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3 Advantages of the AWS Developer Certification for Machine Learning Engineers

The demand for AWS (Amazon Web Services) services is flourishing as it becomes an essential element for businesses. Engineers having AWS certification are enjoying several benefits as it has created an easier path to pursue in cloud computing. Thus, many students are now joining AWS Developer training courses.

Many AWS certifications are available, divided into four main categories: Foundational, Associate, Professional, and Speciality. It’s a tough decision to choose which certification will work best for the candidate. To find more information about the importance of branding, you should try Ways to Handle Bad Amazon Reviews for Amazon sales

People usually struggle and choose the wrong certification, though candidates should always choose based on their skills. Candidates who have basic technical knowledge should start from associate level and then can go for professional level, followed by the speciality course. 

There is also a speciality certification available in machine learning which requires at least two years of experience in developing, architecting, and running ML or deep learning workloads in the AWS Cloud. The machine learning engineers with fewer years of experience or no experience should start with associate courses rather than starting directly with the speciality courses. Starting with basics will help you build a better foundation, and thus there would be fewer chances of quitting mid-way.

The fresh engineer graduates are currently taking an interest in pursuing these AWS certifications. This article includes reasons why a machine learning engineer should start with an associate-level developer certification rather than going for a machine learning speciality certification. Before that, let’s give a quick look at what precisely this certification is. 

What is AWS Developer Certification?

●     AWS Developer certification is an associate-level certification offered by Amazon.

●     It can be earned by clearing an exam of 130 minutes duration. Students appearing for it need to pay a fee of about $150 and an additional amount of $20 if they plan to attempt a practice exam.

●     This certification is specially designed for candidates with hands-on experience of about 1-2 years in developing and maintaining AWS-based applications.

Some of the prerequisites the candidates should have to pursue this certification are listed below.

●     They should have an in-depth understanding of at least one high-level programming language.

●     They should understand the core of AWS services, uses of the services, and basic AWS architecture best practices.

●     They should have skills in using AWS for developing, deploying, and debugging cloud-based applications.

●     They should have the skills to write codes for serverless applications.

●     They should have the ability to use AWS service APIs, AWS CLI, and SDKs to write applications.

How is AWS Developer Certification Beneficial for Machine Learning Engineers?

Machine Learning freshers who do not have sufficient experience or do not fulfill the requirements can go for an associate-level AWS developer certification course. Some of the benefits that machine learning engineers will find in this certification are explained below.

AWS Fundamentals

●     It is slowly becoming important that Machine Learning Engineers who want to build a career in the cloud should know AWS fundamentals. This is mainly because AWS occupies almost 48% market share in cloud services.

●     AWS is the top-most player in the cloud computing market, and many significant and small businesses use AWS services, ranging from startups to well-established Fortune 500 firms. Therefore knowledge of AWS fundamentals could come in handy for the candidate.

●     Some of the fundamentals that will be introduced in the certification are IAM, VPCs, NAT Gateways, Internet Gateways, Security Groups, and many more. These’re quite helpful when it comes to the role of a Machine Learning Engineer.

Machine Learning Models

●     The AWS developer certification can help machine learning engineers learn about deploying and consuming machine learning models.

●     If Machine Learning Engineers could deploy the models made by data scientists, then the model could be easily passed for production.

●     Deploying skills are primarily found in software engineering and DevOps; therefore a machine learning engineer can learn this skill through the developer’s certifications.

CI/CD Pipelines

This certification also gives some core benefits related to the technical field of a Machine Learning Engineer.

●     The developer certification can help ML engineers learn to use AWS services like AWS CodeCommit, CodeDeploy, CodeBuild, CodePipeline, X-ray, Cloudwatch, etc.

●     These services can help ML engineers automate the deployment process and will be beneficial for the whole team.

●     This skill can help ML engineers help the DevOps team too. 

AWS is becoming so popular that even candidates from non-technical fields are joining its online training courses. As various companies constantly look for hiring cloud solution experts, a certificate in AWS can be your chance to enter a profitable career. The average salary a cloud expert in India gets is somewhat around ₹20 lakh per annum, which is pretty impressive. You must read about CI CD Pipeline Jenkins because it’s one of the best programs for Cyber Security.

All these facts become more interesting and important when you are a tech person, especially someone oriented towards Machine Learning. A certificate in AWS sharpens your skills and gives additional knowledge that is helpful for a machine learning career. Therefore, it’s better not to wait and join one of the best AWS courses available online. With consistency and determination, you can make the best out of the combination of AWS and ML.

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Cary Grant
Cary Grant
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