AWS MLA-C01 Exam Questions 2025
Get ready for the AWS Certified Machine Learning – Specialty (MLA-C01) exam using Cert Empire’s up-to-date Exam Questions. Verified by AWS experts and supported with accurate answers and a practical online simulator, they help you study efficiently and pass with ease.
All the questions are reviewed by Vanesa Martin who is a MLA-C01 certified professional working with Cert Empire.
About MLA-C01 Exam
AWS MLA-C01: AWS Certified Machine Learning
What is AWS MLA-C01?
The AWS Certified Machine Learning – Specialty (MLA-C01) exam is an advanced-level certification from Amazon Web Services. It validates a candidate’s expertise in building, training, tuning, and deploying machine learning (ML) models on AWS. Unlike entry-level certifications, this exam goes deep into both machine learning theory and practical AWS service implementation. Candidates are tested on their ability to apply machine learning to solve business problems using services like Amazon SageMaker, Amazon Rekognition, and other AI/ML tools within AWS.
Who Should Take This Exam?
The AWS MLA-C01 exam is intended for professionals who already work with data, analytics, and ML solutions.
Typical candidates include:
- Machine Learning Engineers who design, train, and optimize ML models.
- Data Scientists who apply statistical methods and ML techniques to large datasets.
- Data Engineers who prepare, transform, and manage data pipelines for ML workflows.
- AI/ML Developers building intelligent applications with AWS services.
- Solutions Architects specializing in AI/ML solutions on the cloud.
Experience level:
This exam is designed for mid to senior-level professionals with 2+ years of practical experience in machine learning and hands-on work with AWS AI/ML services.
Prerequisites and Recommendations
Official prerequisites (by AWS):
- No mandatory certifications are required before attempting MLA-C01.
Practical recommendations:
- Experience: At least 2 years of hands-on experience designing and implementing ML or deep learning solutions on AWS.
- Prior certifications: It is highly recommended (but not required) to first earn AWS Certified Solutions Architect – Associate or AWS Certified Data Analytics – Specialty.
- Skills to have:
- Strong understanding of ML algorithms, supervised/unsupervised learning, and deep learning concepts.
- Proficiency in Python and ML frameworks like TensorFlow, PyTorch, or MXNet.
- Ability to select the right AWS service (SageMaker, Rekognition, Comprehend, Translate, etc.) for given ML use cases.
- Knowledge of data engineering concepts such as ETL, data wrangling, and feature engineering.
Exam Objectives and Domains
The AWS MLA-C01 exam measures knowledge across four primary domains.
Domain 1: Data Engineering (20%)
- Collecting and preparing data for ML solutions.
- Implementing data pipelines with AWS Glue, Kinesis, and S3.
- Applying data cleaning and feature engineering best practices.
Domain 2: Exploratory Data Analysis (24%)
- Visualizing and analyzing datasets to detect biases and anomalies.
- Identifying the right statistical methods for data insights.
- Selecting appropriate features for ML models.
Domain 3: Modeling (36%)
- Choosing the right ML algorithm for a business problem.
- Training and optimizing ML models in Amazon SageMaker.
- Applying hyperparameter tuning for model performance.
- Handling model evaluation metrics (accuracy, precision, recall, F1, etc.).
Domain 4: Machine Learning Implementation and Operations (20%)
- Deploying ML models using Amazon SageMaker endpoints.
- Monitoring and scaling ML models in production.
- Automating retraining, versioning, and pipeline management.
- Securing ML workflows with IAM, encryption, and governance.
What Changed in This Version (MLA-C01 vs Previous)?
The latest MLA-C01 includes updated AWS service coverage and refreshed domain weighting compared to the older MLS-C01:
- New topics added: SageMaker Autopilot, SageMaker Pipelines, and AI services like Amazon Kendra.
- Greater focus on MLOps and deployment practices.
- Less focus on purely theoretical ML algorithms (now balanced with practical AWS implementations).
- Weight shift: Modeling remains the heaviest domain, while data engineering now carries slightly less weight.
Registration and Scheduling
- Register through the AWS Training and Certification portal or Pearson VUE/PSI exam providers.
- Available in multiple languages, including English, Japanese, Korean, and Simplified Chinese.
- Offered both online proctored and test center formats.
Pricing and Vouchers
- Cost: $300 USD (standard pricing).
- Regional variations: Local taxes or exchange rates may slightly affect the final cost.
- Discounts:
- Students with a verified academic email may receive a 50% discount voucher through AWS Educate.
