AWS Certified Machine Learning - Specialty Certification: Your Key to a Brighter Future

Taylor Karl
/ Categories: Resources, Cloud
AWS Certified Machine Learning - Specialty Certification: Your Key to a Brighter Future 1358 0

Empowering Your Career with an AWS Certified Machine Learning - Specialty Certification

As we continue to hurdle towards a future dominated by artificial intelligence and machine learning, the demand for professionals well-versed in these technologies is on a steady incline. If you're looking to stay at the forefront of this cutting-edge field, the AWS Certified Machine Learning - Specialty Certification could be one of your most powerful weapons. So, why not give yourself a leg up on the competition.

As a leading training provider for thousands of students seeking to get AWS Certified, we'll tell you everything you need to know. Including how it can boost your career opportunities and salary potential.

What’s Included:

What is the AWS Machine Learning – Specialty Certification?

AWS Certified Machine Learning Specialty BadgeThe AWS Certified Machine Learning - Specialty certification is a part of the AWS certification program, designed specifically for individuals who perform complex Machine Learning (ML) projects and want to showcase their expertise in developing, training, tuning, and deploying machine learning solutions on AWS. Its primary focus is on data analysis, feature engineering, ML model development, deployment, and improvement. 

What is the career outlook for someone with an AWS Machine Learning Certification?

With the rise of automation using AI, job roles that require machine learning knowledge will increase as organizations migrate towards automated processes to reduce operation costs and improve service efficiency. As a global leader in cloud computing, Amazon Web Services is an authoritative source for cloud certifications. Their AWS Machine Learning certification validates hands-on experience and expertise in machine learning on AWS. 

According to Gartner, by 2024, 75% of enterprises are projected to move from experimenting with Artificial Intelligence (AI) to operationalizing it.

With this certification, you're well-positioned to qualify for numerous positions with organizations. Some of the positions available to you with the AWS Machine Learning – Specialty certification include data analysts, project managers, consultants, and more. That level of flexibility gives you opportunities to either advance or switch career lanes. Simply put, this is more than just a certification—it's a career game-changer for most machine learning professionals.

Who should pursue the AWS Machine Learning Certification?

The AWS Machine Learning Specialty Certification is meant for people who use artificial intelligence or machine learning hands-on at their job. Specifically, it's targeted towards professionals who want to work in AI/ML development or data science roles where they actively build, analyze data for, design, or run machine learning systems.

Salary Potential for AWS Certified Machine Learning Specialists

A key question on your mind might be about the salary potential once you've earned your AWS Machine Learning Certification. It's a fair question, and the answer can vary widely depending on various factors, including your geographical location, years of experience in the field, the size of your employer, and your other skills and qualifications.

However, to give you some context, according to research from, the average annual salary of an AWS Certified Machine Learning Specialist in the United States is approximately $145,725.

10 Highest Paying Cities for Machine Learning Specialists


Average Salary

San Francisco, CA


San Jose, CA


Oakland, CA


Hayward, CA


Ashland, CA


Vallejo, CA


Antioch, CA


Seattle, WA


Lebanon, NH


Bothell, WA


Beyond a base salary, most organizations offer a comprehensive package of benefits, including health insurance, retirement plans, performances bonuses, and more. Additionally, having an in-demand certification like the AWS Machine Learning - Specialty certification could give you an edge in negotiation during hiring or promotions.

Benefits of Earning an AWS Machine Learning – Specialty Certification

In addition to the potential for a larger salary, some additional benefits of certification include:

  • Increased job recruitment potential
  • A robust career path with many different job roles available
  • Many industries outside of tech are harnessing the power of ML

As ML plays a more prominent role across all industries, staying relevant is more important than ever. With an AWS Machine Learning – Specialty certification, your career and earning opportunities will increase by differentiating yourself from those who are not certified.

Eligibility Requirements

While there are no prerequisites for AWS certifications, earning this certification is no small feat! Before taking the exam, AWS recommends individuals have the following experience and knowledge:

Recommended Experience and Knowledge:

  • 2+ years developing, architecting, or running ML or deep learning on AWS
  • Data scientists and engineers who design, build, and maintain machine learning solutions on the AWS Cloud
  • Working knowledge of hyperparameter optimization
  • Familiarity with common ML and deep learning frameworks
  • Understand intuitions behind basic ML algorithms
  • Follow best practices for model training, deployment, and operations

Remember, these recommendations are just that – recommendations. They aren't hard-set, mandatory rules, but they can significantly enhance your ability to pass the AWS Certified Machine Learning – Specialty certification exam (MLS-C01).

