How long does it take to complete the program?

The program takes approximately 15 weeks to complete.

What are the prerequisites?

Intermediate Python programming and some familiarity working with data are the only prerequisites. Basic SQL and AWS Cloud services skills may be helpful but are not required.

Who is the instructor?

The instructor is Joe Reis, a data engineering leader and co-author of the best-selling book "Fundamentals of Data Engineering."

How will this program help in my career?

This program will equip you with practical skills and fundamental principles to start and build a career in the high-demand field of data engineering.

Do I need to take the courses in a specific order?

We recommend taking the courses in the prescribed order for a logical and consistent learning experience.

How much does this Professional Certificate cost?

A Coursera subscription costs $49 / month.

I want to purchase this program for my employees. How can I do that?

Visit coursera.org/business for more information, to pick up a plan, and to contact Coursera. For each plan, you decide the number of courses every member can enroll in and the collection of courses they can choose from.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Certificate, you’re automatically subscribed to the full Certificate. Visit your learner dashboard to track your progress.

DeepLearning.AI Data Engineering Professional Certificate

Top instructor

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.

Instructor: Joe Reis

4 course series

Earn a career credential that demonstrates your expertise

4.7

(516 reviews)

Intermediate level

Recommended experience

3 months at 10 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

4 course series

Earn a career credential that demonstrates your expertise

4.7

(516 reviews)

Intermediate level

Recommended experience

3 months at 10 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

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.

Overview

The DeepLearning.AI Data Engineering Professional Certificate is a comprehensive online program for data engineers and practitioners looking to start or grow their careers.

Organizations of all sizes and across all industries are capturing and generating data at an ever-increasing pace. Within these organizations, every team, from executives, sales and marketing, finance and operations, product and engineering, to customer service, can derive insights and value from organizational data. Whether the end use case is data science, machine learning, or analytics, data engineering is what allows raw data to be converted to value for the business. This is why the role of data engineer is one of the highest-demand jobs in tech today.

Throughout this program, you'll learn the foundations of data engineering while gaining hands-on experience designing and implementing data architectures using AWS and open-source tools.

Taught by industry expert Joe Reis, co-author of Fundamentals of Data Engineering, this certificate equips you with the skills and knowledge to excel in a high-demand field, focusing on ingesting, processing, transforming, storing, and serving data to data stakeholders to drive organizational and business objectives. The practical labs were developed in partnership with AWS and Factored.AI to provide you with an authentic experience building data systems on the cloud.

With this certificate, you will have the tools to further your data engineering career.

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English

18 practice exercises

Professional Certificate - 4 course series

In this program, you'll:

Translate stakeholder needs into system requirements and choose the appropriate tools to build the system.
Build end-to-end batch and streaming pipelines on AWS for a product recommendation system.
Apply principles of good data architecture to assess the security, performance, reliability, and scalability of data systems on AWS.
Explore various types of source systems and troubleshoot common connectivity issues.
Use infrastructure and pipelines as code tools to orchestrate, automate, and monitor your data pipelines.
Design data lake and data lakehouse storage architectures for various use cases.
Explore the impact of data storage choices on query performance and cost.
Model and transform data for analytics and machine learning use cases and compare centralized processing frameworks such as Pandas with distributed processing frameworks like Spark.
Serve your data to downstream data stakeholders for business analytics and machine learning use cases.

Introduction to Data Engineering

Course 117 hours4.8 (429 ratings)View course

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

Data Pipelines, Requirements Analysis, Data Architecture, System Requirements, Amazon Web Services, Data Transformation, Scalability, Data Processing, Performance Tuning, Data Modeling, Security Controls, and Data Warehousing

Source Systems, Data Ingestion, and Pipelines

Course 234 hours4.8 (120 ratings)View course

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

Data Pipelines, Extract, Transform, Load, Terraform, Infrastructure as Code (IaC), NoSQL, Data Quality, Apache Airflow, Data Integration, Data Processing, Amazon Web Services, CI/CD, and Amazon CloudWatch

Data Storage and Queries

Course 322 hours4.8 (74 ratings)View course

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

Data Storage, Query Languages, Cloud Storage, Data Lakes, SQL, Data Architecture, Amazon Web Services, Database Management Systems, Data Warehousing, Databases, Performance Tuning, Database Systems, and Apache Spark

Data Modeling, Transformation, and Serving

Course 432 hours4.5 (85 ratings)View course

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

Data Transformation, Star Schema, Apache Spark, Data Pipelines, Data Modeling, Feature Engineering, Extract, Transform, Load, Real Time Data, Machine Learning, Applied Machine Learning, Data Processing, Data Manipulation, Data Warehousing, and Apache Hadoop

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Top Instructor

Joe Reis

DeepLearning.AI

4 Courses37,519 learners

Offered by

DeepLearning.AI

Amazon Web Services

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Frequently asked questions

The focus of this program is to provide foundational training in the field of data engineering that includes both conceptual knowledge and principles as well as practical skills for building data systems on the AWS cloud.

This course is ideal for aspiring or practicing data engineers, as well as data professionals in adjacent roles like software engineering, data science, or analytics looking to broaden and deepen their skills in data engineering. Other data stakeholders such as data team leads and technical business leaders will also find value in these courses as they think about data systems and structures at the organizational level.

You will learn about the stages of the data engineering lifecycle, including generation, ingestion, storage, transformation, and serving data, as well as the s undercurrents of the lifecycle including security, DataOps, Data Management, Data Architecture, Orchestration, and Software Engineering. You’ll also learn how to design good data architecture, choose tools and technologies, and build data pipelines on the AWS cloud.

You will receive a certificate at the end of each course if you pay or receive financial aid for the courses and complete the assessments. There is a limit of 180 days of certificate eligibility, after which you must re-purchase the course to obtain a certificate. If you audit the course for free, you will not receive a certificate.

If you complete all 4 courses in the Professional Certificate, you will also receive an additional certificate showing that you completed the entire Professional Certificate.

You can only get the DeepLearning.AI Data Engineering Professional Certificate if you enroll in the DeepLearning.AI Data Engineering specialization and complete all four courses. If you enrolled in each individual course, you will get the course certificate on completion of each of the four courses but you will not receive the professional certificate.

DeepLearning.AI Data Engineering Professional Certificate

What you'll learn

Overview

Skills you'll gain

Tools you'll learn

What’s included