Amazon Web Services is a market leader when it comes to delivering cloud-based services for global enterprises. As more businesses have started recognising AWS-certified experts and professionals, there has been a steady growth in the number of people who are looking to get AWS certifications.

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AWS Machine Learning Certification

Machine Learning is an application of Artificial Intelligence, which enables systems to automatically learn and evolve from experience rather than having to be programmed or using any human intervention. Machine Learning certification requires training and skill development, and validates your expertise in designing, maintaining, implementing and deploying Machine Learning (ML) solutions for your organisation.

How to Pass the AWS Machine Learning Certification

The AWS Deep Learning exam helps developers to identify patterns using algorithms and also tests your ability to run and design workloads on AWS Cloud. Before applying for this certification, you need to meet the following criteria:

• 1-2 years of experience in developing, architecture and running Machine Learning (ML) or deep learning workloads on AWS Cloud.
• Experience in Machine Learning (ML) and deep learning frameworks and in performing hyperparameter optimisations.
• Have the ability to follow operational, deployment and model training best practices.

Also Read - Boost your IT Career with an AWS certification

Who Should Take the AWS Machine Learning Certification Training?

This certification is designed to benefit many job roles. This includes

1. Cloud administrators
2. System administrators
3. Cloud architects
4. Solutions architect
5. Database administrator
6. Data architect
7. Data administrator
8. Network administrator
9. Developer
10. Security engineer
11. Business intelligence professional
12. Experienced AWS administrator
13. Software developer

AWS Machine Learning Certification Study Guide

When you take the MLS-C01 exam, there are 4 domains that you need to focus on:

Domain 1: Data Engineering

This domain carries 20% weightage in your exam. It tests the following skills -

• Creating machine learning data repositories
• Implementing and identifying data ingestion solutions
• Implementing and identifying data transformation solutions

Domain 2: Exploratory Data Analysis

In this domain, you will cover data for machine learning and modelling concepts. It carries 24% total weightage and includes the following sections -

• Preparing and sanitizing data for modelling
• Performing feature engineering
• Visualising and analysing data for machine learning

Domain 3: Modeling

Modeling carries 36% weightage, more than all the other domains because this is an important focus area. It includes the following sections -

• Framing business problems as machine learning problems
• Training machine learning models
• Select the correct model for a given machine learning problem
• Performing hyperparameter optimisation
• Evaluating machine learning models

Similar Post: AWS Certifications List and Cost 2022

Domain 4: Machine Learning Implementation and Operations

This domain also covers 20% of your total marks. It is the final domain in your exam and includes concepts of machine learning services and implementation. The topics covered in this domain are -

• Building machine learning solutions for availability, resiliency and performance
• Recommending and implementing the correct machine learning services for a given problem
• Applying basic AWS security solutions to machine learning problems
• Deploying and operationalising machine learning solutions

Very briefly, here are the topics you will need to prepare for:

Machine Learning

1. Exploring Data Analysis
   • Feature selection and engineering
   • Handle missing data
   • Handle unbalanced data
2. Modeling
3. Evaluation

AWS Machine Learning

1. Sage Maker
2. Sage Maker Ground Truth
3. Comprehend
4. Lex
5. Polly
6. Rekognition

Analytics

1. Security, identity and compliance
2. Management and Governance tools
3. Storage

The Result:

• Your test will be scored from 100 to 1000.
• To pass, you need 750 or more.
• The exam result will be mailed to you within five working days after you have given the exam.
• The AWS Machine Learning Speciality exam is based on a pass or fail format.
• You need to pass overall. Passing individual sections is not mandated.

The Questions:

• The questions in the AWS Machine Learning Speciality exam are multiple-choice questions. There are also some multiple responsive questions where there can be more than one correct answer.
• No marks are deducted for the wrong answer
• You will also find some portions that won’t have any marks or score mentioned. That is just to collect general information from you and will not have any effect on your exam.

ALSO Read: Overview of AWS CLI (How to Install, Configure AWS CLI in Windows/Linux/Mac/Unix)

Career and Certification Path for AWS Machine Learning Professionals

The Machine Learning path has been designed so that professionals can examine their skills and experience based on developing, training, tuning and deploying Machine Learning (ML) models using AWS cloud services.

1. Path for data scientists:

This Machine Learning (ML) path is meant for professionals and aspirants skilled in statistics, mathematics and analysis, and are looking to become experts in Machine Learning within their organisation.

2. Path for developers:

This Machine Learning path is for software developers and builders. It teaches you how Artificial Intelligence (AI) and Machine Learning (ML) can together help you to innovate better and partner with Data scientists to innovate using Machine Learning technologies and solutions.

Practice Makes Perfect:

When it comes to preparing the best way possible, remember to enroll in a high-performance AWS Certification, and do as many practice tests as you can. But most importantly, stay calm.

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