DeepLearning.AI
Amazon Web Services
DeepLearning.AI Data Engineering Professional Certificate
DeepLearning.AI
Amazon Web Services

DeepLearning.AI Data Engineering Professional Certificate

Learn the principles of effective data engineering. Build your skills in the high-demand field of data engineering and learn how you can deliver real business value by applying a core set of principles and strategies for developing data systems.

Joe Reis

Instructor: Joe Reis

Top Instructor

11,588 already enrolled

Earn a career credential that demonstrates your expertise
4.8

(240 reviews)

Intermediate level

Recommended experience

3 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Earn a career credential that demonstrates your expertise
4.8

(240 reviews)

Intermediate level

Recommended experience

3 months
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Develop a mental model for the field of data engineering as a whole, including the data engineering lifecycle and its undercurrents.

  •  Learn a framework for approaching any data engineering project you work on so you can effectively create business value with data.

  • Build your skill in the five stages of the data engineering lifecycle; including generating, ingesting, storing, transforming, and serving data.

  • Learn the principles of good data architecture and apply them to build data systems on the AWS cloud.

Details to know

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Taught in English
Recently updated!

September 2024

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Professional Certificate - 4 course series

Introduction to Data Engineering

Course 117 hours4.8 (209 ratings)

What you'll learn

  • Gain a comprehensive understanding of the data engineering lifecycle and its undercurrents

  • Gather stakeholder needs and translate them into system requirements

  • Design and implement batch and streaming data pipelines on AWS

Skills you'll gain

Category: The principles of good data architecture
Category: Requirements Gathering
Category: AWS cloud fundamentals
Category: Thinking like a data engineer
Category: Translating requirements into tool and technology choices

Source Systems, Data Ingestion, and Pipelines

Course 234 hours4.6 (43 ratings)

What you'll learn

  • 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.

Skills you'll gain

Category: Networking on the Cloud
Category: DataOps
Category: Batch and Streaming Ingestion
Category: Data orchestration
Category: Infrastructure as Code (IaC)

Data Storage and Queries

Course 322 hours4.8 (30 ratings)

What you'll learn

  • Design storage architectures for various use cases, and select appropriate technologies to implement these architectures

  • Practice common query patters and identify ways to improve query performance and enhance the value of your data systems

Skills you'll gain

Category: Advanced SQL
Category: Data warehouse / data lake / data lakehouse architectures
Category: Data storage fundamentals
Category: Streaming queries with Apache Flink

Data Modeling, Transformation, and Serving

Course 427 hours4.7 (21 ratings)

What you'll learn

  • Model and transform data based on stakeholder needs to deliver business value

  • Choose the appropriate data processing tools for your architecture design

  • Process data for batch analytics and machine learning data pipelines using distributed and non-distributed processing frameworks

Skills you'll gain

Category: Data Modeling
Category: Feature Engineering
Category: Data Transformation
Category: Spark and PySpark

Instructor

Joe Reis

Top Instructor

DeepLearning.AI
4 Courses16,378 learners

Offered by

DeepLearning.AI

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Frequently asked questions

¹Based on Coursera learner outcome survey responses, United States, 2021.