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January 29, 2025
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Launch Your Career in Data Engineering. Master foundational strategies and tools to become proficient in developing data engineering and machine learning solutions
Instructors: Kennedy Behrman
18,925 already enrolled
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(338 reviews)
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Beginner level
Students should have beginner level Linux skills. No experience in Python is required.
(338 reviews)
Recommended experience
Beginner level
Students should have beginner level Linux skills. No experience in Python is required.
Develop data engineering solutions with a minimal and essential subset of the Python language and the Linux environment
Design scripts to connect and query a SQL database using Python
Use a scraping library in Python to read, identify and extract data from websites
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If you are interested in developing the skills needed to be a data engineer, the Python, Bash and SQL Essentials for Data Engineering Specialization is a great place to start. We live in a world that is driven by big data - from what we search online to the route we take to our favorite restaurant, and everything in between. Businesses and organizations use this data to make decisions that impact the ways in which we navigate our lives. How do engineers collect this data? How can this data be organized so that it can be appropriately analyzed? A data engineer is specialized in this initial step of accessing, cleaning and managing big data.
Data engineers today need a solid foundation in a few essential areas: Python, Bash and SQL. In Python, Bash and SQL Essentials for Data Engineering, we provide a nuts and bolts overview of these fundamental skills needed for entering the world of data engineering. Led by three professional data engineers, this Specialization will provide quick and accessible ways to learn data engineering strategies, give you a chance to practice what you’ve learned in integrated lab exercises, and then immediately apply these techniques in your professional or academic life.
Applied Learning Project
Each course includes integrated lab exercises using Visual Studio Code or Jupyter notebooks that give you an opportunity to practice the Python, Bash and SQL skills with real-world applications covered in each course. For each data engineering solution that you explore, you are also encouraged to create a demo video and GitHub repository of code that can be showcased in your digital portfolio for employers. By the end of this Specialization, you will have the foundational skills necessary to begin tackling more complex data engineering solutions.
Setup a provisioned Python project environment
Use Pandas libraries to read and write data into data structures and files
Employ Vim and Visual Studio Code to write Python code
Use Linux tools build data engineering solutions.
Develop Bash syntax to configure and control Linux.
Extract data from different sources and map it to Python data structures.
Design Scripts to connect and query a SQL database from within Python.
Apply scraping techniques to read and extract data from a website.
Construct Python Microservices with FastAPI
Build a Command-Line Tool in Python using Click
Compare multiple ways to set up and use a Jupyter notebook
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This course series has been designed to be completed in 4-6 months.
Students should have beginner level Linux skills. No experience in Python is required.
Yes, the courses have been sequenced in the order in which you should take them.
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.
By the end of this Specialization, you will have the foundational knowledge necessary to begin designing data engineering solutions.
No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
Financial aid available,
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