The Ultimate Guide to the AWS Certified Machine Learning – Specialty Exam

The AWS Certified Machine Learning - Specialty (MLS-C01) exam validates your ability to design, build, deploy, optimize, train, tune, and maintain ML solutions for business problems using the AWS Cloud. This guide provides a comprehensive overview of the exam, including who should take it, what it covers, how it's scored, and how to prepare for it.

The Growing Importance of Machine Learning and AWS Certification

2024 marks the dawn of AI disruption, with the rapid evolution of artificial intelligence leading to mainstream adoption of the tech across the professional landscape. According to PwC, global GDP will rise to 14% by 2030 as a result of the accelerating development and take-up of AI, equating to an additional $15.7 trillion in market value. Machine learning (ML), a branch of AI, involves developing algorithms and statistical models and training computer systems to perform complex tasks autonomously.

ML brings benefits to businesses, with 65% of organizations planning to adopt ML citing its aid in decision-making, and 57% using it to improve consumer experience. ML adoption is increasing rapidly, with North America leading (80%), followed by Asia (37%), and Europe (29%). This increased adoption creates a demand for professionals with the expertise to leverage this technology effectively. Reports indicate that 82% of organizations need employees with machine learning skills, making AI and ML roles the second most in-demand jobs.

Earning AWS certifications is a way to boost your appeal, unlock career opportunities, improve earning potential, and propel your progression within your existing role. AWS offers a certification specifically designed for machine learning, validating expertise in building, training, tuning, and deploying ML models on AWS.

What is the AWS Certified Machine Learning - Specialty Certification?

The AWS Certified Machine Learning - Specialty certification is obtained by successfully passing the MLS-C01 exam. The exam validates a candidate’s ability to design, build, deploy, optimize, train, tune, and maintain ML solutions for business problems by using the AWS Cloud.

Read also: Learn about CPPLP Certification

AWS documentation indicates a focus on testing a candidate’s ability to complete tasks such as:

Identifying appropriate AWS services to implement ML solutions
Designing and implementing cost-optimized, reliable, scalable, and secure ML solutions
Selecting and justifying the appropriate ML approach for a range of business problems

Who Should Obtain This Certification?

The MLS-C01 exam is designed for professionals with specialist knowledge in AI and ML. This includes the ability to express the intuition behind ML algorithms and follow model-training, deployment, and operational best practices.

AWS recommends that professionals working towards this certification have specialist knowledge in AI and ML. The MLS-C01 is intended for professionals in development or data science roles with at least two years of experience developing, architecting, and running ML or deep learning workloads in the AWS Cloud. This includes experience in ML, deep learning frameworks, and performing basic hyperparameter optimization.

How to Earn the AWS Certified Machine Learning - Specialty Certification

The MLS-C01 exam can be taken at an in-person Pearson VUE testing center or as an online proctored exam and is available in English, Japanese, Korean, and Simplified Chinese.

You will have 180 minutes to complete the exam. The questions will be either multiple choice or multiple response:

Read also: CFP Education Guide

Multiple choice: These questions have four responses, with only one correct answer. The three incorrect options, known as ‘distractors’, are plausible responses relevant to the content area.
Multiple response: These questions have five or more answers, with at least two correct answers. Once again, the remaining answers will all be plausible options.

Exam Scoring

The MLS-C01 exam is made up of 65 questions, but you will only be scored on 50 of them. The remaining 15 questions have no impact on your final score-instead, they’re just there to collect candidate performance data and evaluate question types for future use. You won’t know which are the 15 unscored questions when taking the exam, so it’s important to treat each one with the same importance.

The exam is pass/fail and scored against a minimum standard on a scale of 100-1,000. The minimum pass rate to obtain the certification is 750, but as AWS uses a compensatory scoring model, you don’t need to pass each individual section of the exam (just the exam as a whole). Unanswered questions are marked as incorrect, so in instances where you don’t know the answer, it is recommended to guess. Along with your overall score and pass/fail designation, your score report may also include a table of classifications showing your performance across each section of the exam. This feedback is provided to help you identify your areas of strength and weakness across your test performance.

Exam Cost

As with all specialty-level certifications, this certification costs $300 to take.

AWS Certified Machine Learning - Specialty Study Guide

To efficiently and effectively spend your study time, it’s key to know the skills and knowledge you need to focus on. The MLS-C01 exam is split across four areas (also called domains), each having a different weighting on your overall score:

Domain 1 - Data Engineering (20%): creating data repositories for ML; identifying and implementing a data ingestion solution; identifying and implementing a data transformation solution
Domain 2 - Exploratory Data Analysis (24%): sanitizing and preparing data for modeling; performing feature engineering; analyzing and visualizing data for ML
Domain 3 - Modeling (36%): framing business problems as ML problems; selecting the appropriate model(s) for a given ML problem; training ML models; performing hyperparameter optimization; evaluating ML models
Domain 4 - Machine Learning Implementation and Operations (20%): building ML solutions for performance, availability, scalability, resiliency, and fault tolerance; recommending and implementing the appropriate ML services and features for a given problem; applying basic AWS security practices to ML solutions; deploying and operationalizing ML solutions

Expect concepts and technologies to appear across all six domains, including but not limited to:

Read also: Guide to CPA Requirements

Ingestion/collection
Processing/ETL
Data analysis/visualization
Model training
Model deployment/inference
Operationalizing ML
AWS ML application services
Language relevant to ML (for example, Python, Java, Scala, R, SQL)
Notebooks and integrated development environments (IDEs)

The services, tools, and features considered in-scope for the AWS Certified Machine Learning - Specialty certification exam include (but are not limited to):

