Data Engineering Courses
Learn the skills you'll need to become a data engineer in our start-to-finish sequence of interactive data engineering courses!
Why take a data engineering course?
First, you might want to become a data engineer! Working in data engineering is a challenging and satisfying career that pays, on average, more than $131,000/year as of 2020.
But even if you don't aspire to work as a data engineer, data engineering skills are the backbone of data analysis and data science. Learning about Postgres, being able to build data pipelines, and understanding how to optimize systems and algorithms for large volumes of data are all skills that'll make working with data easier in any career.
Read more about why everyone should learn data engineering, or keep scrolling to find out what you'll learn in our data engineering courses!
What's Covered in Our Data Engineering Courses?
Learn how to build data pipelines to work with large data sets.
This path will teach you how to use Python and pandas to work with large data sets, and load and pipe data through a Postgres database.
In this path, you'll learn how to optimize processes for big data, build data pipelines, and more!
Don't worry if you don't know what any of that means yet. You can start our step-by-step sequence of data engineering courses as a total beginner — no coding experience required!
Through it all, you'll be writing real code and analyzing real data. And at the end of the course, you'll complete your first real data engineering project using your new skills!
Who Needs Data Engineering Skills?
If you aspire to work as a data engineer, then these skills are absolutely mission-critical.
But these courses aren't just for aspiring data engineers! Everyone who works with data can benefit from learning data engineering skills!
In our data engineering courses, you'll learn how to optimize your code for faster processing and better handling of large data sets. You'll learn to build data pipelines and processes that are scalable and repeatable. These are valuable skills that'll make you more self-sufficient and valuable in all of your work with data.
Read more about the value of learning data engineering or sign up and start learning for free right now!
Learn by doing with Dataquest!
In all of Dataquest's data engineering courses:
Best of all, it's totally free to get started!
Data Engineering FAQ
Is data engineering hard?
Data engineering is a challenging and highly technical profession, so you should certainly expect to be challenged as you dive into learning these skills.
However, with patience and dedication, these are skills that anyone can learn.
Our course sequence is designed to help take you from total beginner to job-qualified with no gaps or prerequisites, and we've made the journey as smooth as possible.
But if you're not being challenged, you're not really learning! You should come in knowing that you can do it, but expecting a challenge.
How long does it take to learn data engineering?
That depends on how much time you can dedicate to learning, and how consistent you are with sticking to your schedule.
Dataquest's learning platform is fully interactive and self-serve, meaning that you can learn anytime you want, for as long as you want. You don't need to wait for "classes" to start. You learn on your own schedule.
If you're starting from scratch, you can expect to have added valuable professional skills to your skillset within just a few hours!
How long it takes to finish the entire course sequence will depend heavily on your habits and schedule, but most students who complete the path and earn the certificate are able to do so with around six months of part-time study.
What's the best data engineering certificate?
Although Dataquest offers a data engineering certificate, we'll let you in on a little secret — similar to data science certificates, data engineering certificates don't really matter.
Because data science as a whole is a new industry, there really are no established or required credentials for data engineers. Employers aren't looking for a specific name on your resume. What they are looking for is proof of skills.
Learning certificates don't prove that you have the skills to actually do a job. What employers want to see on your resume is either relevant work experience or, if you don't have professional experience, relevant projects.
When you're applying for jobs, your projects and Github portfolio will be critical — they're the proof that you actually have the skills you're claiming. That's why Dataquest's curriculum is project-based, and why we place so much emphasis on building personal projects.
Do data engineers earn more than data scientists?
It varies from place to place and from job to job. As of November 2020, here are the average base salaries for US-based data engineers and data scientists, according to Indeed:
As you can see, while data engineers do earn a little more (based on Indeed's data set), the difference isn't very dramatic. In some locations, the gap may be wider, but the bottom line is that both roles offer excellent average salaries and good career paths to Senior and higher-level positions with even more earning potential.
Rather that choosing based on salaries, you may want to learn more about each role and choose based on which sounds like the best fit for you. We've even got a quiz to help with that!
What are the prerequisites for these courses?
Our data engineering course path is designed for total beginners, so there are no prerequisites! Even if you've never written a line of code before, you can dive in and start learning.
There's also no application process. Our platform is self-serve. All you have to do is sign up for a free account. You'll be writing and running your first code in less than five minutes!
How can I get help while I'm learning?
Learning data engineering can definitely be challenging, but we're here to help! There are a few different ways you can get help when you find yourself stumped or confused in one of our courses:
First, you can opt to view a hint designed to help you with your current task. These hints won't give you the answer; they're just there to nudge you in the right direction.
If the hint doesn't help, you can also choose to view the correct answer. Sometimes, that's all it takes to help you figure out the thing you didn't understand.
But sometimes, there's no substitute for personal, one-on-one help. That's why we have an active learner community! You can post your questions there and get personal help from other students and our learning assistants. Over 99% of student questions posted to our community receive answers!
Those answers typically come fast, bit if you don't want to wait, you can also search through the post archives. Often, you'll find your question has already been asked and answered!
What do learners say about our courses?
recommend Dataquest for career improvement
8 in 10
say learning with Dataquest has improved their lives
total missions completed by Dataquest learners
For more on what our learners think of Dataquest, check out our student outcomes.
Our Data Engineering Course Sequence
This is what you'll learn in our Data Engineering career path!
Learn about the fundamentals of Python programming in the context of data engineering.
Learn important tools for your Python data toolbox.
Programming Concepts with Python
Enhance your understanding of how Python works.
Learn how to assess and implement efficient algorithms with Python.
Learn the basics of working with SQL databases.
Intermediate SQL for Data Analysis
Learn to work with multi-table databases.
Postgres for Data Engineers
Learn about the SQL database Postgres.
Optimizing Postgres Databases
Learn how to optimize your Postgres databases.
NumPy for Data Engineers
Learn how NumPy can be used to optimize your data processing.
Processing Large Datasets in Pandas
Learn how to work with datasets by optimizing your pandas workflow, processing data in batches, and augmenting pandas with SQLite.
Learn parallel processing and MapReduce.
Data Structures Fundamentals
Learn the fundamentals of data structures — Linked Lists, Queues, Stacks and Dictionaries, etc.
Recursion and Trees
Learn about recursion and how it applies to tree data structures, and how tree data structures are used to speed up processing of data analysis tasks.
Building a Data Pipeline
Learn how to build a Python data pipeline from scratch.