Machine learning has become the trend for IT enthusiasts. AWS Machine Learning specialty exam is designed to handle Amazon Web Services product that allows a developer to discover patterns in end-user data through algorithms, construct mathematical models based on these patterns and then create and implement predictive applications. Every organization wants its most important asset – workforce to be always updated in the domain of technology. And if you’re working with the IT company then keeping yourself updated on the technological side is necessary for saving your position and reputation. The certifications also show you dedication towards your work and your organization. Keeping yourself updated makes you feel more confident and also helps you to stand out in the crowd.
AWS Machine Learning Certification was accepted as most difficult certification among all other certifications offered by amazon. These kind of IT certifications have been challenging to crack and requires proper knowledge of the subject. Also, merely getting the certificate is not enough. You have to develop a complete understanding of the subject to know its application in reality. All this can be achieved if you have right set of resources and a proper schedule or your strategy. So, if you are preparing to ace this exam, you are at right destination as we provide you all the necessary details with our AWS Machine Learning Tutorials
What is Amazon machine learning specialty exam?
The AWS Certified Machine Learning – Specialty (MLS-C01) examination is intended for individuals who perform a development or data science role. This exam validates an examinee’s ability to build, train, tune, and deploy machine learning (ML) models using the AWS Cloud.
It evaluates an examinee’s ability to design, implement, deploy, and maintain ML solutions for given business problems. It will validate the candidate’s ability to:
- Select and justify the appropriate ML approach for a given business problem.
- Identify appropriate AWS services to implement ML solutions.
- Design and implement scalable, cost-optimized, reliable, and secure ML solutions.
The exam will test you on the following major domains and the weightage of each domain is given along.
- Domain 1: Data Engineering – 20%
- Domain 2: Exploratory Data Analysis – 24%
- Domain 3: Modeling – 36%
- Domain 4: Machine Learning Implementation and Operations – 20%
AWS Machine Learning Specialty Interview Questions
Practice with AWS Machine Learning Specialty Interview Questions and clear your interview successfully with Confidence.
The AWS Machine Learning Specialist Certification exam consists of 65 scenario-based questions in order to evaluate a candidate’s ability to solve different business problems. This is a specialty exam and duration for the exam is 170 minutes. The AWS Machine Learning Certification Cost is $300 although the prices may vary from place to place. You can schedule the exam at Pearson VUE or PSI. The type of questions asked are multiple choice questions and multiple response questions. AWS machine learning specialty exam is measured on a scale of 1 – 1000 and passing score is 750 marks. AWS machine learning specialty exam is available in English, Japanese, Korean, and Simplified Chinese.
|Name of the exam||AWS machine learning specialty|
|Exam duration||170 minutes|
|Format||Multiple choice questions and multiple response questions|
|Passing score||750 marks|
|Languages available||English, Japanese, Korean, and Simplified Chinese|
AWS Machine Learning Certification Prerequisites
Amazon recommends that a candidate appearing for the AWS machine learning specialty exam shall have following knowledge and experience:
- Firstly, 1-2 years of experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud.
- Subsequently, the ability to express the intuition behind basic ML algorithms.
- Also, Experience performing basic hyperparameter optimization.
- Furthermore, Experience with ML and deep learning frameworks.
- Also, the ability to follow model-training best practices.
- Finally, the ability to follow deployment and operational best practices.
Upon completing your exam, you will receive a pass or fail notification on the testing screen. Most of Amazon exams use a scale-scoring method. You will receive an email confirming your exam completion. Your detailed exam results will be available within five business days of completing your exam.
Exam Retake Policy
The candidates who do not pass an exam must wait 14 days before they are eligible to retake the exam. There is no limit on exam attempts until the candidate has passed. For each exam attempt, the full registration price must be paid i.e. $300 in the case of AWS machine learning specialty exam.
How to register for the AWS Machine Learning Specialty Exam?
