AWS SageMaker I Machine Learning Course I Training

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Its not mandatory to take the certification exam after the course, you simply use the course for learning a new subject and enhance your knowledge.

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What will you learn from this course?

In this complete certification course, you will learn

How to build, execute, and examine different machine learning models through Amazon Web Services.

About different algorithms that are already built in Sage Maker i.e., Linear Learner, Principal Component Analysis, XG-Boost, and K-Nearest Neighbors.

How to explain and run picture and test labeling jobs in Sage Maker.

How to read, clean, and visualize data without using any type of code.

Learn how to automate your workflow without using any code through AWS Lambda and SageMaker framework.

What is AWS?

AWS is a company created by Amazon and it stands for Amazon Web Services. This firm provides the access to cloud computing platforms and APIs for governments, people, or businesses. AWS offers software tools and computer processing capacity through these web computing services.

An Amazon subsidiary called Amazon Web Services, Inc. (AWS) offers individuals, businesses, and governments pay-as-you-go cloud computing systems and APIs. Through AWS server farms, these cloud computing web solutions offer software tools and distributed computer processing capacity. One of these services, Amazon Elastic Compute Cloud, provides users with a virtual cluster of computers that is constantly accessible via the Internet. The majority of the features of a real computer are replicated by AWS' virtual machines, including hardware processing units (CPUs) and graphics processing units (GPUs), local/RAM memory, a choice of operating systems, networking, hard-disk/SSD storage, and pre-installed application software such as web servers, databases, and customer relationship management. For illustration, Amazon Elastic Computer Cloud is among the popular AWS cloud services that allow users to use virtual servers that are accessible around the clock.

What is AWS SageMaker?

A cloud-based machine-learning platform called Amazon SageMaker enables customers to construct, design, develop, test, and deploy machine-learning algorithms in a hosted environment that is prepared for production. Using AWS SageMaker has a number of advantages.

Machine learning has many applications and advantages. Advanced analytics for client data and the detection of security threats on the back end are two examples. Even for seasoned software developers, implementing ML models is challenging. Amazon SageMaker makes an effort to make the process simpler. Utilizing widely used algorithms and other resources expedites the machine-learning process.

What is meant by Machine Learning in Amazon SageMaker?

The process of machine learning is iterative. To process data gathering, special hardware and workflow tools are needed. A data science team often creates ML models in two processes or pipelines: training and inferencing. A computer is taught to operate in a particular way through data training, which is based on the identification of recurrent patterns in data sets. The data is then inferred from or trained to react to fresh data patterns.

Software development teams incorporate the final model within service or product application program interfaces after data scientists refine the machine learning model (APIs). Many businesses lack the resources to hire experts and allocate resources to AI development. Utilizing a combination of technologies, AWS SageMaker automates time-consuming manual operations while reducing hardware expenses and human error.

The AWS SageMaker toolkit includes parts for machine learning modeling. SageMaker templates abstract software functions. They offer a platform for creating, honing, maintaining, and implementing machine learning algorithms at scale on the Amazon cloud service.

How much does a specialist in machine learning for AWS Sagemaker make?

The compensation range for an AWS Sagemaker professional is between $84k and $173k annually, according to several sources. Highly lucrative employment opportunities are available in this industry for you. Through Brainmeasures training, you can obtain this position. Start learning now by enrolling in this course.

What prerequisites are there for this course?

Python proficiency is necessary.

Who may enroll in this course?

Developers interested in learning more about machine learning at Amazon

Newly qualified data scientists who want to further their careers and build their portfolios

experienced consultants eager to apply AI/ML on AWS to transform businesses.

Tech enthusiasts who are curious about computer science and artificial intelligence but are fresh to the topic and want to gain hands-on experience with AWS.


Course Syllabus

Getting Started 11 lectures 17 mins
Introduction Preview 01:42
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Please login to access the syllabus.


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What makes AWS SageMaker I Machine Learning Course I Trainingunique?


The video online course is well-structured and comprehensive.


The topics are organized in proper sequence to enable the candidate understand them easily.


Easy to understand and implement in real life.


Sufficient pictures, tables, graphs have been provided to make this online Course more attractive to the readers.


Final certification exam conducted under surveillance of trained human proctor.


We will ship your hard copy anywhere you ask for.

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    • Immediately after taking the test you can check your scores with detailed.
    • Immediately download soft copy certificate.
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    • Online Video course by Highly qualified Trainers.
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    • If you have any query our trainers are accessible easily.
    • Send your questions and get answers within 7 working days.
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    • Final exam is proctored – you will be monitored throughout, this is done using our high-end Proctor software, so that you need not go to any special location but take it from your own PC.
    • This testing format matches world-class testing standards.
    • Certificate will mention wording proctored to prove the authenticity of your knowledge.
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    • You can take any number of retakes if you are not satisfied with your score or failed to pass.
    • Test re-takes are paid, each retake is worth $ 50.
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