The editors at Solutions Review have compiled this list of the best data engineering courses and online training to consider.
Data engineering is the process of designing and building pipelines that transport and transform data into a usable state for data workers to utilize. Data pipelines commonly take data from many disparate sources and collect them into data warehouses that represent the data as a single source. To do so, data engineers must manipulate and analyze data from each system as a pre-processing step.
With this in mind, we’ve compiled this list of the best data engineering courses and online training to consider if you’re looking to grow your data management or analytics skills for work or play. This is not an exhaustive list, but one that features the best data engineering courses and online training from trusted online platforms. We made sure to mention and link to related courses on each platform that may be worth exploring as well.
The Best Data Engineering Courses
OUR TAKE: This 100-percent online, beginner-level training takes roughly 10 hours to complete and features flexible deadlines based on your schedule.
Description: 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.
More “Top-Rated” Coursera paths: Python Project for Data EngineeringGO TO TRAINING
OUR TAKE: DataCamp’s data engineering training takes 2 hours to complete and consists of 11 videos and 32 unique exercises. By the end of the module, you will uncover how data engineers lay the groundwork for data science.
Description: In this course, you’ll learn about a data engineer’s core responsibilities, how they differ from data scientists and facilitate the flow of data through an organization. Through hands-on exercises you’ll follow Spotflix, a fictional music streaming company, to understand how their data engineers collect, clean, and catalog their data.GO TO TRAINING
OUR TAKE: In partnership with IBM, this data engineering certificate training takes 4 weeks to complete by spending 9-10 hours-per-week. By the end of the module, students obtain a solid understanding of the data engineering field.
Description: Learn about data engineering concepts, ecosystem, and lifecycle. Also learn about the systems, processes, and tools you need as a Data Engineer in order to gather, transform, load, process, query, and manage data so that it can be leveraged by data consumers for operations, and decision-making.
More “Top-Rated” edX paths: Python for Data Engineering ProjectGO TO TRAINING
TITLE: Data Engineering Foundations
OUR TAKE: LinkedIn Learning’s intermediate-level data engineering course is taught by renowned data science instructor Harshit Tyagi. More than 7,000 LinkedIn members have used the module, making it a popular one to consider.
Platform: LinkedIn Learning
Description: In this course, Harshit Tyagi explains the fundamentals of data engineering. He covers key topics like data wrangling, database schema, and developing ETL pipelines. He also details several data engineering tools like Hive, Hadoop, Spark, and Airflow. By the end of this course, it should be abundantly clear why the data engineer is one of the most valuable people in a data-driven organization.
More “Top-Rated” LinkedIn Learning paths: Data Science Foundations: Data EngineeringGO TO TRAINING
OUR TAKE: This intermediate-level content exploration comes from the Big Data LDN 2019 event and is narrated by Suki Dhupar.
Description: Data Operations (DataOps) is a methodology consisting of people, processes, tools, and services for enterprises to rapidly, repeatedly, and reliably deliver production-ready data from the vast array of enterprise data sources. Learn how to and why implementing these key ingredients can help a business achieve the analytic velocity necessary to create a competitive advantage.
More “Top-Rated” Pluralsight paths: Data Engineering with AWS Machine LearningGO TO TRAINING
TITLE: Big Data Engineer
OUR TAKE: With more than 14,000 ratings in partnership with IBM, Simplilearn’s Big Data Engineer training touts a capstone project and more than 15 real-life projects.
Description: Enter the role as a big data engineer with this certification course. It features masterclasses and Ask me Anything sessions by IBM. Learn job critical skills like big data and Hadoop frameworks, leverage the functionality of AWS services, and learn to use the database management tool and MongoDB to store data via interactive live sessions, practical labs, & industry projects.GO TO TRAINING
OUR TAKE: Udacity’s popular data engineering nanodegree program requires intermediate Python and SQL experience and takes 5 months to complete (if you spend between 5 and 10 hours per week on it).
Description: Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets. At the end of the program, you’ll combine your new skills by completing a capstone project. To be successful in this program, you should have intermediate Python and SQL skills.GO TO TRAINING
OUR TAKE: Udemy’s data engineering training features more than 12 hours of on-demand video, 11 downloadable resources, and full lifetime access.
Description: In this beginner course, you will learn how to get started with this powerful toolset. Learners will cover topics like connecting to and transforming web-based data sources. You will also learn how to publish and share your reports and visuals on the Power BI service.
More “Top-Rated” Udemy paths: Data Engineering, Serverless ETL & BI on Amazon Cloud, Data Engineering on Google Cloud PlatformGO TO TRAINING
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