{"id":24817,"date":"2022-03-12T14:00:00","date_gmt":"2022-03-12T08:30:00","guid":{"rendered":"https:\/\/www.testpreptraining.com\/blog\/?p=24817"},"modified":"2023-02-02T11:52:01","modified_gmt":"2023-02-02T06:22:01","slug":"is-aws-machine-learning-certification-worth-it","status":"publish","type":"post","link":"https:\/\/www.testpreptraining.ai\/blog\/is-aws-machine-learning-certification-worth-it\/","title":{"rendered":"Is AWS Machine Learning Certification worth it?"},"content":{"rendered":"\n<p>The AWS Machine Learning Specialty (MLS-C01) certification has been developed to test your knowledge of applied machine and deep learning, both within the AWS environment, but also generally. Even the most highly experienced data scientists and machine learning developers consider the exam difficult without prior preparation. The AWS Machine Learning exam requires appropriate resources and hands-on experience to learn machine learning and artificial intelligence skills. Some people will only go as far as taking courses to help them pass the AWS Machine Learning exam. <em>Let us start by knowing a little more about the exam. <\/em><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>AWS Machine Learning Specialty (MLS-C01)<\/strong><\/h3>\n\n\n\n<p>The AWS Certified Machine Learning &#8211; Specialty certification is a professional certification that demonstrates a deep understanding of Amazon Web Services (AWS) machine learning tools and techniques. It certifies that the individual has the skills and knowledge necessary to develop, deploy, and maintain machine learning models on the AWS platform.<\/p>\n\n\n\n<p>The certification exam covers topics such as:<\/p>\n\n\n\n<ol class=\"wp-block-list\"><li>AWS machine learning services and tools<\/li><li>Designing, deploying, and maintaining machine learning models<\/li><li>Data preparation, processing, and management<\/li><li>Machine learning algorithms and techniques<\/li><li>Model optimization and evaluation<\/li><li>Security and compliance in machine learning<\/li><\/ol>\n\n\n\n<p>The certification is intended for individuals who have a strong background in machine learning, data science, and cloud computing, and who want to demonstrate their expertise in these areas. Obtaining the AWS Certified Machine Learning &#8211; Specialty certification can help individuals differentiate themselves in the job market and increase their marketability to potential employers.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Exam overview<\/strong><\/h3>\n\n\n\n<p>The AWS Machine Learning Specialist Certification exam is made up of 65 scenario-based questions that assess a candidate&#8217;s ability to solve various business problems. This is a speciality exam with a time limit of 170 minutes. The AWS Machine Learning Certification Cost is $300, though prices may vary depending on location. The exam can be scheduled through Pearson VUE or PSI. <\/p>\n\n\n\n<p>The questions are of the multiple-choice and multiple-response variety. The AWS machine learning speciality exam is graded on a scale of 1 to 1000, with 750 being the passing score. The Amazon Web Services machine learning speciality exam is available in English, Japanese, Korean, and Simplified Chinese.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Who should take the exam?<\/strong><\/h4>\n\n\n\n<p>Amazon suggests that a candidate taking the exam have the following knowledge and experience:<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>To begin, you should have at least 1-2 years of experience developing, architecting, or running ML\/deep learning workloads on the AWS Cloud.<\/li><li>As a result, the ability to express the intuition underlying basic ML algorithms.<\/li><li>Also, you should have some experience with basic hyperparameter optimization.<\/li><li>Experience with machine learning and deep learning frameworks is also required.<\/li><li>In addition, the ability to adhere to model-training best practices.<\/li><li>Finally, you must be able to adhere to deployment and operational best practices.<\/li><\/ul>\n\n\n\n<p><em>Let us now move to the main point of the article &#8211; <\/em><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Is AWS Machine Learning Certification worth it?<\/strong><\/h3>\n\n\n\n<p>The ecosystem is thriving and expanding, and traditional educational pathways are struggling to keep up. Earning and displaying the AWS Machine Learning certification on your resume represents deep technical knowledge and critical thinking ability. Employers and managers recognize that it denotes a thorough understanding of algorithms, frameworks, and best practices, and the ability to apply that knowledge to real-world solutions on AWS.<\/p>\n\n\n\n<p>Only Carnegie Mellon University in the United States offers a bachelor&#8217;s level machine learning program, despite the industry&#8217;s dire need. All other programs are at the master&#8217;s or doctoral level, which means massive amounts of student debt. In comparison, the AWS Certified Machine Learning &#8211; Specialty exam costs $300 once, and the practice exam costs $40. The test takes 180 minutes to complete, and preparation typically takes 40+ hours.<\/p>\n\n\n\n<p>Here are some factors to consider:<\/p>\n\n\n\n<ol class=\"wp-block-list\"><li>Market demand: The demand for professionals with AWS machine learning skills is growing as organizations increasingly adopt cloud-based machine learning solutions. If there is high demand in your area, obtaining the certification could make you more competitive in the job market.<\/li><li>Career advancement: The certification can demonstrate to employers that you have a deep understanding of AWS machine learning and can help you advance in your career or open up new job opportunities.<\/li><li>Learning opportunities: The certification process provides an opportunity to gain hands-on experience with AWS machine learning and deepen your knowledge of this field.<\/li><li>Marketability: The certification can increase your marketability and credibility as a professional who is capable of developing, deploying, and maintaining machine learning models on the AWS platform.<\/li><li>Career goals: If your career goals include working with machine learning and AWS, the certification can help you achieve these goals and demonstrate your expertise.