Analytics: Amazon Athena, AWS Glue, Amazon QuickSight
Compute: AWS Batch, Amazon EC2, AWS Lambda
Containers: Amazon Elastic Container Registry (AWS ECR), Amazon Elastic Container Service (Amazon ECS), Amazon Elastic Kubernetes Service (Amazon EKS)
Database: Amazon Redshift
Internet of Things: AWS IoT Greengrass
Machine Learning: AWS DeepLens, Amazon Rekognition, Amazon SageMaker
Management and Governance: AWS CloudTrail, Amazon CloudWatch
Networking and Content Delivery: Amazon VPC
Security, Identity, and Compliance: AWS Identity and Access Management (IAM)
Storage: Amazon Elastic Block Store (Amazon EBS), Amazon FSx, Amazon S3

Knowing what will be covered in the MLS-C01 exam is only one piece of the puzzle. It’s also handy to know what you won’t be tested on, to ensure you don’t waste valuable study time brushing up on things you don’t need to know. Examples of skills, services, and expertise considered out-of-scope for the MLS-C01 exam include but are not limited to:

AWS Data Pipeline
AWS DeepRacer
Extensive or complex algorithm development
Extensive hyperparameter optimization
Complex mathematical proofs and computations
Advanced networking and network design
Advanced database, security, and DevOps concepts
DevOps-related tasks for Amazon EMR

AWS Certified Machine Learning - Specialty Certification Training

AWS and third-party cloud educators offer training courses, question sets, and learning resources to help you pass the MLS-C01 exam.

AWS Certified Machine Learning - Specialty Exam Prep with AWS

The best AWS Certified Machine Learning - Specialty training resources from AWS include:

AWS Certified Machine Learning - Specialty Official Practice Question Set: The official practice question set from AWS Skill Builder is made up of 20 exam-prep questions specifically designed to help you assess your readiness for the MLS-C01. With exam-style scoring, you’ll receive detailed feedback on your answers, along with a range of handy resources to help you improve your know-how in the relevant content areas
Exam Readiness: AWS Certified Machine Learning - Specialty: AWS offer a free, four-hour online course that prepares you to take the AWS Certified Machine Learning - Specialty exam. Featuring a comprehensive exploration of the exam logistics, question mechanics, and each of the exam’s four technical domains, the course promises to help you identify your strengths and weaknesses, better describe technical topics and concepts, and use effective strategies for studying and taking the exam. Better yet, it even accumulates a detailed quiz, so that you’ll know what areas to emphasize in your pre-exam studies

Other Online AWS Certified Machine Learning - Specialty Training Courses

Online training courses from trusted cloud educators include:

Udemy: ‘AWS Certified Machine Learning Specialty 2024 - Hands On!’ This is the most popular MLS-C01 preparation course on Udemy, featuring over 14 hours of on-demand video, a practice test, six expert-written articles, and two downloadable resources! Taught by Frank Kane, who spent nine years working at Amazon in the field of machine learning, and Stephane Maarek, the highest-rated AWS certification instructor on Udemy. The course has also recently been updated to include the latest SageMaker features, Generative AI (GPT), and new AWS ML Services.
A Cloud Guru: Led by the team of subject matter experts at A Cloud Guru, this MLS-C01 preparation course includes over 22 hours of material including engaging lectures, interactive labs, and plenty of real-world examples. Covering all the core domains of the exam, the professional-level course promises to challenge your intuition, creativity, and knowledge of the AWS platform. It will equip you with a solid understanding of how AWS services can be used for ML projects.

A Personal Journey to Certification

One individual shared their experience preparing for and taking the AWS Certified Machine Learning - Specialty certification. This individual had a background in Mechatronics Engineering and experience in various roles, from industrial Computer Vision (CV) with C++ to front-end development with Kotlin/Java. They decided to self-learn their way toward an ML job, starting with the Statistical Learning course by Stanford Online, followed by the Deep Learning Specialization by Andrew Ng. These courses were supplemented with personal projects, including a serverless API that extracts key information from bills automatically each month, using a fine-tuned LayoutLMv3 model.

They landed roles at 2 ML consultancies across 2 years, working on various Deep Learning projects spanning CV, NLP, GenAI, and streaming data processing for medical, industrial, and commercial applications. Recognizing the industry’s growing need for engineers who can demonstrate practical knowledge across the entire ML development pipeline, they decided to add an official ML certification to their resume.

Exam Preparation Strategy

This individual dedicated 6 weeks, 20-30 hours/week, to prepare for the exam.

Week 1 & 2: Knowledge Re-cap: Skimmed through previously learnt course materials, including Statistical Learning by Stanford Online and Deep Learning Specialization by Andrew Ng.
Week 3 & 4: Exam Study Plan: Utilized the Udemy Certified ML Specialty course by Frank Kane and Spaced-recall exercises with Quizlet.
Week 5 & 6: Practice Exams: Utilized Udemy AWS Certified Machine Learning Specialty exam by Frank Kane and Tutorials Dojo AWS Certified Machine Learning Specialty Practice Exams 2025.

Exam Tips

The questions are concise, with every sentence carrying relevant information, so take your time reading through them.
The exam covers many AWS ML/Cloud services but does not delve too deeply into each.
It tests fundamental ML skills such as interpreting results, dealing with missing or imbalanced data, and identifying underfitting or overfitting models.
The questions are framed as business scenarios, which you must convert into technical specifications and find the most optimal solution.
Understanding how each AWS service/ML/linear model works and how they fit together at a high level is essential.

Additional Tips for Exam Day:

Sit the exam at one of the approved centers to reduce the risk of technical issues.
Skip questions you are unsure of and circle back after you have finished the rest.
Have a good night's rest the day before.

tags: #AWS #Certified #Machine #Learning #Specialty #exam