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About this course

Expand your Python for data engineering knowledge with this intermediate course. You’ll cover critical Python theory and key concepts surrounding basic analysis, cleansing, and manipulation of data.

Dig right into real-world data from the Museum of Modern Art. You’ll learn how to prepare text data, introduce uniformity into a messy dataset, and more. You’ll also look behind the scenes and discover object-oriented programming (OOP) and how it powers Python. And finally, you’ll learn new and exciting Python coding concepts for data engineering.

This course focuses on:

  • Building proficiency in basic data analysis, cleansing, manipulation, and exploration’
  • Introducing new concepts like object-oriented programming, classes, and instances
  • Developing skill in the cumbersome task of working with dates and times in Python

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How our Python for Data Engineering Intermediate Course Works

In this Intermediate course, we’ll reinforce your existing knowledge and prepare you to move on to more advanced data engineering courses. Be sure that you take the time to master our Python fundamentals courses before you take this one on. This course requires prerequisite knowledge of fundamental Python concepts like object-oriented programming and proficiency in basic data engineering skills. You’ll need to know how to work with lists, loops, and conditional statements, how to implement basic techniques for data cleansing and analysis, and how to deal with dates and times in Python.

Here at Dataquest, we implement the best possible teaching methods. That’s why we don’t teach with training videos, fill-in-the-blank problems, or mind-numbing memorization. Instead, every lesson, practice problem, and project you complete will be hands-on and interactive. You’ll learn by using real code from day one.

You can embrace this course as a stand-alone growth opportunity, or if you want a more thorough learning experience, check out our complete data engineering career path. It contains this course along with over a dozen others that are designed to take you from complete beginner to entry-level data engineer in a way that’s effective and easy to follow.

Throughout all of our courses, you’ll complete practice projects specifically designed to hone your data engineering skills and help you get hired faster. From the very basics of Python programming to managing databases with SQL, to building data pipelines, we ensure that you acquire and retain the essential knowledge and skills required to become a data engineer.

Additionally, with Dataquest, once you sign up you’ll become part of a vibrant and supportive community of students and professionals who are eager to help one another on the learning path. And if you ever need a hand from our powerful support tools, we’re only a click away.

Here’s a glance at part one of our Python for Data Engineering Intermediate course:

  • This is the third course in the Data Engineering Career Path. It consists of the four lessons listed below, which cover intermediate data engineering techniques in Python.
  • You’ll write real code with dozens of practice problems to validate and apply your skills.
  • When you complete this course, you’ll receive a certificate that you can share with your professional network.
  • Once you complete this course, you’ll be ready for more advanced Python courses.
  • Engage with our friendly community of data professionals, get feedback on your projects, and keep building your skills.
  • At the end of each course, you’ll complete a guided project to reinforce your new knowledge and expand your portfolio.

Who is the Python for Data Engineering Intermediate Course for?

This course has a very broad application. Whether you’re new to data science and just beginning a career path as a data engineer or an experienced Python user looking for a refresher course, this Data Engineering Intermediate course was made with you in mind.

Many people could benefit from this course:

  • Data science beginners looking for fundamental data engineering knowledge
  • People who want a career as a data engineer or data scientist
  • People seeking to switch from an in-person data engineering job to remote work
  • Anyone who works with data in telecommunication, finance, education, and healthcare
  • Anyone who wants to be able to capture, process, and interpret data
  • Students who wish to develop a competitive portfolio
  • Python users who want to fill in the blanks and brush up on the basics

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