<\/li><\/ol>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/www.testpreptraining.ai\/aws-certified-machine-learning-specialty-free-practice-test\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" width=\"961\" height=\"150\" src=\"https:\/\/www.testpreptraining.ai\/blog\/wp-content\/uploads\/2022\/03\/Is-AWS-Machine-Learning-Certification-worth-it-1.png\" alt=\"\" class=\"wp-image-24830\" srcset=\"https:\/\/www.testpreptraining.ai\/blog\/wp-content\/uploads\/2022\/03\/Is-AWS-Machine-Learning-Certification-worth-it-1.png 961w, https:\/\/www.testpreptraining.ai\/blog\/wp-content\/uploads\/2022\/03\/Is-AWS-Machine-Learning-Certification-worth-it-1-300x47.png 300w\" sizes=\"(max-width: 961px) 100vw, 961px\" \/><\/a><\/figure>\n\n\n\n<p><em>Let us now move to the course outline to know more about the exam &#8211; <\/em><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Syllabus outline<\/strong><\/h3>\n\n\n\n<p>The Amazon AWS Machine Learning Certification exam will put you through your paces in the following areas. The domain compositions are also fixed. Consider the AWS Machine Learning Certification Course Outline &#8211; <\/p>\n\n\n\n<div class=\"wp-block-image size-large\"><figure class=\"aligncenter is-resized\"><img decoding=\"async\" src=\"https:\/\/www.testpreptraining.ai\/tutorial\/wp-content\/uploads\/2020\/06\/image-24.png\" alt=\"AWS Machine Learning Specialty Exam Course outline\" class=\"wp-image-6939\" width=\"750\" height=\"400\"\/><\/figure><\/div>\n\n\n\n<h5 class=\"wp-block-heading\"><strong>Domain 1: Data Engineering<\/strong><\/h5>\n\n\n\n<p>1.1 Create data repositories for machine learning.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Identify data sources (e.g., content and location, primary sources such as user data) <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/quicksight\/latest\/user\/supported-data-sources.html\" target=\"_blank\" rel=\"noreferrer noopener\">Supported data sources<\/a>)<\/li><li>Determine storage mediums (e.g., DB, Data Lake, S3, EFS, EBS) <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/using-amazon-s3-with-amazon-ml.html\" target=\"_blank\" rel=\"noreferrer noopener\">Using Amazon S3 with Amazon ML<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/create-datasource-from-redshift-procedure.html\" target=\"_blank\" rel=\"noreferrer noopener\">Creating a Datasource with Amazon Redshift Data<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/using-amazon-rds-with-amazon-ml.html\" target=\"_blank\" rel=\"noreferrer noopener\">Using Data from an Amazon RDS Database<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/host-instance-storage.html\" target=\"_blank\" rel=\"noreferrer noopener\">Host instance storage volumes<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/apn\/amazon-machine-learning-and-amazon-elastic-file-system-amazon-efs-a-perspective-for-apn-partners\/\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Machine Learning and Amazon Elastic File System<\/a>)<\/li><\/ul>\n\n\n\n<p>1.2 Identify and implement a data ingestion solution.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Data job styles\/types (batch load, streaming)<\/li><li>Data ingestion pipelines (Batch-based ML workloads and streaming-based ML workloads)<ul><li>Kinesis <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/kinesis\/data-streams\/getting-started\/\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Kinesis Data Streams<\/a>)<\/li><li>Kinesis Analytics <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/kinesis\/data-analytics\/\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Kinesis Data Analytics<\/a>)<\/li><li>Kinesis Firehose <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/big-data\/build-seamless-data-streaming-pipelines-with-amazon-kinesis-data-streams-and-amazon-kinesis-data-firehose-for-amazon-dynamodb-tables\/\" target=\"_blank\" rel=\"noreferrer noopener\">Build seamless data streaming pipelines<\/a>)<\/li><li>EMR <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/datapipeline\/latest\/DeveloperGuide\/dp-launch-emr-jobflow.html\" target=\"_blank\" rel=\"noreferrer noopener\">Process Data Using Amazon EMR with Hadoop Streaming<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/big-data\/optimizing-downstream-data-processing-with-amazon-kinesis-data-firehose-and-amazon-emr-running-apache-spark\/\" target=\"_blank\" rel=\"noreferrer noopener\">Optimize downstream data processing<\/a>)<\/li><li>Glue <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/big-data\/simplify-data-pipelines-with-aws-glue-automatic-code-generation-and-workflows\/\" target=\"_blank\" rel=\"noreferrer noopener\">Simplify data pipelines<\/a>, <a href=\"https:\/\/aws.amazon.com\/glue\/?whats-new-cards.sort-by=item.additionalFields.postDateTime&amp;whats-new-cards.sort-order=desc\" target=\"_blank\" rel=\"noreferrer noopener\">AWS Glue<\/a>)<\/li><\/ul><\/li><li>Job scheduling <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/batch\/latest\/userguide\/job_scheduling.html\" target=\"_blank\" rel=\"noreferrer noopener\">Job scheduling<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/glue\/latest\/dg\/monitor-data-warehouse-schedule.html\" target=\"_blank\" rel=\"noreferrer noopener\">Time-based schedules for jobs and crawlers<\/a>)<\/li><\/ul>\n\n\n\n<p>1.3 Identify and implement a data transformation solution.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Transforming data transit (ETL: Glue, EMR, AWS Batch) <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/database\/how-to-extract-transform-and-load-data-for-analytic-processing-using-aws-glue-part-2\/\" target=\"_blank\" rel=\"noreferrer noopener\">extract, transform, and load data for analytic processing using AWS Glue<\/a>)<\/li><li>Handle ML-specific data using map reduce (Hadoop, Spark, Hive) <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/big-data\/large-scale-machine-learning-with-spark-on-amazon-emr\/\" target=\"_blank\" rel=\"noreferrer noopener\">Large-Scale Machine Learning with Spark on Amazon EMR<\/a>, <a href=\"https:\/\/aws.amazon.com\/emr\/features\/hive\/\" target=\"_blank\" rel=\"noreferrer noopener\">Apache Hive on Amazon EMR<\/a>, <a href=\"https:\/\/aws.amazon.com\/emr\/features\/spark\/\" target=\"_blank\" rel=\"noreferrer noopener\">Apache Spark on Amazon EMR<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/apache-spark.html\" target=\"_blank\" rel=\"noreferrer noopener\">Use Apache Spark with Amazon SageMaker<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/perform-interactive-data-engineering-and-data-science-workflows-from-amazon-sagemaker-studio-notebooks\/\" target=\"_blank\" rel=\"noreferrer noopener\">Perform interactive data engineering and data science workflows<\/a>)<\/li><\/ul>\n\n\n\n<h5 class=\"wp-block-heading\"><strong>Domain 2: Exploratory Data Analysis<\/strong><\/h5>\n\n\n\n<p>2.1 Sanitize and prepare data for modeling.