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This course is part of DeepLearning.AI Data Engineering Professional Certificate
Instructor: Joe Reis
Top Instructor
6,192 already enrolled
(73 reviews)
Recommended experience
Intermediate level
Intermediate Python and basic data skills required. SQL & AWS knowledge is helpful but not needed. Completing course 1 is recommended.
(73 reviews)
Recommended experience
Intermediate level
Intermediate Python and basic data skills required. SQL & AWS knowledge is helpful but not needed. Completing course 1 is recommended.
Gather stakeholder needs and translate them into system requirements.
Implement a batch and a streaming ingestion process on AWS to ingest data from various source systems.
Integrate aspects of security, data management, DataOps and orchestration into the data systems you build.
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September 2024
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In this course, you will explore various types of source systems, learn how they generate and update data, and troubleshoot common issues you might encounter when trying to connect to these systems in the real world. You’ll dive into the details of common ingestion patterns and implement batch and streaming pipelines. You’ll automate and orchestrate your data pipelines using infrastructure as code and pipelines as code tools. You’ll also explore AWS and open source tools for monitoring your data systems and data quality.
In lesson 1, you will explore source systems data engineers commonly interact with. Then in lesson 2, you will learn how to connect to various source systems and troubleshoot common connectivity issues.
21 videos9 readings1 assignment1 programming assignment3 ungraded labs
This week you will dive deep into the batch and streaming ingestion patterns. You will identify use cases and considerations for each, and then build a batch and a streaming ingestion pipeline. When looking at batch ingestion, you will compare and contrast the ETL and ELT paradigms. You will also explore various AWS services for batch and streaming ingestion.
11 videos6 readings1 assignment1 programming assignment1 ungraded lab
In the first lesson, you will explore DataOps automation practices, including applying CI/CD to both data and code, and using infrastructure as code tools like Terraform to automate the provisioning and management of your resources. Then in lesson 2, you will explore DataOps observability and monitoring practices, including using tools like Great Expectation to monitor data quality, and using Amazon CloudWatch to monitor your infrastructure.
17 videos5 readings1 assignment1 programming assignment2 ungraded labs
This week, you will learn all about orchestrating your data pipeline tasks. You'll identify the various orchestration tools, but will focus on Airflow -- one of the most popular and widely used tools in the field today. You'll explore the core components of Airflow, the Airflow UI, and how to create and manage DAGs using various Airflow features.
11 videos5 readings1 assignment1 programming assignment2 ungraded labs
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
DeepLearning.AI is an education technology company that develops a global community of AI talent. DeepLearning.AI's expert-led educational experiences provide AI practitioners and non-technical professionals with the necessary tools to go all the way from foundational basics to advanced application, empowering them to build an AI-powered future.
Since 2006, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 90 fully featured services for compute, storage, networking, database, analytics, application services, deployment, management, developer, mobile, Internet of Things (IoT), Artificial Intelligence, security, hybrid and enterprise applications, from 44 Availability Zones across 16 geographic regions. AWS services are trusted by millions of active customers around the world — including the fastest-growing startups, largest enterprises, and leading government agencies — to power their infrastructure, make them more agile, and lower costs. Coursera and AWS have been partners since 2017 providing learners and enterprises globally, the skills they need to succeed. Coursera builds on AWS servers to scale with student demand with confidence around capacity and elasticity and in partnership with AWS. In 2019, Coursera achieved Advanced Tier Partner status and further extended the partnership with AWS Educate, AWS EdStart and AWS Academy collaborations. Coursera's been able to make cloud skills more accessible with 8 AWS courses on the Coursera platform featuring top subject matter experts and the portfolio continues to grow. To learn more about AWS, visit https://aws.amazon.com.
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Reviewed on Jan 18, 2025
great learning and exercises. appreciate the community.
Reviewed on Nov 19, 2024
All concepts related to these topics are explained clearly.
Reviewed on Nov 23, 2024
Really valuable, and I got an idea of data-related concepts and infrastructure management.
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