How long does it take to complete the specialization?

The AWS Data, Integration & Modern Workloads specialization can be completed in approximately 7 hours. This includes both theoretical content and hands-on labs to ensure you gain practical experience with the various AWS services covered throughout the specialization.

Can I preview a course before enrolling?

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

When will I have access to the lectures and assignments?

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

What will I get when I enroll?

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

When will I receive my Course Certificate?

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

Why can’t I audit this course?

This course is currently available only to learners who have paid or received financial aid, when available.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

AWS Data, Integration and Modern Workloads

Ce cours n'est pas disponible en Français (France)

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AWS Data, Integration and Modern Workloads

Ce cours fait partie de Spécialisation "AWS Cloud Practitioner CLF-C02 Exam Training"

Instructeur : Packt - Course Instructors

Inclus avec

5 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

5 heures à compléter

Planning flexible

Apprenez à votre propre rythme

5 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

5 heures à compléter

Planning flexible

Apprenez à votre propre rythme

Ce que vous apprendrez

Master AWS database services (RDS, DynamoDB, Aurora, Redshift) and their use cases.
Integrate applications and workflows using SNS, MQ, SQS, and Step Functions.
Analyze data and develop machine learning models using AWS services like Athena, SageMaker, and Rekognition.

Compétences que vous acquerrez

Catégorie : Data Integration
Catégorie : Database Administration
Catégorie : Data Warehousing
Catégorie : Scalability
Catégorie : Extract, Transform, Load
Catégorie : Web Services
Catégorie : Real Time Data
Catégorie : Cloud Deployment
Catégorie : Databases
Catégorie : Data Integrity
Catégorie : Cloud-Based Integration

Outils que vous découvrirez

Catégorie : Amazon Web Services
Catégorie : Cloud Applications
Catégorie : AWS Kinesis
Catégorie : AWS SageMaker
Catégorie : Amazon Redshift
Catégorie : Amazon DynamoDB
Catégorie : Database Management Systems
Catégorie : Relational Databases
Catégorie : Middleware

Détails à connaître

Certificat partageable

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avril 2026

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Ce cours fait partie de la Spécialisation "AWS Cloud Practitioner CLF-C02 Exam Training"

Lorsque vous vous inscrivez à ce cours, vous êtes également inscrit(e) à cette Spécialisation.

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Il y a 5 modules dans ce cours

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.

In this module, we will introduce AWS database services, focusing on Amazon RDS and its use for managing relational databases. You’ll also gain hands-on experience with database creation and learn about other advanced database solutions like Aurora, DynamoDB, and Redshift. By the end, you’ll understand how to choose the right database service based on application needs and scalability requirements.

Inclus

5 vidéos2 lectures1 devoir

5 vidéosTotal 56 minutes

Introduction to Amazon RDS21 minutes
Create an RDS Database – Lab14 minutes
Amazon Aurora, DynamoDB, Redshift, and ElastiCache13 minutes
Database Migration Service (DMS)3 minutes
Additional Database Services6 minutes

2 lecturesTotal 20 minutes

Introduction to the Course 'AWS Data, Integration and Modern Workloads'10 minutes
Full Specialization Resource10 minutes

1 devoirTotal 15 minutes

AWS Database Services - Assessment15 minutes

In this module, we will explore Amazon Route 53, AWS’s scalable and highly available DNS web service. You’ll learn how to configure Route 53 for domain registration, routing policies, and ensuring failover mechanisms. By the end, you'll be equipped to manage the DNS needs of your web applications effectively.

Inclus

1 vidéo1 devoir

In this module, we will dive into AWS’s application integration services, starting with Amazon SNS for notifications, and moving to Amazon MQ and SQS for managing message-based workflows. Additionally, we’ll explore AWS Step Functions and SWF to streamline and orchestrate complex application workflows. You’ll gain the tools needed to integrate your applications efficiently on AWS.

Inclus

3 vidéos1 devoir

In this module, we will explore AWS analytics services, from querying data in Amazon S3 using Amazon Athena to processing real-time data streams with Amazon Kinesis. You’ll also gain insights into Amazon Glue for ETL processes and Amazon QuickSight for data visualizations. By the end, you’ll be prepared to leverage these tools for advanced data analytics in the cloud.

Inclus

4 vidéos1 devoir

In this module, we will introduce you to machine learning services on AWS, starting with Amazon Rekognition for analyzing images and videos. You’ll explore Amazon Polly for building speech-enabled applications and learn about Amazon SageMaker for end-to-end machine learning model development. This module will provide you with the foundational knowledge to integrate machine learning into your AWS applications.

Inclus

6 vidéos1 lecture3 devoirs

6 vidéosTotal 21 minutes

Amazon Rekognition5 minutes
Amazon Polly3 minutes
Amazon Translate2 minutes
Amazon Transcribe5 minutes
Amazon Comprehend3 minutes
Amazon SageMaker2 minutes

1 lectureTotal 10 minutes

Conclusion to the Course 'AWS Data, Integration and Modern Workloads'10 minutes

3 devoirsTotal 90 minutes

Machine Learning on AWS - Assessment15 minutes
Full Course Assessment60 minutes
Full Course Practice Assessment15 minutes

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Packt

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Foire Aux Questions

AWS Data, Integration & Modern Workloads is a specialization that covers the essential AWS services related to databases, application integration, analytics, and machine learning. It is relevant because modern workloads are increasingly reliant on scalable cloud infrastructure, and AWS provides powerful services for managing data, integrating applications, processing analytics, and implementing machine learning models. Understanding these services is crucial for handling the growing demand for data processing and AI capabilities in the cloud.

This specialization focuses on AWS services for database management, application integration, analytics, and machine learning. It includes hands-on lessons on using AWS tools like Amazon RDS, DynamoDB, and Aurora for databases, Route 53 for DNS, SNS and SQS for messaging, and Athena and Kinesis for real-time data processing. Additionally, you'll explore machine learning services such as Rekognition, Polly, and SageMaker, which empower developers to build intelligent, data-driven applications.

After completing this specialization, you will have the skills to design and implement database solutions using AWS, integrate various AWS services for application workflows, process and analyze large amounts of data, and apply machine learning techniques to enhance applications. You'll be equipped to use AWS’s tools for developing modern, scalable, and intelligent workloads, making you proficient in a wide range of AWS services for real-world applications.

A basic understanding of cloud computing concepts and experience with fundamental IT principles such as databases and networking will be beneficial. This specialization is beginner-friendly and designed for those who have some familiarity with AWS or cloud technologies. If you're new to AWS, the foundational knowledge covered in introductory AWS training will be helpful.

This specialization is designed for developers, data engineers, cloud architects, and IT professionals who want to deepen their understanding of AWS services related to data management, application integration, analytics, and machine learning. It’s ideal for those looking to build modern cloud-based workloads that leverage AWS’s powerful infrastructure and services.