Data Engineer Courses Online

Data Engineer Courses for Online Learning

Love data? Love learning how to collect, store, and analyze it at scale? Neither do I. Just kidding! But if you’re thinking of becoming a data engineer, here are some of the best data engineering courses for online learning.

Data is the lifeblood of any business. But it’s data engineers who build the data pipelines that enable decision-making, and it allows companies to take action on information.

Think of data engineers like the ones who build bridges between different business functions by helping them extract, transform, and analyze the information that is collected.

Data engineering is one of the highest-paying jobs in tech ($115,000), and the skills you learn can be used in many different industries. Get started with these 10 data engineering courses online.

1. Data Engineer Nanodegree Program (Udacity)

Udacity

The Udacity Data Engineer Nanodegree Program is an intensive program that will teach you how to build data warehouses, automate data pipelines, and work with big data. You’ll also learn how to use industry-leading tools like Spark, Apache Airflow, and Apache Cassandra. By the end of the program, you’ll have a portfolio project to show off your skills to future employers.

PROS

  • Learn all the data engineering skills you need to be successful in a data-driven world.
  • Designed around the latest technologies and tools, and taught by industry experts.
  • The only program that provides mentorship, resume/CV, and career services.

CONS

  • Although it’s the best data engineering program hands-down today, it’s also the most costly.
COURSES
  • Data Modeling: Get the skills you need to build and manage databases using ETL in PostgreSQL and Apache Cassandra.
  • Cloud Data Warehouses: Get started with a cloud data warehouse on Amazon Web Services (AWS). Learn from experts and take a deep-dive into data warehousing and its infrastructure.
  • Spark and Data Lakes: This course will teach you how to use big data with Spark and how to use it to store, manage and query big data in a data lake.
  • Data Pipelines with Airflow: Learn how to use Apache Airflow to create data pipelines and run quality checks in production.
  • Capstone Project: Build your own data engineering portfolio project to showcase your skills, knowledge from the program.
VERDICT

Enroll today in the Udacity Data Engineer Nanodegree Program to help make sound data science decisions as a data engineer. In this program, you’ll learn how to create cloud-based data warehouses on Amazon Web Services (AWS). You’ll also gain a deeper understanding of data infrastructure, so you can put your data to work for any business.

InstructorUdacity
Duration5 months (5 – 10 hours per week)
CertificationData Engineer Nanodegree Program
PrerequisitesIntermediate Python & SQL
Skills AcquiredPostgreSQL, Apache Cassandra, ETL, NoSQL data models, Spark, Apache Airflow, SQL, and Python

2. Professional Certificate in Data Engineering (IBM)

IBM

Data engineering is a specialized field of computer science involving the collection, storage, and retrieval of big data for meaningful insights. The IBM Professional Certificate in Data Engineering is designed for anyone with an interest in the development of such applications for data pipelines and warehouses. In this 14-course program, you can also gain insights into cloud-based relational database (RDBMS) models as well as NoSQL data repositories.

PROS

  • Great pivot point for anyone learning data engineering to launch an entry-level data engineer career.
  • Receive expert instructions from IBM, which look great on any CV/resume.
  • Finalize the certificate with a Capstone project.

CONS

  • It has a long time of dedication (over one year) with a total of 14 courses to complete the certificate.
  • Slight focus on IBM products and services like IBM Db2, IBM Cloudant, etc.
COURSES
  • Python for Data Engineering: Gain the fundamental knowledge and skills you need for your career in data engineering such as its ecosystem, lifecycle, and tools to manage data for decision-making.
  • SQL for Data Engineers: A deeper understanding of SQL will allow you to extract the right data you need from data warehouses. This course teaches SQL for Data Engineers so you will have a more powerful understanding of the concepts and tools at your disposal.
  • Building ETL and Data Pipelines: Learn how to use the latest technologies to build data pipelines and ETL processes from a shell script, Airflow, and Kafka.
  • Big Data, Hadoop, and Spark Basics: Develop a deeper understanding of big data as a whole. Master the use of advanced big data tools. Learn how to analyze and interpret data with Hadoop and Spark.
  • Machine Learning Pipelines: Learn how to create machine learning pipelines using Apache Spark. Build your own ETL pipelines SQL to prepare data for ML workflows.
  • Data Engineering Capstone Project: Demonstrate your skills and knowledge through a Capstone Project designed for data engineers using BI tools, Bash, Data Warehousing, Python, and Big Data.
VERDICT

