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via Udemy |
Go to Course: https://www.udemy.com/course/aws-certified-data-analytics-specialty-210-unique-ques/
Certainly! Here's a comprehensive review and recommendation for the AWS Data Analytics Specialty course available on Coursera: --- **Course Review and Recommendation: AWS Data Analytics Specialty Certification** If you're a data professional with at least five years of experience in data analytics and looking to deepen your expertise in cloud-based data solutions, the AWS Data Analytics Specialty course on Coursera is an exceptional choice. This course is designed for professionals who want to validate their skills and demonstrate proficiency in designing, building, securing, and maintaining analytics solutions on AWS. **Course Highlights:** - **Industry-Recognized Credential:** Earn a certification that not only boosts your credibility but also shows your ability to craft efficient, cost-effective, and secure data analytics solutions on AWS. - **Comprehensive Coverage:** The curriculum covers a broad spectrum of AWS services and technologies including Kinesis, S3, DynamoDB, Glue, EMR, SageMaker, Redshift, Athena, Elasticsearch, and more. - **Practical and In-Depth Learning:** Topics include real-world applications such as streaming massive data with Kinesis, managing data pipelines with Glue, querying data lakes with Athena, and deploying machine learning models with SageMaker. - **Hands-On Approach:** While the course primarily prepares you for a certification exam, it emphasizes practical understanding, enabling you to translate knowledge into real-world solutions. **Delivery and Exam Details:** - The exam is an online proctored test lasting approximately 180 minutes. - The cost is $300 USD, with a practice exam available for $40 USD. - The exam format is multiple choice/multiple answer questions, testing your breadth and depth of knowledge. **Who Should Take This Course?** - Data analysts, data engineers, and cloud architects aiming to specialize in AWS data services. - Professionals seeking to validate their experience with an AWS industry credential. - Individuals comfortable with data technologies and AWS services, looking to expand their expertise into big data and machine learning integrations. **Pros:** - Extensive coverage of multiple key AWS data services. - Real-world scenarios that enhance practical understanding. - Preparation for a highly regarded industry certification. - Available in multiple languages including English, Japanese, Korean, and Simplified Chinese. **Cons:** - The course requires prior experience in data analytics and AWS, making it less suitable for absolute beginners. - The exam fee is relatively high, but justified by the recognition and career benefits. **Final Recommendation:** This course is highly recommended for seasoned data professionals who want to establish or advance their expertise in AWS big data and analytics solutions. Its thorough coverage of services and practical focus makes it an excellent investment for those pursuing industry certification and aiming to lead cloud-based data initiatives. If you meet the prerequisites and are committed to expanding your cloud data skills, enrolling in this course will be a valuable step toward achieving your professional goals. --- If you need more tailored advice or assistance with registration, feel free to ask!
FormatMultiple choice, multiple answerTypeSpecialtyDelivery MethodTesting center or online proctored examTime180 minutes to complete the examCost300 USD (Practice exam: 40 USD)LanguageAvailable in English, Japanese, Korean, and Simplified ChineseEarn an industry-recognized credential from AWS that validates your expertise in AWS data lakes and analytics services. Build credibility and confidence by highlighting your ability to design, build, secure, and maintain analytics solutions on AWS that are efficient, cost-effective, and secure. Show you have breadth and depth in delivering insight from data.The world of data analytics on AWS includes a dizzying array of technologies and services. Just a sampling of the topics we cover in-depth are:Streaming massive data with AWS KinesisQueuing messages with Simple Queue Service (SQS)Wrangling the explosion data from the Internet of Things (IOT)Transitioning from small to big data with the AWS Database Migration Service (DMS)Storing massive data lakes with the Simple Storage Service (S3)Optimizing transactional queries with DynamoDBTying your big data systems together with AWS LambdaMaking unstructured data query-able with AWS GlueProcessing data at unlimited scale with Elastic MapReduce, including Apache Spark, Hive, HBase, Presto, Zeppelin, Splunk, and FlumeApplying neural networks at massive scale with Deep Learning, MXNet, and TensorflowApplying advanced machine learning algorithms at scale with Amazon SageMakerAnalyzing streaming data in real-time with Kinesis AnalyticsSearching and analyzing petabyte-scale data with Amazon Elasticsearch ServiceQuerying S3 data lakes with Amazon AthenaHosting massive-scale data warehouses with Redshift and Redshift SpectrumIntegrating smaller data with your big data, using the Relational Database Service (RDS) and AuroraVisualizing your data interactively with QuicksightKeeping your data secure with encryption, KMS, HSM, IAM, Cognito, STS, and moreAbilities Validated by the CertificationDefine AWS data analytics services and understand how they integrate with each otherExplain how AWS data analytics services fit in the data life cycle of collection, storage, processing, and visualizationRecommended Knowledge and ExperienceAt least 5 years of experience with data analytics technologiesAt least 2 years of hands-on experience working with AWSExperience and expertise working with AWS services to design, build, secure, and maintain analytics solutions