AWS Certified Machine Learning Specialty Certification - Complete Guide

AWS Certified Machine Learning Specialty Certification – Complete Guide

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In this blog, we are going to guide you through the complete process of AWS Certified Machine Learning Specialty Certification from where you can opt for the courses, what are the topics that are going to be covered in this certification and how can you prepare for this certification.

Not sure Which Machine Learning Certification is Best for You? Check out our blog post!

AWS Certified Machine Learning

AWS Certified Machine Learning  Specialty is a certification provided by Amazon in the field of machine learning. There is a machine learning path defined by AWS to complete this certification. The machine learning path for exam preparation is also defined by the AWS to help to study and prepare for the exam. We look into this further is this blog.

There are various abilities that are being validated by this certification. They are listed below”

  • Select and justify the appropriate machine learning approach for the business problems.
  • Identifying appropriate Amazon Web Services to implement machine learning solutions.
  • Designing and implementing scalable, cost-optimised, reliable, and secure machine learning solutions.

Further, this certification is divided into multiple domains and each domain has a specific set of percentages which represents the total percentage of 100 during the exam. These domains are listed below 

  • Domain 1: Data Engineering (20% of scored content)
  • Domain 2: Exploratory Data Analysis (24% of scored content)
  • Domain 3: Modeling (36% of scored content)
  • Domain 4: Machine Learning Implementation and Operations (20% of scored content)

Pre-requisites Provided By AWS For This Certification

  • You need to ask least to have experience of one to 2 years in the field of machine learning slash deep learning and the workloads on the cloud.
  • You need to have the ability to express the intuition behind the machine learning algorithm.
  • you need to have experience in performing basic hyperparameter optimization.
  • you need to have experience with machine learning and deep learning frameworks.
  • The ability to follow the model training practices.
  • The ability to follow the deployment and operational practices.

Machine Learning Path 

A machine learning path is specifically designed to help you to prepare for the machine learning certification that machine learning- specialty certification this learning path provides interactive content and consists of hands-on labs and video courses. The image below represents the machine learning path for exam preparation.

AWS Certified Machine Learning Specialty Certification Path

Machine Learning Exam Basics: It helps to explore the services for building training and deploying models for machine learning.

Process Model: CRISP-DM on the AWS Stack: it helps you to have a walk-through of CRISP- DM methodology and the framework hey and then apply the models to your daily work. 

The Elements of Data Science: learn how to build and continuously improve your machine learning models. 

Storage Deep Dive Learning Path: Moving from fundamentals to technical and also having a deep dive to the advanced AWS storage.

Machine Learning Security: It covers the above products and services that help you to seeker applications and the environment. 

Developing Machine Learning Applications: Explore Amazon’s fully managed machine learning platform. 

Types of Machine Learning Solutions: learning 3 different disciplines of machine learning – computer vision, natural language processing, and chat boards having some practical experience with AWS services.

AWS Certified Machine Learning – Specialty: finally getting ready for the exam with all the skills required to build and tune the data models for machine learning and helps you to grow in the field of machine learning. 

What You Will Be Learning From AWS Machine Learning – Specialty Certification?

  • E2E Machine learning life cycle
  • Data collection
  • Transformation
  • Usable and efficient Machine learning models
  • Data pre-processing
  • Training models
  • Validating and implementation of models

Service You Will Be Learning And Using For This Exam

AWS Machine Learning
Storage
  • S3
  • Relational database service (RDS)
  • Dynamo DB
  • Elastic Block Storage (EBS)
  • Redshift
Data Processing
  • Amazon Glue
  • Kinesis
  • Athena
  • QuickSight
  • Elastic MapReduce
  • Apache Spark
Machine Learning Services
  • Rekognition
  • Polly
  • Lex
  • Comprehend
  • Transcribe
  • Translate
  • Elastic Interface
Security
  • KMS Encryption
  • Security groups
Management and Other Services

Courses For AWS Machine Learning – Specialty Certification

There are various places from where we can prepare for this course the only thing is you need to select a proper course that covers all the sections that are required for this certification. Since I have covered all the topics that are required for this certification you can either opt for a course with a different service in AWS or it’s better to choose a course with a complete AWS machine learning specialty certification portion.

Whizlabs covers all the portions that are required for this certification in addition it provides you with the labs on which you can have your AWS hands-on experience to make better learning progress as well as they also provides a set of papers to solve to get the exam experience the whistling course for AWS Machine Learning Specialty Certification is pasted below.

Preparing For AWS Certified Machine Learning Specialty 

To prepare for the AWS machine learning specialty exam it’s based on an individual and their learning process here is just a suggestion how can you prepare for the exam which might help you with a much better understanding?

If you are new to AWS or have some experience on it, I would suggest that you understand the services first, that are used for machine learning. It will help you to understand the machine learning process in a much simpler way as you already know how the services work and you have some experience with the services.

Check out Whizlabs Free Test with 300+ Practice Questions and Exhaustive Explanations today! No Credit Card is needed to attempt the test!

There is another way to do this, If you are new to the AWS you better go for the hey AWS cloud practitioner certification which cost around $100. This certification will help you the to gain the basic understanding of the services in the AWS. Once you have cleared this exam you will receive a 50% off gift voucher from Amazon for your next exam which can reduce your $300 fees to $150. So in this way you can save $50 on your exam and also get to certification.

Details Regarding the Exam

Format: – A total of 65 questions and each question are multiple choice. 

Examination method: – onsite center or online exam.

Time: – 180 minutes

Cost: – 300 U.S. dollars 

Language available: – English, Japanese, Korean and simplified Chinese 

Certification Validity: – 3 years

Model Exam price: – 40$ from AWS

FAQs

Q1. How many days will it take to prepare for this exam? 

Ans. It depends on the learning and grasping power, but we would suggest to at least have 2-3 months of preparation.

Q2. Does Whizlabs provide a cloud practitioner certification course? 

Ans. Yes, we have the course. Here is the link https://www.whizlabs.com/aws-certified-cloud-practitioner/ 

Q3. Does Whizlabs courses cover all the required topics for this exam? 

Ans. Yes, It does cover all the topics.

Q4. How many exam model paper are present for machine learning certification in which lab course?

Ans. There are total of 7 paper to solve.

Q5. Do we receive 50% off voucher after every exam we clear?

Ans. Yes, we do receive the voucher.

Q6. What are the number and length of videos in this course?

Ans. There are total of 71 videos which in total is length of 9+ hours.

About Pavan Gumaste

Pavan Rao is a programmer / Developer by Profession and Cloud Computing Professional by choice with in-depth knowledge in AWS, Azure, Google Cloud Platform. He helps the organisation figure out what to build, ensure successful delivery, and incorporate user learning to improve the strategy and product further.

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