Data-driven technology is transforming businesses, and the most successful companies of today will be those who understand and leverage data. To gain a competitive edge in today’s data-driven global economy, you need to tap into the power of data engineering. The IBM Professional Certificate in Data Engineering is one of the top data engineering course programs today to learn this versatile skillset.

InstructorIBM Professional Certificate in Data Engineering
Duration1 year and 2 months (3 – 4 hours per week)
CertificationProfessional Certificate in Data Engineering
Coursework14 skill-building courses
Skills AcquiredHadoop, Spark, Kafka, SQL, NoSQL, RDBMS, Bash, Python, ETL, Data Warehousing, BI tools, Big Data, MySQL, PostgreSQL, and IBM Db2.

3. Data Engineer with Python (DataCamp)

DataCamp

If you’re looking to become a data engineer and become more proficient in Python, DataCamp has you covered. The Data Engineer with Python track will teach you the fundamentals of building your own data architecture and scale for high-volume data processing. This hands-on track will also teach you how to work with cloud and big data tools like AWS Boto, PySpark, Spark SQL, and MongoDB.

PROS

  • DataCamp is a great starting point for introducing data engineering and jumping into the world of data science.
  • Learn an extremely diverse variety of skill sets in bite-size lessons from 21 modules.

CONS

  • Useful for learning how to write small pieces of code but does not teach you other aspects like machine setup.
  • No final project to apply the knowledge you’ve gained to showcase your new skills.
COURSES
  • Intermediate/Advanced Python: Develop a solid knowledge of the fundamentals of Object-Oriented Programming (OOP) such as inheritance and polymorphism, and gain an arsenal of skills to help you become a better Python programmer.
  • Data Pipelines: Learn how to manage data with distributed data management and automate the scheduling of repetitive tasks through Apache Airflow.
  • Optimizing Data Workflows: Explore how to use AWS Boto in Python and Scala to deploy scalable Cloud applications and optimized data engineering infrastructure.
  • Big Data Fundamentals: Get a crash course in the fundamentals of big data and learn how to work with large sets of data with PySpark.
VERDICT

You’ll learn how to create and query databases, wrangle data and configure schedules to run your pipelines. You’ll also learn about Shell, SQL, and Scala – so you can create data engineering pipelines, automate common file system tasks, and build a high-performance database. By the end of the Data Engineer with Python track, you’ll be ready for your next career move into this growing field.

InstructorDataCamp
Duration73 hours
CertificationData Engineer with Python
Courework19 courses
Skills AcquiredAWS Boto, PySpark, Spark SQL, MongoDB, Shell, SQL, and Scala

4. Data Engineering Career Path (Dataquest)

Dataquest

If you want to be a data engineer, you need to understand fundamental concepts such as algorithms and data structures. The Data Engineer Career Path by Dataquest will help you learn how to build data pipelines, how to use PostgreSQL for data engineering, and how to analyze large sets of data using SQL queries. Develop the skills employers are looking for today in the field of data engineering.

PROS

  • Complete guided projects at the end of every course to put your knowledge into practice.
  • Build a portfolio by learning real code that you can showcase to future employers.
  • Receive sharable certificates upon completion of a career path course.

CONS

  • Although the course material is of high quality, the instructor is not from an industry-leading firm like IBM or Google.
COURSES
  • Build a foundation in Python programming: Python is a programming language that is easy to learn and use. Even if you’re at a beginner level, Dataquest can get you started writing real code quickly through its hands-on and interactive instructions.
  • Use PostgreSQL for Data Engineering: This course will teach you how to use PostgreSQL for data engineering. It’ll cover topics like data modeling, database design, and best practices for managing data in your projects.
  • Build data pipelines: This course introduces you to the world of data pipelines, with hands-on training that will help you build your own pipeline that is reliable, scalable, and easy to work with.
VERDICT

The Data Engineering Career Path from Dataquest will give you a deep understanding of how to design and implement data engineering solutions for business organizations. You’ll learn about the fundamentals of data pipelines, data quality, and analytics and will cover topics such as recursion and trees, big data optimization, algorithms, and data structures.