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Identify and handle missing data, corrupt data, stop words, etc. <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/managing-missing-values-in-your-target-and-related-datasets-with-automated-imputation-support-in-amazon-forecast\/\" target=\"_blank\" rel=\"noreferrer noopener\">Managing missing values in your target and related datasets<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/amazon-sagemaker-deepar-now-supports-missing-values-categorical-and-time-series-features-and-generalized-frequencies\/\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon SageMaker DeepAR now supports missing values,<\/a><a href=\"https:\/\/docs.aws.amazon.com\/cloudsearch\/latest\/developerguide\/configuring-analysis-schemes.html\" target=\"_blank\" rel=\"noreferrer noopener\"> Configuring Text Analysis Schemes<\/a>)<\/li><li>Formatting, normalizing, augmenting, and scaling data <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/understanding-the-data-format-for-amazon-ml.html\" target=\"_blank\" rel=\"noreferrer noopener\">Understanding the Data Format for Amazon ML<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/cdf-training.html\" target=\"_blank\" rel=\"noreferrer noopener\">Common Data Formats for Training<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/data-transformations-reference.html\" target=\"_blank\" rel=\"noreferrer noopener\">Data Transformations Reference<\/a>, <a href=\"https:\/\/aws.amazon.com\/about-aws\/whats-new\/2020\/11\/introducing-aws-glue-databrew-visual-data-preparation-tool-to-clean-and-normalize-data-up-to-80-percent-faster\/\" target=\"_blank\" rel=\"noreferrer noopener\">AWS Glue DataBrew<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/easily-train-models-using-datasets-labeled-by-amazon-sagemaker-ground-truth\/\" target=\"_blank\" rel=\"noreferrer noopener\">Easily train models using datasets<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/making-machine-learning-predictions-in-amazon-quicksight-and-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Visualizing Amazon SageMaker machine learning predictions<\/a>)<\/li><li>Labeled data (recognizing when you have enough labeled data and identifying mitigation strategies [Data labeling tools (Mechanical Turk, manual labor)]) <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/sagemaker\/data-labeling\/what-is-data-labeling\/\" target=\"_blank\" rel=\"noreferrer noopener\">data labeling for machine learning<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/AWSMechTurk\/latest\/AWSMechanicalTurkGettingStartedGuide\/SvcIntro.html\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Mechanical Turk<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/use-amazon-mechanical-turk-with-amazon-sagemaker-for-supervised-learning\/\" target=\"_blank\" rel=\"noreferrer noopener\">Use Amazon Mechanical Turk with Amazon SageMaker<\/a>)<\/li><\/ul>\n\n\n\n<p>2.2 Perform feature engineering.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Identify and extract features from data sets, including from data sources such as text, speech, image, public datasets, etc. <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/feature-processing.html\" target=\"_blank\" rel=\"noreferrer noopener\">Feature Processing<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/wellarchitected\/latest\/machine-learning-lens\/feature-engineering.html\" target=\"_blank\" rel=\"noreferrer noopener\">Feature engineering<\/a>, <a href=\"https:\/\/aws.amazon.com\/textract\/\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Textract<\/a>, <a href=\"https:\/\/aws.amazon.com\/textract\/features\/\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Textract features<\/a>)<\/li><li>Analyze\/evaluate feature engineering concepts (binning, tokenization, outliers, synthetic features, 1 hot encoding, reducing dimensionality of data) <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/data-transformations-reference.html\" target=\"_blank\" rel=\"noreferrer noopener\">Data Transformations Reference<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/compute\/building-a-serverless-tokenization-solution-to-mask-sensitive-data\/\" target=\"_blank\" rel=\"noreferrer noopener\">Building a serverless tokenization solution to mask sensitive data<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/quicksight\/latest\/user\/anomaly-detection-function.html\" target=\"_blank\" rel=\"noreferrer noopener\">ML-powered anomaly detection for outliers<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/databrew\/latest\/dg\/recipe-actions.ONE_HOT_ENCODING.html\" target=\"_blank\" rel=\"noreferrer noopener\">ONE_HOT_ENCODING<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/running-principal-component-analysis-in-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Running Principal Component Analysis<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/perform-a-large-scale-principal-component-analysis-faster-using-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Perform a large-scale principal component analysis<\/a>)<\/li><\/ul>\n\n\n\n<p>2.3 Analyze and visualize data for machine learning. <\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Graphing (scatter plot, time series, histogram, box plot) <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/quicksight\/latest\/user\/scatter-plot.html\" target=\"_blank\" rel=\"noreferrer noopener\">Using scatter plots<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/AmazonCloudWatch\/latest\/logs\/CWL_AnalyzeLogData_VisualizationQuery.html\" target=\"_blank\" rel=\"noreferrer noopener\">Run a query that produces a time series