- Information Engineering
- Python Programming
- Extraction, Transformation And Loading (ETL)
- Relational Database Management System (RDBMS)
- SQL
- Data Science
- Database (DBMS)
- NoSQL
- Data Analysis
- Pandas
- Numpy
- Web Scraping
Data Engineering Foundations Specialization
Build the Foundation for a Data Engineering Career. Develop hands-on experience with Python, SQL, and Relational Databases and master the fundamentals of the Data Engineering ecosystem.
Offered By

What you will learn
Working knowledge of Data Engineering Ecosystem and Lifecycle. Viewpoints and tips from Data professionals on starting a career in this domain.
Python programming basics including data structures, logic, working with files, invoking APIs, using libraries such as Pandas and Numpy, doing ETL.
Relational Database fundamentals including Database Design, Creating Schemas, Tables, Constraints, and working with MySQL, PostgreSQL & IBM Db2.
SQL query language, SELECT, INSERT, UPDATE, DELETE statements, database functions, stored procs, working with multiple tables, JOINs, & transactions.
Skills you will gain
About this Specialization
Applied Learning Project
All courses in the Specialization contain multiple hands-on labs and assignments to help you gain practical experience and skills.
The projects range from working with data in multiple formats to transforming and loading that data into a single source to analyzing socio-economic data with SQL and working with advanced SQL techniques.
You will work hands-on with multiple real-world databases and tools including MySQL, PostgresSQL, IBM Db2, PhpMyAdmin, pgAdmin, IBM Cloud, Python, Jupyter notebooks, Watson Studio, etc.
Basic Computer & IT Literacy, and working experience on one or more Operating Systems. No prior knowledge or experience of Data Engineering needed.
Basic Computer & IT Literacy, and working experience on one or more Operating Systems. No prior knowledge or experience of Data Engineering needed.
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 5 Courses in this Specialization
Introduction to Data Engineering
This course introduces you to the core concepts, processes, and tools you need to know in order to get a foundational knowledge of data engineering. You will gain an understanding of the modern data ecosystem and the role Data Engineers, Data Scientists, and Data Analysts play in this ecosystem.
Python for Data Science, AI & Development
Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. Python is one of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries.
Python Project for Data Engineering
This mini-course is intended to apply foundational Python skills by implementing different techniques to collect and work with data. Assume the role of a Data Engineer and extract data from multiple file formats, transform it into specific datatypes, and then load it into a single source for analysis. Continue with the course and test your knowledge by implementing webscraping and extracting data with APIs all with the help of multiple hands-on labs. After completing this course you will have acquired the confidence to begin collecting large datasets from multiple sources and transform them into one primary source, or begin web scraping to gain valuable business insights all with the use of Python.
Introduction to Relational Databases (RDBMS)
Are you ready to dive into the world of data engineering? You’ll need a solid understanding of how data is stored, processed, and accessed. You’ll need to identify the different types of database that are appropriate for the kind of data you are working with and what processing the data requires.
Offered by

IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
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