To register for an exam, sign in to aws.training and click Certification in the top navigation. Next, click the AWS Certification Account button, followed by Schedule New Exam. Find the exam you wish to take and click either the Schedule at PSI or Schedule at Pearson VUE button. You will then be redirected to the test delivery provider’s scheduling page, where you will complete your exam registration.
Path for AWS Machine Learning Professionals
AWS has designed Machine Learning path so that Professionals can examine their skills and experience based on developing, tuning, training and deploying Machine learning models using services of AWS cloud.
For Specialty Level Machine Learning path in AWS have two paths,
Machine Learning Path for Data Scientist
This path is for individuals who are skilled in statistics, mathematics and analysis and want to become an expert in Machine learning in their organization. In this you will learn about the frameworks and analysis tools which are used for improving workplace.
AWS Machine Learning Path for Developer
Machine Learning Developer path is for software developers and builders. This will help you learn how Artificial Intelligence and Machine learning together can help you get better partner with Data Scientist to innovating with Machine learning technologies.
Other exam policies
Before you sit for the exam, make sure that you have all the information related to exam policies and terms and conditions of the exam by visiting official site. Do not miss out on anything important before sitting for the AWS Machine Learning Specialty Certificate exam.
To know more, visit: FAQs for AWS machine learning specialty exam
The Amazon AWS Machine Learning Certification exam will test you on the basis of following domains. The compositions of the domains are also fixed. Let us have a look at the AWS Machine Learning Certification Course Outline
Domain 1: Data Engineering
- Firstly, Create data repositories for machine learning. (Amazon documentation for this module: Using Amazon S3 as a data repository, Using Amazon Redshift as a data source, Using Amazon RDS Database as an Amazon ML Datasource)
- Secondly, identify and implement a data-ingestion solution. (AWS Documentation: Data Ingestion methods in AWS, Understand how data is ingested with Amazon SageMaker and a Data Lake on AWS, How Kinect Energy ingests data to forecast energy prices)
- Thirdly, identify and implement a data-transformation solution. (AWS Documentation: N-gram Transformation, Orthogonal Sparse Bigram (OSB) Transformation, Lowercase Transformation, Data Rearrangement: Create datasource based on a section of the input data)
Domain 2: Exploratory Data Analysis
- Firstly, sanitize and prepare data for modelling. (AWS Documentation: Prepare your data in Amazon Machine Learning, Use Amazon SageMaker Ground Truth for Data Labeling, Prepare data in Amazon SageMaker)
- Secondly, perform feature engineering. (AWS Documentation: Understanding the Importance of Feature Transformation, Feature Processing in Amazon Machine Learning, Feature Processing using Spark & Scikit-learn in SageMaker)
- Lastly, analyze and visualize data for machine learning. (AWS Documentation: Analyzing Data with Amazon Machine Learning, Explore, Analyze & Process data, Visualizing the distribution of data, Visualizing insights for binary models, Visualizing insights for Regression models)
Domain 3: Modeling
Firstly, frame business problems as machine learning problems. (AWS Documentation: Resources from AWS: Formulating the Problem, Resources from Amazon: Solving Business Problems with Amazon ML)
- Subsequently, select the appropriate model(s) for a given machine learning problem. (AWS Documentation: Amazon Machine Learning: Types of ML Models)
- Also, train machine learning models. (AWS Documentation: Build, Train, and Deploy a Machine Learning Model with SageMaker, Train a Model with Amazon SageMaker, Incremental training of model in SageMaker, Training with Amazon EC2 Spot Instances, Train a Deep Learning model)
- Furthermore, perform hyperparameter optimization. (AWS Documentation: Understanding the Training Parameters, Hyperparameters available in Amazon ML, How does Hyperparameter Tuning work?, Defining Hyperparameter Ranges, Best Practices for Hyperparameter Tuning)
- Finally, evaluate machine learning models. (AWS Documentation: Binary Model Insights, Multiclass Model Insights, Regression Model Insight, Understand the Cross-validation technique for evaluating ML Models, Evaluating Model Fit: Underfitting vs. Overfitting)
Domain 4: Machine Learning Implementation and Operations
- Firstly, build machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance. (AWS Documentation: Review the ML Model’s Predictive Performance, Deploy Multiple Instances Across Availability Zones, Amazon SageMaker: Infinitely Scalable Machine Learning Algorithms, Review this Whitepaper: Power Machine Learning at Scale)
- Subsequently, recommend and implement the appropriate machine learning services and features for a given problem. (AWS Documentation: Protect Data at Rest, Protect Data in Transit, Secure access to Amazon SageMaker with IAM Roles)
- Also, apply basic AWS security practices to machine learning solutions.
