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. And for good reason—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.
Among the many branches of AI is machine learning (ML), which is the practice of developing algorithms and statistical models, and training computer systems to use them to perform complex tasks autonomously. This brings a whole host of benefits to businesses both internally and customer-facing, with 65% of organizations who plan to adopt ML saying the technology helps businesses in decision-making, and 57% of businesses using machine learning to improve consumer experience.
With this in mind, it’s no surprise that ML adoption is increasing rapidly, with North America leading the way (80%), followed by Asia (37%), and Europe (29%). And of course, with this increased adoption comes an increase in demand for professionals with the expertise and skills to leverage this technology effectively. In fact, some reports show that as many as 82% of organizations need employees with machine learning skills, with AI and ML roles being the second most in-demand jobs on the market currently.
This all highlights plenty of opportunity for AWS professionals looking to take the next step down their career path. But what’s the best way for talent to secure these positions?
Earning AWS certifications is a highly effective way of boosting your curb appeal, unlocking more career opportunities, improving your earning potential, and propelling your progression within your existing role. And the good news is, AWS offers a certification specifically designed for machine learning, validating expertise in building, training, tuning, and deploying ML models on AWS.
But as a Specialty-level accreditation, the AWS Certified Machine Learning – Specialty (MLS-C01) exam is no easy ride. That’s why we’ve put together this comprehensive guide detailing everything you need to know about earning this certification, from what topics you’ll be tested on to the best resources that can help you prepare for the examination.
In this guide, we’ll cover:
- What is the AWS Certified Machine Learning – Specialty certification?
- Who should obtain the AWS Certified Machine Learning – Specialty certification?
- How to earn the AWS Certified Machine Learning – Specialty certification
- AWS Certified Machine Learning – Specialty study guide
- AWS Certified Machine Learning – Specialty certification training
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, which validates a candidate’s ability to design, build, deploy, optimize, train, tune, and maintain ML solutions for business problems by using the AWS Cloud.
According to AWS documentation, there will be a specific focus on testing a candidate’s ability to complete tasks like:
- 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 the AWS Certified Machine Learning – Specialty certification?
As the highest-level difficulty of all AWS certifications, it probably doesn’t come as much of a surprise to learn that this isn’t an accreditation aimed at professionals with foundational knowledge of the technology.
Instead, AWS recommends that professionals working towards this certification have specialist knowledge in AI and ML (you know, the clue’s in this being a specialty certification!). This includes the ability to express the intuition behind ML algorithms, and follow model-training, deployment, and operational best practices.
Of course, these specialist-level certifications also aren’t aimed at professionals just starting out their cloud journey. Instead, the MLS-C01 is intended for professionals in development or data science roles that have 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 either at an in-person Pearson VUE testing center or as an online proctored exam. It’s available to sit in the following languages:
- English
- Japanese
- Korean
- Simplified Chinese
You’ll have 180 minutes to complete the exam. The questions will be either:
- Multiple choice: these questions have four responses for you to choose from, but only one is correct. The other three incorrect options, known as ‘distractors’, are usually plausible responses relevant to the content area.
- Multiple response: these questions have five or more answers for you to choose from, and at least two of them are correct. But remember to look out for those pesky distractors! Once again, the remaining answers will all be plausible options, so take your time to read the questions and answers carefully to avoid being caught out!
How is the AWS Certified Machine Learning – Specialty exam scored?
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. However, 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).
It probably goes without saying, but unanswered questions are marked as incorrect (obviously), so in instances where you don’t know the answer, we always recommend taking a punt and guessing!
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.
How much does the AWS Certified Machine Learning – Specialty certification cost?
As with all specialty-level certifications, this certification costs $300 to take.
AWS Certified Machine Learning – Specialty study guide
To ensure your study time is spent most efficiently and effectively, 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
You should expect lots of concepts and technologies to appear across all six domains, including but not limited to:
- 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 – e.g. Amazon Athena, AWS Glue, Amazon QuickSight
- Compute – e.g. AWS Batch, Amazon EC2, AWS Lambda
- Containers – e.g. Amazon Elastic Container Registry (AWS ECR), Amazon Elastic Container Service (Amazon ECS), Amazon Elastic Kubernetes Service (Amazon EKS)
- Database – e.g. Amazon Redshift
- Internet of Things – e.g. AWS IoT Greengrass
- Machine Learning – e.g. AWS DeepLens, Amazon Rekognition, Amazon SageMaker
- Management and Governance – e.g. AWS CloudTrail, Amazon CloudWatch
- Networking and Content Delivery – e.g. Amazon VPC
- Security, Identity, and Compliance – e.g. AWS Identity and Access Management (IAM)
- Storage – e.g. 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, however. 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.
Of course, that doesn’t mean related areas that don’t pop up in the exam aren’t important to your wider understanding of ML and AWS. But with a lack of time to study consistently cropping up as the primary reason respondents in our Careers and Hiring Guide stop before completing a certification, it’s a wise move to leave these areas off the revision list for now.
So, what aren’t you to expected to know to obtain the AWS Certified Machine Learning certification? 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
So, you know what you need to learn, but where do you go to learn it? Fear not, we’ve got you covered! Here are all the best training courses, question sets, and learning resources available online from AWS and third-party cloud educators 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
Of course, there’s also a whole host of great places to hone your skills and level-up the knowledge for the MLS-C01 exam, outside of the official AWS material. Our favorite online training courses from trusted cloud educators include:
- Udemy: ‘AWS Certified Machine Learning Specialty 2024 – Hands On!’ 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, you know you’re in good hands – Frank spent nine years working at Amazon in the field of machine learning! Better yet, he’s joined by Stephane Maarek, who’s not only an AWS expert, but also 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, meaning you can rest assured that you’re getting the very latest information, taught from the best possible source.
- A Cloud Guru: led by the tried and tested 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, plain-speak 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. Not only will it equip you with a solid understanding of how AWS services can be used for ML projects, but it will also help you build a solid foundation of knowledge that helps you pass the MLS-C01 exam and confidently use the AWS ML portfolio in real-world applications.
Earning an AWS Certified Machine Learning – Specialty certification is no plain sailing, but by putting the time, effort, and dedication in today, you can reap the benefits for your career tomorrow—whether that be expanding your job and contract opportunities, boosting your salary, or accelerating your professional development. Keep these goals in mind when studying for the MLS-C01 exam, and consider this guide as your essential resource for ensuring you stay focused and informed. Good luck!
