the cloud faster.
Machine Learning Security
This curriculum covers the AWS products and services that enable you to secure your applications and environments with specific topics detailing NACLs, security groups, AWS identity and access management, and encryption key management.
Digital | 30 minutes
Developing Machine Learning Applications
Explore Amazon's fully managed ML platfrom, Amazon SageMaker.
Types of Machine Learning Solutions
Review the three different disciplines for machine learning: computer vision, natural language processing, and chat bots. Go through practical applications and the AWS services used in each.
Digital | 15 minutes
Branching content areas
Communicating with Chat Bots
Learn how to build smart chat bots with the Communicating with Chat Bots curriculum.
Digital | 3.5 hours
Speaking of: Machine Translation and NLP
These courses explore how machines interact with the human language. Review AWS services that help you with neural networks and natural language processing topics like automatic speech recognition, natural and fluent language translation, and insights and relationships in text.
Digital | 80 minutes
Seeing Clearly: Computer Vision Theory
This curriculum explores how machines achieve understanding of images and videos.
Big Data on AWS
Big Data on AWS introduces you to cloud-based big data solutions such as Amazon Elastic MapReduce (EMR), Amazon Redshift, Amazon Kinesis and the rest of the AWS big data platform.
Classroom | 3 days