AWS Certified Machine Learning – Specialty 2022

This credential helps organizations identify and develop talent with critical skills for implementing cloud initiatives.

Earning AWS Certified Machine Learning – Specialty validates expertise in building, training, tuning, and deploying machine learning (ML) models on AWS.

Who should take this exam?

AWS Certified Machine Learning – Specialty is intended for individuals who perform a development or data science role and have more than one year of experience developing, architecting, or running machine learning/deep learning workloads in the AWS Cloud.

Before you take this exam, we recommend you have:

  • At least two years of hands-on experience developing, architecting, and running ML or deep learning workloads in the AWS Cloud.

  • Ability to express the intuition behind basic ML algorithms.

  • Experience performing basic hyperparameter optimization.

  • Experience with ML and deep learning frameworks.

  • Ability to follow model-training, deployment, and operational best practices

What does it take to earn this certification?

To earn this certification, you’ll need to take and pass the AWS Certified Machine Learning – Specialty exam (MLS-C01). The exam features a combination of two question formats: multiple choice and multiple response. Additional information, such as the exam content outline and passing score, is in the exam guide.

Download the exam guide »

Review sample questions that demonstrate the format of the questions used on this exam and include rationales for the correct answers.

Download the sample questions »

Exam overview

Level: Specialty
Length: 180 minutes to complete the exam
Cost: 300 USD 
Visit Exam pricing for additional cost information.

Format: 65 questions; either multiple choice or multiple response
Delivery method: Pearson VUE and PSI; testing center or online proctored exam

Languages offered

This exam is offered in the following languages: English, Japanese, Korean, and Simplified Chinese.

Prepare for your exam

You’ve set your goal. Now it’s time to build knowledge and skills to propel your career.

Check out these resources from AWS Training and Certification that are relevant to AWS Certified Machine Learning – Specialty.

It’s not required to take any specific training before you take an exam.

These recommended resources are opportunities to learn from the experts at AWS.

Exam review:

AWS Training for developers and data scientists


Best AWS Certified Machine Learning – Specialty Books 2022

Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines

Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines

With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services.

The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level up your skills.

This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days.

Throughout the book, authors Chris Frogly and Antje Barth demonstrate how to reduce cost and improve performance.

  • Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more
  • Use automated machine learning to implement a specific subset of use cases with Sage Maker Autopilot
  • Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment
  • Tie everything together into a repeatable machine learning operations pipeline
  • Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka
  • Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more

AWS Certified Machine Learning Study Guide: Specialty (MLS-C01) Exam

AWS Certified Machine Learning Study Guide: Specialty (MLS-C01) Exam

Succeed on the AWS Machine Learning exam or in your next job as a machine learning specialist on the AWS Cloud platform with this hands-on guide 

As the most popular cloud service in the world today, Amazon Web Services offers a wide range of opportunities for those interested in the development and deployment of artificial intelligence and machine learning business solutions. 

The AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam delivers hyper-focused, authoritative instruction for anyone considering the pursuit of the prestigious Amazon Web Services Machine Learning certification or a new career as a machine learning specialist working within the AWS architecture. 

From exam to interview to your first day on the job, this study guide provides the domain-by-domain specific knowledge you need to build, train, tune, and deploy machine learning models with the AWS Cloud.

And with the practice exams and assessments, electronic flashcards, and supplementary online resources that accompany this Study Guide, you’ll be prepared for success in every subject area covered by the exam. 

You’ll also find: 

  • An intuitive and organized layout perfect for anyone taking the exam for the first time or seasoned professionals seeking a refresher on machine learning on the AWS Cloud 
  • Authoritative instruction on a widely recognized certification that unlocks countless career opportunities in machine learning and data science 
  • Access to the Sybex online learning resources and test bank, with chapter review questions, a full-length practice exam, hundreds of electronic flashcards, and a glossary of key terms 

AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam is an indispensable guide for anyone seeking to prepare themselves for success on the AWS Certified Machine Learning Specialty exam or for a job interview in the field of machine learning, or who wishes to improve their skills in the field as they pursue a career in AWS machine learning. 

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