visualization<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/quicksight\/latest\/user\/histogram-charts.html\" target=\"_blank\" rel=\"noreferrer noopener\">Using histograms<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/quicksight\/latest\/user\/box-plots.html\" target=\"_blank\" rel=\"noreferrer noopener\">Using box plots<\/a>)<\/li><li>Interpreting descriptive statistics (correlation, summary statistics, p value)<\/li><li>Clustering (hierarchical, diagnosing, elbow plot, cluster size)<\/li><\/ul>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/www.testpreptraining.ai\/aws-certified-machine-learning-specialty-free-practice-test\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" width=\"961\" height=\"150\" src=\"https:\/\/www.testpreptraining.ai\/blog\/wp-content\/uploads\/2022\/03\/Is-AWS-Machine-Learning-Certification-worth-it-1-1.png\" alt=\"\" class=\"wp-image-24831\" srcset=\"https:\/\/www.testpreptraining.ai\/blog\/wp-content\/uploads\/2022\/03\/Is-AWS-Machine-Learning-Certification-worth-it-1-1.png 961w, https:\/\/www.testpreptraining.ai\/blog\/wp-content\/uploads\/2022\/03\/Is-AWS-Machine-Learning-Certification-worth-it-1-1-300x47.png 300w\" sizes=\"(max-width: 961px) 100vw, 961px\" \/><\/a><\/figure>\n\n\n\n<h5 class=\"wp-block-heading\"><strong>Domain 3: Modeling<\/strong><\/h5>\n\n\n\n<p>3.1 Frame business problems as machine learning problems.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Determine when to use\/when not to use ML <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/when-to-use-machine-learning.html\" target=\"_blank\" rel=\"noreferrer noopener\">When to Use Machine Learning<\/a>)<\/li><li>Know the difference between supervised and unsupervised learning<\/li><li>Selecting from among classification, regression, forecasting, clustering, recommendation, etc. <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/k-means-clustering-with-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">K-means clustering with Amazon SageMaker<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/building-a-customized-recommender-system-in-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Building a customized recommender system in Amazon SageMaker<\/a>)<\/li><\/ul>\n\n\n\n<p>3.2 Select the appropriate model(s) for a given machine learning problem.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Xgboost, logistic regression, K-means, linear regression, decision trees, random forests, RNN, CNN, Ensemble, Transfer learning <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/xgboost.html\" target=\"_blank\" rel=\"noreferrer noopener\">XGBoost Algorithm<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/k-means-clustering-with-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">K-means clustering with Amazon SageMaker<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/forecasting-time-series-with-dynamic-deep-learning-on-aws\/\" target=\"_blank\" rel=\"noreferrer noopener\">Forecasting financial time series<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/amazon-forecast-can-now-use-convolutional-neural-networks-cnns-to-train-forecasting-models-up-to-2x-faster-with-up-to-30-higher-accuracy\/\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Forecast can now use Convolutional Neural Networks<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/detecting-hidden-but-non-trivial-problems-in-transfer-learning-models-using-amazon-sagemaker-debugger\/\" target=\"_blank\" rel=\"noreferrer noopener\">Detecting hidden but non-trivial problems in transfer learning models<\/a>)<\/li><li>Express intuition behind models<\/li><\/ul>\n\n\n\n<p>3.3 Train machine learning models.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Train validation test split, cross-validation <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/ex1-train-model.html\" target=\"_blank\" rel=\"noreferrer noopener\">Train a Model<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/incremental-training.html\" target=\"_blank\" rel=\"noreferrer noopener\">Incremental Training<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/model-managed-spot-training.html\" target=\"_blank\" rel=\"noreferrer noopener\">Managed Spot Training<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/how-it-works-model-validation.html\" target=\"_blank\" rel=\"noreferrer noopener\">Validate a Machine Learning Model<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/cross-validation.html\" target=\"_blank\" rel=\"noreferrer noopener\">Cross-Validation<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/autopilot-model-support-validation.html\" target=\"_blank\" rel=\"noreferrer noopener\">Model support, metrics, and validation<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/splitting-types.html\" target=\"_blank\" rel=\"noreferrer noopener\">Splitting Your Data<\/a>)<\/li><li>Optimizer, gradient descent, loss functions, local minima, convergence, batches, probability, etc.<\/li><li>Compute choice (GPU vs. CPU, distributed vs. non-distributed, platform [Spark vs. non-Spark]) <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/big-data\/what-is-spark\/\" target=\"_blank\" rel=\"noreferrer noopener\">Introduction to Apache Spark<\/a>)<\/li><li>Model updates and retraining <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/retraining-models-on-new-data.html\" target=\"_blank\" rel=\"noreferrer noopener\">Retraining Models on New Data<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/automating-model-retraining-and-deployment-using-the-aws-step-functions-data-science-sdk-for-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Automating model retraining and deployment<\/a>)<ul><li>Batch vs. real-time\/online<\/li><\/ul><\/li><\/ul>\n\n\n\n<p>3.4 Perform hyperparameter optimization.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Regularization <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/training-parameters1.html\" target=\"_blank\" rel=\"noreferrer noopener\">Training Parameters<\/a>)<ul><li>Drop out<\/li><li>L1\/L2<\/li><\/ul><\/li><li>Cross validation <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/cross-validation.html\" target=\"_blank\" rel=\"noreferrer noopener\">Cross-Validation<\/a>)<\/li><li>Model initialization<\/li><li>Neural network architecture (layers\/nodes), learning rate, activation functions<\/li><li>Tree-based models (# of trees, # of levels)<\/li><li>Linear models (learning rate)<\/li><\/ul>\n\n\n\n<p>3.5 Evaluate machine learning models.