The Data Engineering domain of the AWS Machine Learning Specialist certification exam comprises obtaining the data, transforming it and transferring it to a repository. Twenty percent of the exam marks come from this knowledge domain which is divided into three subdomains.
- 1.1 Create data repositories for machine learning.
- 1.2 Identify and implement a data-ingestion solution.
- 1.3 Identify and implement a data-transformation solution.
The data repository (subdomain 1.1) is where the raw and processed data is stored. S3 is the repository of choice for Machine Learning in AWS although some other data stores are also mentioned. The data ingestion subdomain (1.2) is concerned with getting the raw data into the repository. This can be via batch processing or streaming data. With batch processing data is collected and grouped at a point in time and passed to the data store. Streaming data is constantly being collected and fed into the data store. The third subdomain (1.3) focuses on how raw data is transformed into data that can be used for ML processing. The transformation process changes the data structure. The data may also need to be cleaned, de-duplicated, incomplete data managed and have it’s attributes standardised.
Once these data engineering processes are complete the data is ready for further pre-processing prior to being fed into a Machine Learning algorithm. This preprocessing is covered by the second knowledge domain, Exploratory Data Analysis.
- For description of the exam structure see this article: https://www.mlexam.com/aws-machine-learning-exam-syllabus/.
- The AWS exam guide pdf can be downloaded from: https://d1.awsstatic.com/training-and-certification/docs-ml/AWS-Certified-Machine-Learning-Specialty_Exam-Guide.pdf
AWS Certified Machine Learning Study Guide: Specialty (MLS-C01) Exam
This study guide provides the domain-by-domain specific knowledge you need to build, train, tune, and deploy machine learning models with the AWS Cloud. The online resources that accompany this Study Guide include practice exams and assessments, electronic flashcards, and supplementary online resources. It is available in both paper and kindle version for immediate access. (Vist Amazon books)
Sample Data Engineering questions
This test is five questions randomly taken from 17 questions of the three sub-domains.
Data engineering study guides
This is a summary of the AWS Power Machine Learning at Scale White Paper which is a 15 page pdf document focusing on High Power Computing (HPC) in AWS. It can be downloaded from here: The list of White Papers for Machine Learning is on the Prepare for Your AWS Certification Exam web page: AWS…
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Streaming data processing is used when data is continuously being generated and needs to be processed as it arrives. The AWS service for data streaming processing is Kinesis. Kineses comprises of four services each with different capabilities and some that can be used together. As well as Kinesis there is another AWS service that can…
This Study Guide is about transforming raw data so it is ready for Machine Learning. There are two types of transformation: Identify and implement a data-transformation solution is sub-domain 1.3 of the Data Engineering knowledge domain. For more information about the exam structure see: AWS Machine Learning exam syllabus Questions To confirm your understanding scroll to…
For Machine Learning AWS glue and AWS Database Migration Service are used to ingest data. Batch processing refers to processing usually performed to a specific schedule. Before the batch process starts data is waiting and often any new data will have to wait for the next batch processing to be processed. In AWS any compute…
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