InstructorDataquest
CertificationData Engineering Career Path
PrerequisitesIntroductory Python and SQL
Coursework21 courses
Skills AcquiredPython, PostgreSQL, SQL, Pandas, NumPy, and MapReduce

5. Professional Certificate in Data Warehouse Engineering (IBM)

IBM

Nowadays, data warehousing and analytics are playing a significant role in enhancing business performance through reporting, monitoring, and analysis. The Professional Certificate in Data Warehouse Engineering from IBM allows you to develop your knowledge in this field and gain skills that enable you to implement successful solutions within your organization or start a data analytics business on your own.

PROS

  • Receive expert instructions from IBM, which can be a centerpiece on any CV/resume.
  • Focus is on building data warehouses but gives instructions for other applications like BI tools and SQL as well.
  • Great for labs and hands-on instructions.

CONS

  • Some areas catered to IBM products such as the business intelligence tools with Cognos.
COURSES
  • Data Engineering Basics for Everyone: You will learn the concepts and tools that data engineers need in their daily work. You will also gain a better understanding of the data ecosystem as well as the systems, processes, and tools that data engineers use in order to transform, load, process, and manage data.
  • SQL Concepts and RDBMS for Data Engineers: In this course, you will learn how to design, implement, troubleshoot, and automate databases such as MySQL, PostgreSQL, and Db2 with an emphasis on SQL concepts and RDBMS for data engineers.
  • Building ETL and Data Pipelines with Bash, Airflow and Kafka: Explore how to build data pipelines through Extract, Transform, Load (ETL) processes using shell scripts, Airflow and Kafka.
  • Data Warehousing and BI Analytics: From populating a data warehouse, this course will guide you through the process of using SQL for retrieval and Business Intelligence (BI) tools for analysis.
VERDICT

Data warehouses are a powerful tool in organizations seeking to better manage and understand their data by helping companies to process information more efficiently and effectively. The Professional Certificate in Data Warehouse Engineering is designed to teach students the basics of data warehouse engineering. With this program, students learn how the data warehouse functions at a conceptual level, along with how it can be implemented into a business.

InstructorIBM
Duration9 months (3 – 4 hours per week)
CertificationProfessional Certificate in Data Warehouse Engineering
Coursework8 skill-building courses
Skills AcquiredETL, Shell scripts, Airflow, Kafka, MySQL, PostgreSQL, Db2, RDBMS, IBM Cognos Analytics

6. Postgres For Data Engineers (Dataquest)

Dataquest

Many data engineers are now looking to PostgreSQL as their go-to database of choice. As a data engineer, you’re responsible for designing and building systems for enterprise-level data processing. You might be in charge of the entire data pipeline from acquisition through analysis and reporting. In the Postgres For Data Engineers track from Dataquest, you’ll learn how to use Postgres, one of the most popular open-source relational databases, to create efficient, robust systems that will help your organization reach its goals.

PROS

  • Learn how to use Postgres and ensure the efficiency of your data in all aspects of operations.
  • Apply your skills by loading and deploying a database with real data from crime reports.

CONS

  • Not enough career support and mentorship feedback is available.
  • You learn to code from day one, but some graduates still feel a lack of ability to translate skills into the workplace.
COURSES
  • Intro to Postgres: Get an understanding of the core concepts of Postgres, including how to create tables, data types, and relations.
  • Loading and Extracting Data with SQL: Gain a better understanding of the language and learn how to create and query data using SQL. You will be able to create and execute queries in SQL that extract data from an API with authentication.
  • User and Database Management: You’ll learn everything you need to know about managing users, databases, and permissions. This course will teach you to plan, deploy, and manage the databases and administer it.
  • Project: Building a Database for Crime Reports: You will learn how to install and configure PostgreSQL and the Psycopg2 library. Next, you will apply what you have learned to set up a database from scratch and administer users, groups, schemas and tables.
VERDICT

This is a program for data engineers who need to learn about Postgre, designed for anyone ready to take the next step in their career. The Postgres For Data Engineers track includes content on how SQL works, user management, and finishes it off with a hands-on project. It also includes a review of the basic functions of PostgreSQL and a walk-through of query planning and execution in PostgreSQL.