- AWS sometimes provides promotional vouchers during training events.
- Military and veterans may qualify for regional discount programs
Policies You Should Know
- You must wait 14 days before retaking a failed exam.
- Results are valid for 3 years.
- Identification: Two forms of government-issued ID may be required.
- Online exams require a quiet, private environment with webcam monitoring.
Scoring and Results
- Score range: 100 – 1,000.
- Passing score: 750.
- AWS uses a scaled scoring system (different questions carry different weights).
- Partial credit: Not officially given; questions are graded as correct or incorrect.
- Result delivery: Preliminary pass/fail is shown immediately; detailed score report is available within 5 business days in the AWS Certification account
Exam Day and Test Experience
- On-site proctoring: Arrive early with IDs; personal items stored in lockers.
- Online proctoring: Room scan required, webcam must remain on, no breaks unless stated
- Allowed items: No notes, phones, or devices. A digital whiteboard is provided for calculations.
- Interface tips: Flag questions for review, manage time carefully (65 questions in 170 minutes).
- Time management advice: Spend about 2 minutes per question, leaving time to review marked items
Study Plan and Resources
For Beginners (12 weeks):
- Weeks 1–2: Review ML basics (algorithms, supervised vs unsupervised, bias/variance trade-off).
- Weeks 3–4: Learn AWS ML services (SageMaker, Rekognition, Comprehend).
- Weeks 5–6: Practice data engineering with Glue, S3, and Kinesis.
- Weeks 7–8: Work on modeling and hyperparameter tuning in SageMaker.
- Weeks 9–10: Explore deployment, scaling, and MLOps.
- Weeks 11–12: Attempt full-length practice exams, review weak areas, and schedule the exam.
For Experienced Candidates (6 weeks):
- Week 1: Refresh ML fundamentals.
- Weeks 2–3: Deep dive into SageMaker and AWS ML ecosystem.
- Week 4: Focus on deployment and real-world scenarios.
- Week 5: Take practice tests and analyze mistakes.
- Week 6: Final revision and exam readiness check.
Recommended resources:
- AWS Skill Builder courses.
- AWS Whitepapers on ML, Data Lakes, and Security.
- Hands-on with SageMaker and AI services in a free-tier AWS account.
- Practice exams from providers like Whizlabs, Tutorials Dojo, or Cert Mage.
Certification Validity and Renewal
- Valid for 3 years.
- Renewal options:
- Retake the MLA-C01 exam.
- Earn a higher-level AWS certification (automatically renews lower-level ones).
- Use AWS continuing education credits (when available).
Career Outcomes
Job roles and salary ranges for AWS MLA-C01 holders:
|
Job Role |
Average Salary (USD) |
|
Machine Learning Engineer |
$120,000 – $160,000 |
|
Data Scientist |
$110,000 – $150,000 |
|
AI/ML Solutions Architect |
$130,000 – $170,000 |
|
Applied Scientist |
$115,000 – $155,000 |
|
Data Engineer (ML-focused) |
$105,000 – $145,000 |
Related or Next-Step Certifications
- AWS Certified Data Analytics – Specialty (for advanced data pipeline and analytics expertise).
- AWS Certified Solutions Architect – Professional (for enterprise-level ML solutions design).
- TensorFlow Developer Certificate (if focusing on ML frameworks).
- Google Cloud ML Engineer or Azure AI Engineer Associate (for multi-cloud expertise).
How This Exam Compares to Similar Certifications
- Compared to Google Professional ML Engineer, AWS MLA-C01 has a stronger focus on AWS service integration rather than general ML theory.
- Compared to Azure AI Engineer Associate, AWS MLA-C01 is more advanced and requires deeper ML knowledge, while Azure’s certification is more beginner-friendly.
About MLA-C01 Exam Questions
A Smarter Overview of Exam Questions for AWS MLA-C01 Preparation
For anyone looking to save time and study more effectively, authentic exam questions have become an essential part of the preparation plan. Practice Questions offer a direct, structured way to test your understanding of real exam topics. Instead of spending hours passively consuming material, learners can now challenge themselves using question-focused review methods. With MLA-C01, this method is especially useful because the exam requires more than just knowing the theory—you need to recognize patterns, understand AWS tools, and pick the best-fit solutions fast.
At Cert Empire, we take valid exam questions seriously. What we offer isn’t random or outdated—it’s shaped around real exam experience and practical logic. Our well-structured exam questions reflect how the actual MLA-C01 test is designed, helping users get familiar with tone, pacing, and decision-making. That’s why so many users trust Cert Empire to help them get exam-ready in less time, and with more confidence.