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Avoid overfitting\/underfitting (detect and handle bias and variance) <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/model-fit-underfitting-vs-overfitting.html\" target=\"_blank\" rel=\"noreferrer noopener\">Underfitting vs. Overfitting<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/aws\/new-amazon-sagemaker-clarify-detects-bias-and-increases-the-transparency-of-machine-learning-models\/\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon SageMaker Clarify Detects Bias and Increases the Transparency<\/a>, <a href=\"https:\/\/aws.amazon.com\/sagemaker\/clarify\/?sagemaker-data-wrangler-whats-new.sort-by=item.additionalFields.postDateTime&amp;sagemaker-data-wrangler-whats-new.sort-order=desc\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon SageMaker Clarify<\/a>)<\/li><li>Metrics (AUC-ROC, accuracy, precision, recall, RMSE, F1 score)<\/li><li>Confusion matrix <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/comprehend\/latest\/dg\/cer-doc-class.html\" target=\"_blank\" rel=\"noreferrer noopener\">Custom classifier metrics<\/a>)<\/li><li>Offline and online model evaluation, A\/B testing <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/how-it-works-model-validation.html\" target=\"_blank\" rel=\"noreferrer noopener\">Validate a Machine Learning Model<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/wellarchitected\/latest\/machine-learning-lens\/machine-learning-lens.html\" target=\"_blank\" rel=\"noreferrer noopener\">Machine Learning Lens<\/a>)<\/li><li>Compare models using metrics (time to train a model, quality of model, engineering costs) <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/easily-monitor-and-visualize-metrics-while-training-models-on-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Easily monitor and visualize metrics while training models<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/model-monitor-model-quality-metrics.html\" target=\"_blank\" rel=\"noreferrer noopener\">Model Quality Metrics<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/model-monitor-model-quality.html\" target=\"_blank\" rel=\"noreferrer noopener\">Monitor model quality<\/a>)<\/li><li>Cross validation <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/cross-validation.html\" target=\"_blank\" rel=\"noreferrer noopener\">Cross-Validation<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/autopilot-model-support-validation.html\" target=\"_blank\" rel=\"noreferrer noopener\">Model support, metrics, and validation<\/a>)<\/li><\/ul>\n\n\n\n<h5 class=\"wp-block-heading\"><strong>Domain 4: Machine Learning Implementation and Operations<\/strong><\/h5>\n\n\n\n<p>4.1 Build machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance. <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/step-4-review-model-and-set-cutoff.html\" target=\"_blank\" rel=\"noreferrer noopener\">Review the ML Model&#8217;s Predictive Performance<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/best-practices.html\" target=\"_blank\" rel=\"noreferrer noopener\">Best practices<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/disaster-recovery-resiliency.html\" target=\"_blank\" rel=\"noreferrer noopener\">Resilience in Amazon SageMaker<\/a>)<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>AWS environment logging and monitoring <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/sagemaker-incident-response.html\" target=\"_blank\" rel=\"noreferrer noopener\">Logging and Monitoring<\/a>)<ul><li>CloudTrail and CloudWatch <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/logging-using-cloudtrail.html\" target=\"_blank\" rel=\"noreferrer noopener\">Logging Amazon ML API Calls with AWS CloudTrail<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/logging-using-cloudtrail.html\" target=\"_blank\" rel=\"noreferrer noopener\">Log Amazon SageMaker API Calls<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/cw-doc.html\" target=\"_blank\" rel=\"noreferrer noopener\">Monitoring Amazon ML<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/monitoring-cloudwatch.html\" target=\"_blank\" rel=\"noreferrer noopener\">Monitor Amazon SageMaker<\/a>)<\/li><li>Build error monitoring <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/whitepapers\/latest\/build-secure-enterprise-ml-platform\/ml-platform-monitoring.html\" target=\"_blank\" rel=\"noreferrer noopener\">ML Platform Monitoring<\/a>)<\/li><\/ul><\/li><li>Multiple regions, Multiple AZs <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/regions-and-endpoints.html\" target=\"_blank\" rel=\"noreferrer noopener\">Regions and Endpoints<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/best-practices.html\" target=\"_blank\" rel=\"noreferrer noopener\">Best practices<\/a>)<\/li><li>AMI\/golden image <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/dlami\/latest\/devguide\/what-is-dlami.html\" target=\"_blank\" rel=\"noreferrer noopener\">AWS Deep Learning AMI<\/a>)<\/li><li>Docker containers <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/opensource\/why-use-docker-containers-for-machine-learning-development\/\" target=\"_blank\" rel=\"noreferrer noopener\">Why use Docker containers for machine learning development<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/docker-containers.html\" target=\"_blank\" rel=\"noreferrer noopener\">Using Docker containers with SageMaker<\/a>)<\/li><li>Auto Scaling groups <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/endpoint-auto-scaling.html\" target=\"_blank\" rel=\"noreferrer noopener\">Automatically Scale Amazon SageMaker Models<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/configuring-autoscaling-inference-endpoints-in-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Configuring autoscaling inference endpoints<\/a>)<\/li><li>Rightsizing<ul><li>Instances <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/ensure-efficient-compute-resources-on-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Ensure efficient compute resources on Amazon SageMaker<\/a>)<\/li><li>Provisioned IOPS <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/optimizing-i-o-for-gpu-performance-tuning-of-deep-learning-training-in-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Optimizing