Launch Your Career in Data Engineering. Master foundational strategies and tools to become proficient in developing data engineering and machine learning solutions

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Python, Bash and SQL Essentials for Data Engineering SpecializationDuke University

What you will learn

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
Setup a provisioned Python project environment

Skills you will gain

About this Specialization

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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.

Shareable Certificate

Earn a Certificate upon completion

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Beginner Level

Approximately 4 months to complete

Suggested pace of 6 hours/week

English

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Shareable Certificate

Earn a Certificate upon completion

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Beginner Level

Approximately 4 months to complete

Suggested pace of 6 hours/week

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

See how employees at top companies are mastering in-demand skills

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How the Specialization Works

Take Courses

A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.

Hands-on Project

Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.

Earn a Certificate

When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

There are 4 Courses in this Specialization

Course1

Course 1

Python and Pandas for Data Engineering

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105 ratings

In this first course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will learn how to set up a version-controlled Python working environment which can utilize third party libraries. You will learn to use Python and the powerful Pandas library for data analysis and manipulation. Additionally, you will also be introduced to Vim and Visual Studio Code, two popular tools for writing software. This course is valuable for beginning and intermediate students in order to begin transforming and manipulating data as a data engineer.

Course2

Course 2

Linux and Bash for Data Engineering

4.6

stars

50 ratings

In this second course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will learn the fundamentals of Linux necessary to perform data engineering tasks. Additionally, you will explore how to use both Bash and zsh configurations, and develop the syntax needed to interact and control Linux. These skills will allow you to manage and manipulate databases in a Bash environment.

Course3

Course 3

Scripting with Python and SQL for Data Engineering

4.6

stars

49 ratings

In this third course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will explore techniques to work effectively with Python and SQL. We will go through useful data structures in Python scripting and connect to databases like MySQL. Additionally, you will learn how to use a modern text editor to connect and run SQL queries against a real database, performing operations to load and extract data. Finally, you will use extracted data from websites using scraping techniques. These skills will allow you to work effectively when data is not readily available, or when spatial queries are required to extract useful information from databases.

Course4

Course 4

Web Applications and Command-Line Tools for Data Engineering

4.2

stars

15 ratings

In this fourth course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will build upon the data engineering concepts introduced in the first three courses to apply Python, Bash and SQL techniques in tackling real-world problems. First, we will dive deeper into leveraging Jupyter notebooks to create and deploy models for machine learning tasks. Then, we will explore how to use Python microservices to break up your data warehouse into small, portable solutions that can scale. Finally, you will build a powerful command-line tool to automate testing and quality control for publishing and sharing your tool with a data registry.

Instructors

Offered by

Duke University

Frequently Asked Questions

What is the refund policy?
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.
Can I just enroll in a single course?
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.
Is financial aid available?
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.
Can I take the course for free?
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.
Is this course really 100% online? Do I need to attend any classes in person?
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.
How long does it take to complete the Specialization?
This course series has been designed to be completed in 4-6 months.
What background knowledge is necessary?
Students should have beginner level Linux skills. No experience in Python is required.
Do I need to take the courses in a specific order?
Yes, the courses have been sequenced in the order in which you should take them.
Will I earn university credit for completing the Specialization?
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.
What will I be able to do upon completing the Specialization?
By the end of this Specialization, you will have the foundational knowledge necessary to begin designing data engineering solutions.
Will I receive a transcript from Duke University for completing this course?
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.

More questions? Visit the Learner Help Center.

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Python, Bash and SQL Essentials for Data Engineering Specialization

What you will learn

Skills you will gain

About this Specialization

Applied Learning Project