If you have the Amazon AWS Certified Machine Learning – Specialty certification, you are able to validate your skills in building, tuning, deploying, and training machine learning models on AWS. It is created to prove your knowledge of the design, building, deployment, optimization, training, maintenance, and tuning of ML solutions while using AWS Cloud. This certificate also shows that you have the skills in choosing and justifying the appropriate ML approach for the given business problems. Also, you will be able to demonstrate the identification of the appropriate AWS services for the implementation of ML solutions.
Usually, this certification path is chosen by those individuals who perform artificial intelligence or machine learning development or want to land the data science role. The potential candidates are expected to have 2 years of hands-on experience. It includes their ability to develop, architect, and run ML or deep learning workloads in AWS Cloud. Besides that, it is important to be able to follow the operational best practices, model-training best practices, or deployment best practices when needed.
Amazon MLS-C01 is a qualification exam of this specialty-level certification. It consists of 65 questions of various types, including multiple choice as well as multiple response. The test lasts for 180 minutes and you will need to complete it during this time with 750 or more points in the overall score. To be sure that you pass this prerequisite exam with flying colors, you have to prepare for the following topics:
- Data Engineering – The first domain is all about the creation of data repositories for ML. This means that you should be able to identify data ingestion solutions or data transformation solutions and implement them;
- Modeling – If talking about this area, it includes the questions that assess your skills in performing the hyperparameter optimization and training the ML models. It is also vital to have knowledge of the ML models and understand how to evaluate them. The potential candidates should know about the models and be able to select the appropriate ones for the given machine learning problems. Moreover, having knowledge of how to frame the business problems as the ML ones is important as well;
- Exploratory Data Analysis – The next part covers the details of the analysis and visualization of data for ML, performance of feature engineering, as well as sanitization and preparation of data for modeling;
- ML Implementation & Operations – The last section of the exam covers the details of the basic AWS security practices and your ability to apply them to ML solutions. You should also have the skills in building machine learning solutions for scalability, resiliency, fault tolerance, performance, and availability. It will be a huge advantage to have knowledge of machine learning services and their features and possess the competence in recommending and implementing them for the given issues. You should also know how to deploy and operationalize machine learning solutions.
Further Career Path
Obtaining the AWS Certified Machine Learning – Specialty certification is a really good option for the data scientists who are interested in getting certified and validated by Amazon. If you add this certificate to your resume, you will have more chances to select the best position in the market that offers a higher salary. But you need to remember that the IT world is constantly changing and new skills are required from the IT professionals. Thus, the vendor offers to renew its certifications every 3 years. It is important to keep track of the status changes and recertify when the time comes to ensure your relevancy to the industry.
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