AWS Certified Machine Learning Specialty Practice Exam
AWS Certified Machine Learning – Specialty
About AWS Certified Machine Learning – Specialty Practice Exam
AWS Certified Machine Learning Specialty certification exam checks the knowledge of the candidates in planning, applying, deploying, and maintaining machine learning (ML) solutions. However, this exam is best for professionals in the role of development and data science professionals. Further, it also assesses candidates’ skills for creating, training, tuning, and deploying machine learning (ML) models using the AWS Cloud.
Who should take the exam?
The AWS Certified Machine Learning Specialty Exam is suitable for candidates having 2 or more years of hands-on experience in developing, architecting, and running ML or deep learning workloads in the AWS Cloud.
Skills Validated
- Selecting and explaining the suitable ML method for a provided business problem
- Identifying suitable AWS services for implementing ML solutions
- Planning and implementing scalable, cost-optimized, reliable, and secure ML solutions
AWS Certified Machine Learning – Specialty Exam Details
- Exam Format: Multiple choice, multiple answers
- Exam Type: Specialty
- Total Questions: 65 questions
- Exam Time: 180 minutes to complete the exam
- Exam Cost: $300 USD
- Exam Languages: Available in English, Japanese, Korean, and Simplified Chinese
Recommended AWS Knowledge
Candidate for this exam must have at least 1-2 years of applied experience in developing, architecting, or running ML/deep learning workloads on the AWS Cloud, along with -
- Ability in expressing the intuition behind basic ML algorithms
- Experience in executing basic hyperparameter optimization
- Experience with ML and deep learning frameworks
- Ability in following the model-training best practices and deployment and operational best practices
AWS Certified Machine Learning – Specialty Practice Exam Course Outline
The exam covers the given core topics as per the latest exam updates -
Module 1: Describe Data Engineering (20%)
- Creating data repositories for machine learning.
- Identifying and implementing a data-ingestion solution.
- Identifying and implementing a data-transformation solution.
Module 2: Describe Exploratory Data Analysis (24%)
- Sanitizing and preparing data for modeling.
- Performing feature engineering.
- Analyzing and visualizing data for machine learning.
Module 3: Describe Modeling (36%)
- Framing business problems as machine learning problems.
- Selecting the appropriate model(s) for a given machine learning problem.
- Training machine learning models.
- Performing hyperparameter optimization.
- Evaluating machine learning models.
Module 4: Describe Machine Learning Implementation and Operations (20%)
- Creating machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance.
- Recommending and implementing the appropriate machine learning services and features for a given problem.
- Applying basic AWS security practices to machine learning solutions.
- Deploying and operationalizing machine learning solutions.
What do we offer?
- Full-Length Mock Test with unique questions in each test set
- Practice objective questions with section-wise scores
- In-depth and exhaustive explanation for every question
- Reliable exam reports to evaluate strengths and weaknesses
- Latest Questions with an updated version
- Tips & Tricks to crack the test
- Unlimited access
What are our Practice Exams?
- Practice exams have been designed by professionals and domain experts that simulate real time exam scenario.
- Practice exam questions have been created on the basis of content outlined in the official documentation.
- Each set in the practice exam contains unique questions built with the intent to provide real-time experience to the candidates as well as gain more confidence during exam preparation.
- Practice exams help to self-evaluate against the exam content and work towards building strength to clear the exam.
- You can also create your own practice exam based on your choice and preference
