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ONLINE INTRODUCTION TO DATA ENGINEERING COURSE

Learn Valuable Tech Skills from Industry Experts

Ready to master the fundamentals of data engineering and become a stronger data scientist? This Data Engineering course will help you build skills and apply them to a project of your own design, so you can use your knowledge in the real world. 

ENROLL NOW

Upcoming Program Dates

Online Flex

Jan 31 - Feb 25

Flexible Schedule

Part-Time | Enroll

Online Flex

Feb 28 - Mar 25

Flexible Schedule

Part-Time | Enroll

Live Online

Mar 28 - Apr 8

11am - 6pm ET

Full-Time | Enroll

Questions?
Schedule a Call

Upskill in a Fast-Growing Field

It’s no secret that data engineering knowledge is widely recognized as an extremely important and in-demand skill set. Find out how our unique Short Immersive Course format will put you ahead of the curve.

Learn from Premier
Data Science
Instructors

Our teachers must have deep instructional know-how in addition to having an impressive amount of data knowledge.

Design Project for
Your Portfolio

You'll finish a professional project for your portfolio, showcasing your ability to apply the skills and knowledge you’ve just learned.

Skill Up Fast with Our
In-Depth Format

In-depth classes help you learn data engineering skills fast, so you can use them in your career.

Join the Metis
Professional Network

Connect and network with a far-reaching community of data science professionals who will become mentors and lifelong contacts.

The Metis Data Engineering Immersive Course at a Glance

ONLINE INTRODUCTION TO DATA ENGINEERING COURSE

Unit 1

Advanced Databases, Cloud Computing and Big Data Handling

In unit one we’ll dive into advanced database tools, cloud computing, and big data handling tools, and how to leverage them in a real world setting.

Unit 2

Advanced Programming and Web Applications

In unit two, we will explore advanced programming techniques and web application deployment. At the end of the course, you’ll present a final project.

PROJECT

For your project, you’ll show off your ability to develop a modularized data processing pipeline, using tools like non-relational and relational databases, cloud computing, big data handling tools, and web application deployment.

What's Covered

  • How to write well-structured and reusable code by leveraging key concepts
  • Ways to leverage cloud resources to create remote servers for computing, storage, and application deployment
  • How to build and deploy python web applications that mirror production environments
  • Relational and non-relational/NoSQL databases, including their data representations and appropriate use cases
  • Advanced queries in SQL and using NoSQL syntax to extract information from databases
  • Big data handling technology and how to process massive scale datasets in a parallelized manner

Prerequisites

We recommend that students have a basic understanding of the following topics:

  • Basic visualization libraries and how to use these tools to explore and visualize tabular datasets
  • General Python and pandas
  • Relational databases and SQL syntax, as well as how to write simple queries from relational databases
  • Regression models, foundational terminology and approaches in machine learning like unsupervised learning and classification
  • How to web scrape or obtain data through application programming interfaces is a bonus

ENROLL

The Online Learning Experience Brought to Life

Live Online | Online Flex

Experience what a lecture is like and how you’ll participate during class.

Watch lectures whenever it’s convenient for you.

Follow along during lecture as your teacher presents.

Assignment deadlines and topic modules keep you accountable and organized.

Interact with your teachers and peers through video, chat, and with the interactive polls.

Test your knowledge directly in the platform—so you can deepen your learning immediately.

Our whiteboarding makes it feel like you’re actually in the classroom.

The online learning platform lets you connect with other students and your instructor.

Partner with classmates during project work, pair-programming, and more.

Join social events, live presentations, and more.

Use the dedicated Slack channel to chat with your instructors and classmates.

WHICH SHORT IMMERSIVE FORMAT WORKS FOR YOU?

Whether you choose Live Online or Online Flex, you’ll be on the fast track to upskilling in Data Engineering.

LIVE ONLINE FORMAT

Immerse yourself full-time with two weeks of live online lectures. You’ll get to focus completely on your studies, with plenty of instructor interaction.

ONLINE FLEX FORMAT

Fit studying into your daily life with on-demand lectures. Plus, you’ll get an organized study plan, 1:1 instructor support, and assignment deadlines to keep you on track.