Exam Topics

When getting ready for the AWS Machine Learning certification exam, it's important to have a strong handle on the exam topics. These topics cover real-world machine learning situations and theoretical ideas you need to know. As well as knowledge of other AWS offerings. There are four main domains for the exam.

Exam Domains:

  1. Data Engineering: Create, maintain, and transform datasets, including tasks like data collection, storage, and processing using AWS services.
  2. Exploratory Data Analysis: Interpret data with data visualization, analyze structured and unstructured data using statistical measures, and suggest appropriate ML.
  3. Modeling: Understand different ML models and algorithms and demonstrate proficiency in model training, evaluation, and interpretation.
  4. Machine Learning Implementation and Operations: Deploy, integrate, optimize, and operate ML solutions in a production environment.

For a more detailed listing of the domains and the knowledge areas being tested, and the most up-to-date information on the exam, download the AWS Machine Learning – Specialty (MLS-C01) Exam Guide.

Exam Format

Being familiar with the exam's format can significantly enhance your preparation strategy and help you manage your time more effectively during the exam itself. You should anticipate the following components:

  • Exam Location: In person at a testing center or online proctoring 
  • Exam Time Limit: The exam is three hours (180 minutes) long
  • Exam Languages: English, Japanese, Korean, and Simplified Chinese
  • Exam Domains: There are four domains covered in the exam
    • Domain 1: Data Engineering (20% of the exam)
    • Domain 2: Exploratory Data Analysis (24% of the exam)
    • Domain 3: Modeling (36% of the exam)
    • Domain 4: Machine Learning Implementation and Operations (20% of exam)
  • Question Format: 65 total questions with only 50 graded
    • Multiple Choice: One correct answer with three incorrect answers serving as distractors
    • Multiple Response: Two or more correct answers out of five or more answer options
  • Unanswered Questions: Any questions unanswered are marked as incorrect
  • Passing Score: The exam is pass/fail and you must achieve a score of 750 out of 1000 to pass
  • Score Report: Your post-exam score report may show your performance in each of the exam domains; you do not have to achieve a passing score in all domains to pass the exam
  • Important note about exam questions: 15 of the questions are unscored so that AWS can collect information to evaluate whether these questions are suitable to be included as graded questions for future exam use.

Success Stories from AWS Machine Learning Specialists

Example 1: United Airlines worked with an AWS Certified Machine Learning Specialist to create a tool that helps check passengers' documents faster and cheaper.

United Airlines Logo

The specialist used AWS services to build a system that automatically recognizes text in passports and other documents to extract key details like names and passport numbers without needing manual review. Adopting this Machine Learning-based approach for document handling enables United to effectively scale up in line with their increasing passenger count.

Example 2: Amazon Music worked with an AWS Certified Machine Learning Specialist to optimize its machine learning models using AWS SageMaker and NVIDIA for better performance and cost savings.

Amazon Music Logo

The specialist improved search features like spellcheck and vector search, enabling faster discovery of songs and podcasts, even with typos. With the help of NVIDIA's high-performance GPUs and exclusive optimization tools, they managed to quicken the pace of model training and diminish overall costs. The outcome? A faster, seamless search experience for all Amazon Music users which, in return, spiked their overall gratification.


As more organizations integrate AWS Machine Learning services into their operations, demand for certified talent will skyrocket globally. Early adopters who gain this credential now can ride the wave as leaders in the field. The certification also has strong future-proofing power.

Even if new advanced services and technologies emerge, foundational ML skills and cloud fluency will remain relevant. Lifelong learners can build on this base certification with additional focused credentials later. And with demand for machine learning outpacing supply for AWS machine learning experts, competitive salaries will only continue rising for those carrying this certification.

Learn how New Horizons can partner with you on the path to mastery - get AWS Machine Learning training now.

FAQ: How to Prepare for the AWS Certified Machine Learning - Specialty Exam

When preparing for the AWS Machine Learning - Specialty certification, regularly reviewing materials and consistently practicing are key. Additionally, the following strategies can help you get exam-day ready:

  • Hands-On Practice: Engage in practical sessions using AWS labs to gain real-world problem-solving experience.
  • Online Courses & AWS Training: Enroll in courses and AWS-specific training to cover exam topics comprehensively.
  • AWS Whitepapers & FAQs: Utilize AWS-authored materials for insights on ML Services and exam preparation.
  • Join a Study Group: Connect with peers on AWS's re:Post forum for discussions and clarifications.
  • Practice Exams: Test your knowledge with practice exams to identify areas needing improvement.