I\/O for GPU performance tuning of deep learning<\/a>)<\/li><li>Volumes <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/customize-your-notebook-volume-size-up-to-16-tb-with-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Customize your notebook volume size, up to 16 TB<\/a>)<\/li><\/ul><\/li><li>Load balancing <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/managing-your-machine-learning-lifecycle-with-mlflow-and-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Managing your machine learning lifecycle<\/a>)<\/li><li>AWS best practices <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/machine-learning-best-practices-in-financial-services\/\" target=\"_blank\" rel=\"noreferrer noopener\">Machine learning best practices in financial services<\/a>)<\/li><\/ul>\n\n\n\n<p>4.2 Recommend and implement the appropriate machine learning services and features for a given problem.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>ML on AWS (application services)<ul><li>Poly <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/polly\/?nc=sn&amp;loc=1\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Polly<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/build-a-unique-brand-voice-with-amazon-polly\/\" target=\"_blank\" rel=\"noreferrer noopener\">Build a unique Brand Voice with Amazon Polly<\/a>)<\/li><li>Lex <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/lex\/latest\/dg\/what-is.html\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Lex<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/build-more-effective-conversations-on-amazon-lex-with-confidence-scores-and-increased-accuracy\/\" target=\"_blank\" rel=\"noreferrer noopener\">Build more effective conversations on Amazon Lex<\/a>)<\/li><li>Transcribe <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/transcribe\/?nc=sn&amp;loc=1\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Transcribe<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/transcribe-speech-to-text-in-real-time-using-amazon-transcribe-with-websocket\/\" target=\"_blank\" rel=\"noreferrer noopener\">Transcribe speech to text in real time<\/a>)<\/li><\/ul><\/li><li>AWS service limits <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/general\/latest\/gr\/sagemaker.html\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon SageMaker endpoints and quotas<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/general\/latest\/gr\/machinelearning.html\" target=\"_blank\" rel=\"noreferrer noopener\">Amazon Machine Learning endpoints and quotas<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/system-limits.html\" target=\"_blank\" rel=\"noreferrer noopener\">System Limits<\/a>)<\/li><li>Build your own model vs. SageMaker built-in algorithms <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/algos.html\" target=\"_blank\" rel=\"noreferrer noopener\">Use Amazon SageMaker Built-in Algorithms or Pre-trained Models<\/a>)<\/li><li>Infrastructure: (spot, instance types), cost considerations <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/cmn-info-instance-types.html\" target=\"_blank\" rel=\"noreferrer noopener\">Instance Types for Built-in Algorithms<\/a>)<ul><li>Using spot instances to train deep learning models using AWS Batch <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/train-deep-learning-models-on-gpus-using-amazon-ec2-spot-instances\/\" target=\"_blank\" rel=\"noreferrer noopener\">Train Deep Learning Models on GPUs<\/a>)<\/li><\/ul><\/li><\/ul>\n\n\n\n<p>4.3 Apply basic AWS security practices to machine learning solutions.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>IAM <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/controlling-access-to-amazon-ml-resources-by-using-iam.html\" target=\"_blank\" rel=\"noreferrer noopener\">Controlling Access to Amazon ML Resources<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/deep-learning-containers\/latest\/devguide\/security-iam.html\" target=\"_blank\" rel=\"noreferrer noopener\">Identity and Access Management in AWS Deep Learning Containers<\/a>)<\/li><li>S3 bucket policies <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/using-amazon-s3-with-amazon-ml.html\" target=\"_blank\" rel=\"noreferrer noopener\">Using Amazon S3 with Amazon ML<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/machine-learning\/latest\/dg\/granting-amazon-ml-permissions-to-read-your-data-from-amazon-s3.html\" target=\"_blank\" rel=\"noreferrer noopener\">Granting Amazon ML Permissions to Read Your Data from Amazon S3<\/a>)<\/li><li>Security groups <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/part-1-secure-multi-account-model-deployment-with-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Secure multi-account model deployment with Amazon SageMaker<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/AWSEC2\/latest\/UserGuide\/efa-start-nccl-dlami.html\" target=\"_blank\" rel=\"noreferrer noopener\">Use an AWS Deep Learning AMI<\/a>)<\/li><li>VPC <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/securing-amazon-sagemaker-studio-connectivity-using-a-private-vpc\/\" target=\"_blank\" rel=\"noreferrer noopener\">Securing Amazon SageMaker Studio connectivity<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/direct-access-to-amazon-sagemaker-notebooks-from-amazon-vpc-by-using-an-aws-privatelink-endpoint\/\" target=\"_blank\" rel=\"noreferrer noopener\">Direct access to&nbsp;Amazon SageMaker notebooks<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/building-secure-machine-learning-environments-with-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Building secure machine learning environments<\/a>)<\/li><li>Encryption\/anonymization <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/encryption-at-rest.html\" target=\"_blank\" rel=\"noreferrer noopener\">Protect Data at Rest Using Encryption<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/encryption-in-transit.html\" target=\"_blank\" rel=\"noreferrer noopener\">Protecting Data in Transit with Encryption<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/big-data\/anonymize-and-manage-data-in-your-data-lake-with-amazon-athena-and-aws-lake-formation\/\" target=\"_blank\" rel=\"noreferrer noopener\">Anonymize and manage data in your data lake<\/a>)<\/li><\/ul>\n\n\n\n<p>4.4 Deploy and operationalize machine learning solutions.