Length

Tuition

Weekly Time Commitment

Schedule

Lectures

Instructors

Office Hours

Project Presentations

Social Activities

Payment Options

PAY UP FRONT

Live Online: $3,500

Online Flex: $2,500

FINANCING OPTIONS

Coming soon! Finance your tuition through our lending partner: Ascent.

EMPLOYER SPONSORSHIP

Find out if your employer will cover the cost of tuition to support your development.

TALK WITH US

A Few of Our Elite Instructors

The Data Engineering for Data Science Course is led by industry-seasoned data scientists who meet our high bar of online teaching excellence.

  • Rita Biagioli

    Data Scientist

Meet the Full Team

Upcoming Program Dates

Online Flex

Jan 31 - Feb 25

Flexible Schedule

Part-Time | Enroll

Online Flex

Feb 28 - Mar 25

Flexible Schedule

Part-Time | Enroll

Live Online

Mar 28 - Apr 8

11am - 6pm ET

Full-Time | Enroll

Questions?
Schedule a Call

Frequently Asked Questions

  • Am I qualified to enroll in the Introduction to Data Engineering short immersive course? Are there any prerequisites?

    Introduction to Data Engineering is an advanced course, which anyone can enroll in; However, we strongly recommend students only enroll if the following statements apply:

    • - Proficiency in command line and general Python programming with an ability to  effectively use standard Python syntax and data structures to implement algorithms.
    • - Understanding of the fundamentals of relational databases and proficiency in basic SQL syntax; the ability to write simple queries to extract information from relational databases.
    • - Working familiarity with regression models and an understanding of foundational terminology/approaches in machine learning such as classification and unsupervised learning.
    • - Students who have comfort with web scraping or obtaining data through application programming interfaces (APIs) will be able to pursue a larger range of project possibilities, though these skills aren’t necessary to succeed in the course. 
    • - Students need a Github account, which they can sign up for easily (and for free) before class begins.

  • What is the enrollment process like? Is there an application for this course?

    There is no application. To enroll in the Introduction to Data Engineering course, click here. Just be sure to do so by the deadline, which is 8pm ET on the Friday before the course start date. This deadline ensures that we can send students the information they’ll need to login and start class on day one.

  • Are there payment options for this course? How much is tuition?

    Tuition for the Introduction to Data Engineering course is $3,500 for the Live Online format and $2,500 for the Online Flex format. Students can pay for the course in full or consider one of our financing options. We partner with Ascent to offer monthly repayment options for our students. Learn more by visiting Ascent.

  • What kind of time commitment does the Introduction to Data Engineering course require?

    Students who select the Live Online format are expected to be online from 11:00 am - 6:00 pm ET / 10:00 am - 5:00 pm CT / 8:00 am - 3:00 pm PT Monday through Friday for two weeks. This short immersive course schedule includes daily pair programming, lectures, independent project work, and a one-hour lunch break. In order to receive a certificate of completion, students must maintain attendance and achieve passing scores on both the project and assessments.

    Students should also expect to spend time outside of these required class hours to review lectures, complete assignments, and work on their projects.

    Students who pick the Online Flex course format are expected to complete 15-to-20 hours a week for four weeks. They will watch on-demand lectures and engage with instructors and teaching assistants live online during 1:1 sessions weekly.

  • Do I have access to Metis career support if I enroll in this course?

    No, we do not offer career support for our short immersive courses like we do for those in our bootcamps. However, Introduction to Data Engineering students will have access to our expansive and always-growing network of data professionals and will be made aware of networking events and job opportunities as they’re posted in Slack.

  • Who teaches this Metis short immersive course?

    Our short immersive courses, including Introduction to Data Engineering, are taught by the same Data Science Instructors who teach our bootcamps. These highly-reviewed, qualified instructors bring a wealth of expertise with advanced work and educational backgrounds spanning finance, business, education, mathematics, neuroscience, engineering, and more.

ADDITIONAL FAQ

Questions?

Read our FAQs

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