InstructorDataquest
Duration7 Courses
CertificationPostgres For Data Engineers
PrerequisitesNone
Skills AcquiredPostgres, Psycopg2, CSV, SQLite, and Python

7. Microsoft Azure Data Engineering Associate DP-203 Exam Prep Specialization

Microsoft

There are many paths to becoming a Microsoft Azure Data Engineering Associate. One of the most rewarding ways to prepare for it is by taking the Microsoft Azure Data Engineering Associate Exam Prep Specialization courses offered by Coursera. This specialization is a 10-course curriculum designed for those with no experience in data engineering, as well as those who have some experience but want to take their skills to the next level. The course covers all topics that would be on the exam and provide you with hands-on experience using real-world scenarios.

PROS

  • Learn from Microsoft and improve your knowledge for the Microsoft Azure Data Engineering Associate Exam.

CONS

  • Technical information from courses are unstructured with some areas filled with only theory.
  • Exercises to build hands-on skills have data missing with a drop-off in content in some topics.
  • No career or CV/resume support upon completion.
COURSES
  • Data Engineering with Microsoft Azure: Explore the Azure cloud environment with an overview on the different tools available for data, artificial intelligence, and analytics projects available through the platform.
  • Data Storage and Integration: Gain an understanding of the basics of storage management in Azure, configure a storage account, and select a suitable model for storing data in the cloud.
  • Data Warehousing and Engineering: Build modern data warehouses and operational analytical solutions through Azure Synapse Analytics. You’ll explore how to load data into a data warehouse and how to optimize query performance.
  • Preparation for Data Engineering on Microsoft Azure Exam: This course is a must-take for students who want to prepare for the Microsoft Azure Data Engineering Associate Exam. Acquire the knowledge you need to take the exam so that you can get certified.
VERDICT

Microsoft Azure is a powerful platform for data processing and analytics. Whether you want to learn anything about Microsoft Azure like data lakes, operational analytics, or just want to boost your knowledge for the exam, the Microsoft Azure Data Engineering Associate Exam Prep Specialization is a good choice for you.

InstructorMicrosoft
Duration13 months (2 hours per week)
CertificationMicrosoft Azure Data Engineering Associate DP-203 Exam Prep Specialization
LevelIntermediate
Skills AcquiredAzure Synapse Analytics, Azure Databricks, Apache Spark, Modern Data Warehouses, Azure Cosmos DB, Azure Synapse Link, and Azure Data Lake Storage

8. Professional Certificate in Data Engineering Fundamentals (IBM)

IBM

Data engineers are at the center of the data science revolution as they build pipelines that help organizations make sound decisions. The IBM Professional Certificate in Data Engineering Fundamentals provides a comprehensive introduction to these topics with hands-on training from data engineering ecosystems to lifecycles.

PROS

  • Receive training from a world-class institute of technology with IBM.
  • Add a feather to your cap by adding this certificate to your resume to potential employers.

CONS

  • Only teaches foundational skills for engineering concepts without getting into as much hands-on detail as other certification programs.
COURSES
  • Data Engineering Basics: This course provides an overview of the roles, key skills, and critical tasks required to be successful in a data engineering. For instance, you will learn about ecosystems, lifecycles, gathering, transforming, loading, and querying.
  • Python Basics for Data Science: Gain the skills and confidence to apply data science techniques in Python through lab exercises.
  • Relational Databases and SQL: Learn the practical skills you’ll need to extract, manipulate, and share data in the simplest and most efficient ways possible. This course includes examples of how to use SQL to work with relational databases.
VERDICT

The IBM Professional Certificate in Data Engineering Fundamentals focuses on the foundational concepts and skills needed to build a career as a data engineer. You’ll learn how to use Python, SQL, and an overview of what you need to be a successful data engineer.