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Exposing endpoints and interacting with them <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/creating-a-machine-learning-powered-rest-api-with-amazon-api-gateway-mapping-templates-and-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Creating a machine learning-powered REST API<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/call-an-amazon-sagemaker-model-endpoint-using-amazon-api-gateway-and-aws-lambda\/\" target=\"_blank\" rel=\"noreferrer noopener\">Call an Amazon SageMaker model endpoint<\/a>)<\/li><li>ML model versioning <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/rekognition\/latest\/dg\/face-detection-model.html\" target=\"_blank\" rel=\"noreferrer noopener\">Model versioning<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/model-registry-version.html\" target=\"_blank\" rel=\"noreferrer noopener\">Register a Model Version<\/a>)<\/li><li>A\/B testing <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/a-b-testing-ml-models-in-production-using-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">A\/B Testing ML models in production<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/dynamic-a-b-testing-for-machine-learning-models-with-amazon-sagemaker-mlops-projects\/\" target=\"_blank\" rel=\"noreferrer noopener\">Dynamic A\/B testing for machine learning models<\/a>)<\/li><li>Retrain pipelines <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/automating-model-retraining-and-deployment-using-the-aws-step-functions-data-science-sdk-for-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Automating model retraining and deployment<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/wellarchitected\/latest\/machine-learning-lens\/machine-learning-lens.html\" target=\"_blank\" rel=\"noreferrer noopener\">Machine Learning Lens<\/a>)<\/li><li>ML debugging\/troubleshooting <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/aws\/amazon-sagemaker-debugger-debug-your-machine-learning-models\/\" target=\"_blank\" rel=\"noreferrer noopener\">Debug Your Machine Learning Models<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/analyzing-open-source-ml-pipeline-models-in-real-time-using-amazon-sagemaker-debugger\/\" target=\"_blank\" rel=\"noreferrer noopener\">Analyzing open-source ML pipeline models in real time<\/a>, <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/deploy-model-troubleshoot.html\" target=\"_blank\" rel=\"noreferrer noopener\">Troubleshoot Amazon SageMaker model deployments<\/a>)<ul><li>Detect and mitigate drop in performance <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/identify-bottlenecks-improve-resource-utilization-and-reduce-ml-training-costs-with-the-new-profiling-feature-in-amazon-sagemaker-debugger\/\" target=\"_blank\" rel=\"noreferrer noopener\">Identify bottlenecks, improve resource utilization, and reduce ML training costs<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/optimizing-i-o-for-gpu-performance-tuning-of-deep-learning-training-in-amazon-sagemaker\/\" target=\"_blank\" rel=\"noreferrer noopener\">Optimizing I\/O for GPU performance tuning of deep learning training<\/a>)<\/li><li>Monitor performance of the model <strong>(AWS Documentation:<\/strong> <a href=\"https:\/\/docs.aws.amazon.com\/sagemaker\/latest\/dg\/model-monitor.html\" target=\"_blank\" rel=\"noreferrer noopener\">Monitor models for data and model quality, bias, and explainability<\/a>, <a href=\"https:\/\/aws.amazon.com\/blogs\/machine-learning\/monitoring-in-production-ml-models-at-large-scale-using-amazon-sagemaker-model-monitor\/\" target=\"_blank\" rel=\"noreferrer noopener\">Monitoring in-production ML models at large scale<\/a>)<\/li><\/ul><\/li><\/ul>\n\n\n\n<p><strong><em>Now, we will be looking at some of the resources that help you ace the exam in one go!<\/em><\/strong><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>The Official learning path by Amazon<\/strong><\/h3>\n\n\n\n<p>Amazon&#8217;s official website suggests combining hands-on experience with online training and sample papers in order to ace the exam. Always make a point of visiting the official website to learn more about each aspect of the exam. The official site contains information about the exam&#8217;s technical aspects as well as the most recent updates. There are numerous official resources for the exam available on Amazon. Amazon is also offering free webinars to help spread awareness of the exam. Amazon also offers a variety of classroom sessions and expert-led courses, as listed below:<\/p>\n\n\n\n<h5 class=\"wp-block-heading\"><strong>Recommended Progression<\/strong><\/h5>\n\n\n\n<ul class=\"wp-block-list\"><li><a href=\"https:\/\/www.aws.training\/Details\/Curriculum?id=27271\" target=\"_blank\" rel=\"noreferrer noopener\">Machine Learning Exam Basics<\/a><\/li><li>Also, <a href=\"https:\/\/www.aws.training\/Details\/eLearning?id=27200\" target=\"_blank\" rel=\"noreferrer noopener\">Process Model: CRISP-DM on the AWS Stack<\/a><\/li><li>furthermore, <a href=\"https:\/\/www.aws.training\/Details\/eLearning?id=26598\" target=\"_blank\" rel=\"noreferrer noopener\">The Elements of Data Science<\/a><\/li><li>moreover, <a href=\"https:\/\/aws.amazon.com\/training\/path-storage\/\" target=\"_blank\" rel=\"noreferrer noopener\">Storage Deep Dive Learning Path<\/a><\/li><li>also, <a href=\"https:\/\/www.aws.training\/Details\/Curriculum?id=27273\" target=\"_blank\" rel=\"noreferrer noopener\">Machine Learning Security<\/a><\/li><li>moreover, <a href=\"https:\/\/www.aws.training\/Details\/Curriculum?id=27243\" target=\"_blank\" rel=\"noreferrer noopener\">Developing Machine Learning Applications<\/a><\/li><li><a href=\"https:\/\/www.aws.training\/Details\/Video?id=27224\" target=\"_blank\" rel=\"noreferrer noopener\">Types of Machine Learning Solutions<\/a><\/li><\/ul>\n\n\n\n<h5 class=\"wp-block-heading\"><strong>Branching content areas<\/strong><\/h5>\n\n\n\n<ul class=\"wp-block-list\"><li><a href=\"https:\/\/www.aws.training\/Details\/Curriculum?id=27156\" target=\"_blank\" rel=\"noreferrer noopener\">Communicating with Chat Bots<\/a><\/li><li><a href=\"https:\/\/www.aws.training\/Details\/Curriculum?id=27153\" target=\"_blank\" rel=\"noreferrer noopener\">Speaking of: Machine Translation and NLP<\/a><\/li><li><a href=\"https:\/\/www.aws.training\/Details\/Curriculum?id=27151\" target=\"_blank\" rel=\"noreferrer noopener\">Seeing Clearly: Computer Vision Theory<\/a><\/li><\/ul>\n\n\n\n<h5 class=\"wp-block-heading\"><strong>Optional training<\/strong><\/h5>\n\n\n\n<ul class=\"wp-block-list\"><li><a href=\"https:\/\/www.aws.training\/training\/schedule?courseId=10015\" target=\"_blank\" rel=\"noreferrer noopener\">Big Data on AWS<\/a><\/li><\/ul>\n\n\n\n<p>For more training options, you can visit<a href=\"https:\/\/www.aws.training\/LearningLibrary?filters=classification%3A30&amp;search=&amp;tab=view_all\" target=\"_blank\" rel=\"noreferrer noopener\">&nbsp;Training Library by Amazon<\/a>&nbsp;for machine learning.