How Exam Questions Help You Study Better Than Before
The role of best exam questions has shifted in recent years. They are no longer seen as last-minute cram tools. Today, serious learners use authentic exam questions to fine-tune their prep and approach the exam from a place of familiarity. They are incredibly effective for:
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Because the MLA-C01 includes scenario-based decision making, using reliable exam questions helps you develop the ability to think critically about architecture, service limits, and model performance. That’s something passive study rarely teaches.
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FAQs About MLA-C01 Exam Questions and Cert Empire
Is the AWS Certified Machine Learning – Associate exam hard to pass?
Most people find it moderate in difficulty. It depends on your hands-on experience with both AWS and ML workflows. Practice and review help a lot.
What topics are most important in the MLA-C01 exam?
Model building, data preparation, and deployment hold the most weight in the exam. These areas appear more often in real questions.
Can exam questions really help you prepare for AWS certifications?
Yes, reliable exam questions help reinforce question logic and train your brain to identify patterns. They work best alongside real study methods.
How frequently are AWS exam questions updated on Cert Empire?
Cert Empire updates valid exam questions regularly to reflect any recent changes in exam format, questions, or AWS services.
Do employers accept certifications gained using exam questions?
Employers care more about your skills and knowledge. If you pass the test and show ability in interviews, prep method doesn’t matter.
What’s the best way to combine exam questions with other resources?
Use authentic exam questions as a reinforcement tool after going through courses, documentation, and labs. They help lock in what you’ve learned.
Is MLA-C01 still valuable in 2025?
Definitely. Machine learning skills are still in high demand, especially with cloud integration. This cert still holds serious value.
How accurate are the MLA-C01 exam questions from Cert Empire?
Our best exam questions are verified and curated based on real feedback. We update and review them regularly for accuracy and relevance.
Final Thoughts
Cert Empire continues to lead as the best exam questions website 2025, helping thousands of learners prep smart and pass confidently. What sets us apart is not just our quality but the way we design our authentic exam questions to match real-world exam patterns. For anyone prepping for the AWS MLA-C01 exam, our PDFs offer a clear, updated, and reliable method to get ahead. Cert Empire puts in the work so you can stay focused on what matters. Smart learners know where to go when the goal is to pass without wasting time.
FAQs
Frequently Asked Questions (FAQs)
What is the format of the AWS MLA-C01 exam?
The exam has 65 multiple-choice and multiple-response questions, and you get 170 minutes to complete it. Some questions are scenario-based, requiring you to choose the best solution.
Do I need coding experience for this exam?
Yes. While you don’t need to be an expert programmer, you should be comfortable with Python and ML frameworks like TensorFlow or PyTorch since many exam scenarios involve applying these skills.
Can I take the exam without prior AWS certifications?
Yes, you can. However, most successful candidates have already earned associate-level certifications (like Solutions Architect – Associate) to gain familiarity with AWS services before attempting MLA-C01.
How hard is the AWS MLA-C01 exam?
It is considered a specialty-level exam, meaning it’s more challenging than associate-level certifications. The difficulty comes from balancing ML theory with practical AWS service knowledge.
Is hands-on AWS experience necessary?
Absolutely. The exam expects you to know how to implement ML solutions using SageMaker, manage data pipelines, and deploy models. Hands-on labs or real-world experience make a huge difference.
How often should I renew the certification?
The AWS MLA-C01 certification is valid for 3 years. After that, you must either retake the exam or earn a higher-level certification to maintain your status.
What resources are best for exam preparation?
AWS provides official training, but many candidates also rely on practice exams, whitepapers, and online courses from providers like Coursera, Udemy, or Cert Mage for dumps and practice tests.
What is the pass rate for the AWS MLA-C01 exam?
AWS does not publish official pass rates. However, it is known to be one of the harder specialty exams, with candidates often needing 2–3 months of preparation.
Can I take the exam from home?
Yes. The AWS MLA-C01 exam is available as an online proctored exam, provided you meet system requirements and have a quiet, distraction-free environment.
What career opportunities open up after passing AWS MLA-C01?
Professionals with this certification often move into ML Engineer, Data Scientist, or AI Solutions Architect roles. It strengthens credibility and typically leads to higher salaries and leadership opportunities in AI/ML projects.
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Quiana Monroe (verified owner) –
The MLA-C01 exam wasn’t as hard as I expected. I used practice questions and study resources to get familiar with the exam format. It was a great prep and I passed comfortably.