The Amazon MLS-C01 Exam also known as the AWS Certified Machine Learning – Professional exam, is designed to validate your skills in building, training, tuning, and using machine learning models in the AWS cloud. Here are the main points of the exam.
Exam Overview
The AWS Certified Machine Learning – Professional MLS-C01 Exam Question validates advanced skills in building, training, tuning, and deploying machine learning models on AWS. It has 170 minutes of multiple options and multiple questions focusing on information engineering, data analysis, modeling and machine learning, and operations. Candidates must have at least 1-2 years of hands-on experience with AWS ML services such as Amazon Sage Maker, AWS Lambda. The test costs $300 and can be done at the testing center or online. Successful candidates will receive certifications that will increase their confidence and open up careers in machine learning and artificial intelligence at AWS.
Exam Format
- Type: Multiple choice and multiple response questions.
- Number of Questions: Typically 65 questions.
- Duration: 170 minutes (2 hours and 50 minutes).
- Delivery Method: Available at testing centers and online proctored exams.
- Languages Offered: English, Japanese, Korean, and Simplified Chinese.
MLS-C01 Exam Content Outline
AWS Certified Machine Learning – Professional (MLS-C01) exam content is divided into four main areas: data engineering (20%), data analytics (24%), modeling (36%), and machine learning and operations (20%). Assesses the candidate’s ability to create and implement pipelines, perform data visualization and analysis, select and train ML models, and deploy ML solutions on AWS. This exam tests skills in AWS services such as Amazon Sage Maker, AWS Lambda, and Amazon S3 to ensure candidates can solve real machine learning problems. Each area evaluates critical aspects of the machine learning lifecycle, from data preparation and training models to operations and maintenance.
Prerequisites
The AWS Certified Machine Learning – Professional MLS-C01 Exam is designed for individuals with extensive experience with AWS Machine Learning and Deep Learning. Prerequisites include 1-2 years of designing, architecting, and running machine learning workloads on AWS. Candidates must have expertise in machine learning techniques, machine learning algorithms, and hyperparameter optimization. It is important to understand key AWS services such as Amazon S3, AWS Lambda, Amazon RDS, Amazon Kinesis, AWS Glue, Amazon Sage Maker, AWS IAM, and AWS Key Management Service (KMS). Successful content analysis requires knowledge of data engineering, data analysis, and the workings of machine learning models.
MLS-C01 Exam Preparation Resources
MLS-C01Exam Guide:
This provides a detailed breakdown of the exam content and is essential for understanding the exam domains.
AWS Training and Certification:
AWS offers various training courses and practice exams.
Whitepapers and Documentation:
Reviewing AWS whitepapers, especially those related to machine learning and data analytics, can be helpful.
MLS-C01 Exam Books and Online Courses:
There are several books and online courses available that cover the material needed for this exam.
Hands-on Practice:
Utilizing AWS services to build and deploy machine learning models is crucial for practical understanding.
MLS-C01 Exam Recommended Knowledge and Experience
Passing the AWS MLS-C01 exam requires 1-2 years of ML experience on AWS. Core skills include the fundamentals of machine learning, traditional methods, and optimization. Experience with AWS services like S3, Lambda, RDS, Kinesis, Glue, Sage Maker, IAM, and KMS is essential. Expertise in data engineering, data mining and machine learning is an advantage. Candidates must understand data collection, transformation, architecture, model selection, training, development, deployment and maintenance. Effective planning includes AWS training sessions, hands-on activities, and real-world machine learning projects for clinical diagnosis.
What does it take to earn this certification?
Earning the AWS Certified Machine Learning – Specialization (MLS-C01) certification requires a solid foundation in machine learning and extensive experience with AWS services. Candidates must understand information engineering, data analysis, training models, and operational deployments. Preparation includes exploring AWS-native machine learning services, such as Amazon SageMaker, and practicing data pipelines, modeling, and machine learning operations. The exam contains 65 multiple choice and multiple answer questions and must be completed in 170 minutes. A score above 750 out of 1000 points indicates that the candidate is performing well. Great learning resources include AWS courses, free resources, and hands-on labs. Successful candidates will receive a certification that builds confidence and opens doors to advanced careers in machine learning and artificial intelligence.
Who should take this exam?
The AWS Certified Machine Learning – Professional (MLS-C01) exam is ideal for professionals who have experience with machine learning and want to demonstrate their skills in applying the AWS Cloud to the problem of machine learning solutions. It is designed for data scientists, engineers, software developers, and IT professionals using ML models and AWS services. Candidates must have in-depth knowledge of machine learning concepts, algorithms, and frameworks, as well as experience building and implementing machine learning models on AWS. This certification is suitable for individuals who want to advance their careers in data science, artificial intelligence, and cloud computing as it proves expertise in performing complex machine learning tasks using AWS technology.
MLS-C01 Exam Scoring
The passing score for the AWS Certified Machine Learning – Specialty (MLS-C01) exam is 750 out of 1000.
Preparing for the AWS Certified Machine Learning – Specialty exam requires both theoretical knowledge and practical experience with AWS services. Making the most of the resources provided and gaining experience is the key to success.