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Study groups and discussions<\/strong><\/h3>\n\n\n\n<p>You can join a variety of study groups to help you improve your preparations and pool different resources. Discussions allow you to put your knowledge to the test. Try to form groups with more interactive people, as this will help you get answers faster. This will help you develop a competitive spirit and improve your performance.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Practice papers and test series<\/strong><\/h3>\n\n\n\n<p>The only way to pass the exam with a good score is to take the Practice Exam. The more you practice, the clearer your ideas will become. Always practice sample papers and take as many test series as you can. This will aid in the discovery of loopholes and the identification of weak points. You will find the areas where you need to work harder and the areas where you are completely prepared for the exam. This is the most important step in the preparation process. <a href=\"https:\/\/www.testpreptraining.ai\/aws-certified-machine-learning-specialty-free-practice-test\" target=\"_blank\" rel=\"noreferrer noopener\">Try a free practice test now!<\/a><\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-full\"><a href=\"https:\/\/www.testpreptraining.ai\/aws-certified-machine-learning-specialty-free-practice-test\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" width=\"961\" height=\"150\" src=\"https:\/\/www.testpreptraining.ai\/blog\/wp-content\/uploads\/2022\/03\/Is-AWS-Machine-Learning-Certification-worth-it-1-2.png\" alt=\"\" class=\"wp-image-24832\" srcset=\"https:\/\/www.testpreptraining.ai\/blog\/wp-content\/uploads\/2022\/03\/Is-AWS-Machine-Learning-Certification-worth-it-1-2.png 961w, https:\/\/www.testpreptraining.ai\/blog\/wp-content\/uploads\/2022\/03\/Is-AWS-Machine-Learning-Certification-worth-it-1-2-300x47.png 300w\" sizes=\"(max-width: 961px) 100vw, 961px\" \/><\/a><\/figure><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><strong><span style=\"text-decoration: underline;\">Some Basic Exam Tips<\/span>:<\/strong><\/h3>\n\n\n\n<ol class=\"wp-block-list\"><li>Familiarize yourself with the AWS Machine Learning services and tools, including Amazon SageMaker, Amazon Comprehend, Amazon Rekognition, and others.<\/li><li>Study the official AWS Certified Machine Learning &#8211; Specialty exam objectives and syllabus.<\/li><li>Practice using AWS Machine Learning services and tools to develop, deploy, and maintain machine learning models.<\/li><li>Familiarize yourself with machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and others.<\/li><li>Learn about data preparation, processing, and management, including data storage, retrieval, and cleaning.<\/li><li>Study best practices for model optimization and evaluation, including model selection, training, and testing.<\/li><li>Get hands-on experience with security and compliance in machine learning, including data protection and privacy.<\/li><li>Take advantage of AWS&#8217;s training resources and sample exams to supplement your self-study.<\/li><li>Join online forums and discussion groups to connect with other AWS professionals and learn from their experiences.<\/li><li>Make sure you are comfortable with the examination format, timing, and delivery platform before taking the certification exam.<\/li><\/ol>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Conclusion <\/strong><\/h3>\n\n\n\n<p>Whether the AWS Machine Learning certification is worth it depends on your career goals and the demands of the job market. The certification can demonstrate to employers and clients that you have a deep understanding of Amazon Web Services (AWS) machine learning tools and techniques and that you are capable of using them to develop, deploy, and maintain machine learning models. This can increase your marketability and potentially lead to career advancement or higher pay.<\/p>\n\n\n\n<p>On the other hand, if your current role and responsibilities do not require knowledge of AWS machine learning or if the job market in your area does not place a high value on this certification, obtaining the certification may not be as beneficial.<\/p>\n\n\n\n<p>Ultimately, the value of the AWS Machine Learning certification will depend on your specific circumstances, so it is important to carefully consider your career goals and the demands of the job market before making a decision.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The AWS Machine Learning Specialty (MLS-C01) certification has been developed to test your knowledge of applied machine and deep learning, both within the AWS environment, but also generally. Even the most highly experienced data scientists and machine learning developers consider the exam difficult without prior preparation. The AWS Machine Learning exam requires appropriate resources and&#8230;<\/p>\n","protected":false},"author":7,"featured_media":24829,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[31],"tags":[332,4247,4248,4249,4246],"class_list":["post-24817","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-aws","tag-aws-certification-exam","tag-aws-machine-learning-certification","tag-aws-machine-learning-certification-free-test","tag-aws-machine-learning-specialty-mls-c01","tag-is-aws-machine-learning-certification-worth-it"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Is AWS Machine Learning Certification worth it? - Blog<\/title>\n<meta name=\"description\" content=\"Know the worth of AWS Machine Learning Certification. 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