- Lastly, deploy and operationalize machine learning solutions.
2 ways to deploy your model:
a. Amazon SageMaker hosting services (to set up an endpoint to get predictions) (AWS Documentation: Deploy a Model on Amazon SageMaker Hosting Services)
b. Amazon SageMaker batch transform (to get predictions on the entire dataset) (AWS Documentation: Overview: Deploying a model with Amazon SageMaker batch transform, Deploy the Model with Batch Transform, Troubleshoot Amazon SageMaker Model Deployments)
Preparatory Guide for AWS Machine Learning Specialty Exam
AWS Machine Learning Specialty Preparations are quite challenging one and requires a lot of dedication and hard work combined with right set of resources to ace the exam. There are numerous resources but we need to figure out the ones which are beneficial for us. The resources through which we can gain more in less time. This will help in increasing the time that will be available for practice and revisions. Let us look some handful resources that will help you in passing the exam with flying colors.
Resource 1: The Official learning path by Amazon
The official site of amazon recommends the hands-on experience along with the online training and sample papers in order to ace the exam. Always make sure to visit the official site to gather details about every detail of the exam. The official site provides knowledge about technical aspects about the exam and about the latest updates of the exam. There are many official resources that are made available the amazon for the exam. Amazon is also providing free webinars to help spread knowledge about the exam. in addition, amazon provides various classroom sessions and expert-led courses as listed below:
- Machine Learning Exam Basics
- Process Model: CRISP-DM on the AWS Stack
- The Elements of Data Science
- Storage Deep Dive Learning Path
- Machine Learning Security
- Developing Machine Learning Applications
- Types of Machine Learning Solutions
Branching content areas
- Communicating with Chat Bots
- Speaking of: Machine Translation and NLP
- Seeing Clearly: Computer Vision Theory
For more training options, you an visit Training Library by Amazon for machine learning.
Resource 2: Online training programs
There are many AWS Machine Learning Certification Training programs which are made available by the educational sites. You can find the training programs that are best suitable to you according to the syllabus and availability of time. There are online classes as well as instructor-led classes which offers interactive way of learning. You can clear your doubts without any hesitation and take the test series along with the courses from the same site.
Resource 3: Books
Books are the most valued resources for all time. You can refer to many books for AWS machine learning specialty exam. You can choose any book that covers the aspects of the syllabus and has the language according to your ease. There are many books available as:
- Mastering Machine Learning on AWS: Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow
- Machine Learning with Aws
- Effective Amazon Machine Learning
- Learning Amazon Web Services (AWS): A Hands-On Guide to the Fundamentals of AWS Cloud | First Edition | By Pearson
- Pragmatic AI an Introduction to Cloud Based Machine Learning
Also, you can enhance your learning with AWS Machine Learning Documentation and AWS Machine Learning White Papers.
Resource 4: Join study groups and discussions
You can join many study groups for improving your preparations and pooling different resources. Discussions help you test your knowledge. Try to form the groups with the people who are more interactive as this will help you in getting answers quickly. This will help to instill a competitive spirit in you and increase your performance.
Resource 5: Practice papers and test series
AWS Machine Learning Practice Exam is the only way out to pass the exam with a good score. The more you practice, the more your concepts will be clear. Always practice sample papers and take test series as much as you can. This will help to find your loopholes and will help to identify your weak areas. You will find the parts that you need to work more on and the parts that are fully prepared from the exam point of view. This is the most important part of preparation. Many reliable educational sites offer you sample papers and guarantee 100% success. Try a free practice test now!