InstructorIBM
Duration4 months (4 – 6 hours per week)
CertificationProfessional Certificate in Data Engineering Fundamentals
Coursework6 skill-building courses
Skills AcquiredPython, SQL, and RDBMS

9. Introduction to Designing Data Lakes in AWS (Amazon)

Amazon Web Services

Amazon Web Services (AWS) is one of the best cloud computing platforms for data-intensive workloads. However, it can be challenging to set up and manage a secure and scalable data lake architecture. The Introduction to Designing Data Lakes in AWS course will introduce you to data lakes in AWS answering the “why” and the “how”.

PROS

  • Get instructions from Amazon Web Services (AWS) for an introductory level course in data lakes.
  • Great pace for learning with engaging course material.

CONS

  • Overview course on a single topic without intermediate to advanced level topics.
  • No Capstone project or anything too challenging to test your knowledge.
COURSES
  • Data Lake Fundamentals: You’ll explore what a data lake is and its characteristics, as well as how they are different from data warehouses. You’ll also learn about the components that make up a data lake, as well as how they are implemented and managed.
  • Data Cataloging and Ingestion: When you need to process data, this course will help you prioritize the right time to do so and control data flow.
  • Data Processing and Optimization: Learn how to improve performance and efficiency of your dataset by learning best practices to use the best tool for data processing.
VERDICT

When creating a data lake in AWS, it’s important to have a good foundation of what’s required. For instance, you will have to consider how your data is processed, managed, and understood. The Introduction to Designing Data Lakes in AWS course will walk you through the process of designing a data lake in AWS that meets your business needs.

InstructorAmazon
Duration14 hours
CourseIntroduction to Designing Data Lakes in AWS
LevelIntermediate
Skills AcquiredAmazon Web Services (AWS), Amazon S3, AWS Glue, Amazon Athena, Amazon Elasticsearch Service, LakeFormation, Amazon Rekognition, API Gateway, AWS Transfer Family, Amazon Kinesis Data Streams, Kinesis Firehose, Kinesis Analytics, AWS Snow Family, AWS Glue Crawlers

10. Data Structures and Algorithms Nanodegree (Udacity)

Udacity

In the Data Structures and Algorithms Nanodegree from Udacity, you will learn over 100 data structures and algorithms, so you can create code that is efficient and accurate. Get the skills you need to pass interviews and the next level of development.

PROS

  • Get trained by industry experts at Udacity on a well-built online learning platform.
  • Enjoy reaching out to a community of students and get personalized project reviewers.

CONS

  • Strict review process with high standards for passing and forces to retaking of projects.
COURSES
  • Data Structures: Get a better understanding of data structures and how to store data. Understand different algorithms used to manipulate any data structures and examine the efficiency of these methods.
  • Basic Algorithms: Learn how to use basic algorithms to solve various problems. This course will help you improve your understanding of algorithms and their efficiency.
  • Advanced Algorithms: Get up to speed with some of the most complex algorithms available, so you can build more complex and innovative solutions. This course will teach you how to apply these algorithms to real-world problems.
VERDICT

Data structures and algorithms are important tools for programmers. However, they can also be challenging to learn. That’s why the Data Structures and Algorithms Nanodegree is essential for anyone looking to learn these skills. By mastering these concepts, you’ll be able to create efficient and effective code that will help your application work better.

InstructorUdacity
Duration4 months (10 hours per week)
CertificationData Structures and Algorithms
PrerequisitesPython and Basic Algebra
Skills AcquiredPython, SQL, and Algebra

Data Engineer Courses Online

Data engineering is a complex but rewarding career that combines both programming and databases. It’s also one of the highest-paying jobs in tech ($115,000) today. We introduced you to 10 data engineering courses for online learning.

With this list of data engineering courses, you can learn how to hone your skills and make them become the focal point of your CV/resume.

Once you master these skills, you never know what opportunities may be waiting in the exciting field of data engineering.

Whether or not you’re interested in data engineering or just want to get started in data science, here are some certificate options to get started.

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