What You’ll Learn
In this intermediate course, you’ll dive into real data problems and develop your skills in analyzing, preparing, exploring, and manipulating data. We’ll teach you fundamental operations using strings and loops and also give you a glimpse into the inner workings of Python by introducing object-oriented programming and its affiliated concepts. You’ll even learn to create your own custom class in Python.In addition, you’ll learn the basics of working with dates and time in Python, a task that routinely presents difficulties and headaches for all types of data professionals. You’ll use powerful tools like strftime and datetime to make quick work of these obstacles.
Finally, you’ll combine all of your data knowledge and skill to complete a data project from start to finish that is focused on finding out what it takes to get to the top of the Hacker News feed.
Enroll in this skill path if you want to learn how to do the following:
- Implement basic data analysis techniques
- Discover object-oriented programming’s importance in data engineering
- Learn key concepts including classes, instances, attributes, and methods
- Create your own custom class
- Implement date and time analysis techniques
- Format dates using strftime
- Use loops to explore CSV data
- Use string methods to clean and analyze data
- Build a data engineering portfolio project from scratch
- Parse dates from strings using the datetime library
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.
Enroll in this course to learn Python for Data Engineering Intermediate!
Python for Data Engineering Intermediate Lessons List
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
Students who Enrolled in This Course Also Enrolled in:
If you’d like to learn with Dataquest to prepare for a career as a data engineer, data scientist, or Python developer, we recommend you check out the following paths and courses to put your best foot forward:
Or, if you’re already in a data science role and simply want to reinforce your existing skills and expand your knowledge base, we suggest you look into our other skill development courses:
Qualify for In-demand Jobs in Data Engineering With Python
Python remains one of the most popular programming languages in the world, and possessing proficiency in Python makes you a hot commodity for many positions across a variety of industries. With the skills you’ll acquire by completing this course, you’ll be one step closer to landing any of the following in-demand jobs:
- Python developer
- Data engineer
- Data analyst
- Data scientist
- Business intelligence engineer
- Quality assurance engineer
- Computer vision engineer
- Software developer
- Python full stack developer
- Big Data engineer
- Machine learning engineer
- Statistician
- Software engineer
- Data architect
