AWS Data, Integration and Modern Workloads

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you'll dive into AWS's powerful data services and tools for modern workloads. Starting with Amazon RDS, you'll explore how to set up and manage relational databases on AWS. You'll also gain an understanding of advanced AWS database solutions, such as Aurora, DynamoDB, Redshift, and ElastiCache. Each of these services is tailored to different use cases, allowing you to choose the right database solution for your applications. Next, the course covers AWS Route 53 for DNS and domain management, enabling you to ensure high availability and failover capabilities for your websites and services. You will also explore Application Integration Services, including SNS, MQ, SQS, Step Functions, and SWF—all designed to integrate and coordinate your applications and workflows seamlessly. The course also dives into AWS's powerful Analytics tools like Athena, Kinesis, Elasticsearch, Glue, and QuickSight, which help you analyze large datasets, stream real-time data, and create insightful visualizations. You’ll also explore how Machine Learning services such as Rekognition, Polly, Translate, Transcribe, Comprehend, and SageMaker empower developers to build intelligent, scalable applications with advanced capabilities like image recognition, translation, text-to-speech, and NLP. This course is perfect for developers, data engineers, and professionals looking to expand their knowledge of AWS and modern data and machine learning workloads. While no formal prerequisites are required, familiarity with basic cloud computing concepts is beneficial. The course is designed for an intermediate skill level, ideal for those who want to level up their knowledge of AWS data services and machine learning tools. By the end of the course, you will be able to deploy, manage, and integrate databases on AWS, set up and use analytics and machine learning services, and design modern, scalable cloud workloads using AWS tools.

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