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It can be overwhelming if you're thinking about becoming a data engineer, as the tools and skills you need to learn can seem quite intimidating. If you're looking for data engineering jobs, job descriptions ask for a lot, which makes people look away.
However, you shouldn't feel obligated to meet all the requirements as long as you have the basic knowledge. Learning the basics of data engineering can help you navigate your career as a data engineer.
In this blog, I will go over five free online courses that will help you learn the fundamentals of data engineering.
Data engineering for everyone
Link: Data engineering for everyone
As the title says, whether you are just starting out or you are already halfway there, this course offered by DataCamp is for all those interested in data engineering. This course is an introduction to no-code data engineering, where you will learn everything about data engineers.
You will learn how data engineers lay the foundation and how this enables data scientists to complete their tasks. It is important to understand the difference between a data engineer and a data scientist. From data storage to data processing techniques, this will help you learn how to develop data pipelines and how to use parallel and cloud computing in your data engineering projects.
Data engineering course for beginners
Link: Data engineering course for beginners
Maybe you're not one to follow a written course outline and need to feel like you're in a classroom. This 3-hour data engineering course for beginners is offered by freeCodeCamp.
In this beginner-friendly course, you'll learn the basics of data engineering. You'll learn about databases, Docker, and analytics engineering, explore advanced topics like building data pipelines with Airflow, and get involved in batch processing with Spark and streaming data with Kafka. The course culminates with a comprehensive project that tests your skills in building a complete data pipeline from start to finish.
ASUx: Data Engineering
Link: ASUx: Data Engineering
In 5 weeks, from 1 to 9 hours per week, you will receive introductory knowledge on data engineering offered by Arizona State University. In this course, you will have interactive videos that will help you understand both analytical concepts and software.
It focuses on working with databases in data engineering and how to interact with them using SQL. By learning about the structure of databases and how to join data from multiple tables, you will develop a solid foundational knowledge of data engineering that will enable you to later create reports using SQL and write scripts for data processing.
Python and Pandas for Data Engineering
Link: Python and Pandas for Data Engineering
Mastering Python and Pandas is essential for your career in data engineering. They are a very popular programming language and library, respectively. If you master these skills, your career in data engineering will be much better.
In less than 4 weeks, you will learn how to set up development environments, manipulate data, and solve real-world problems efficiently. You will also learn basic Python syntax and data structures, Pandas data frames for data manipulation, and Pandas alternatives for big data.
IBM Professional Certificate in Data Engineering
Link: IBM Professional Certificate in Data Engineering
Let’s say you’re the type of person who commits to a course from start to finish, from beginner to expert. This course may be for you. Offered by IBM, this data engineering course is a professional certificate consisting of 16 series and can be completed in 6 months if you dedicate 10 hours a week.
In this course, you’ll learn the practical skills and most up-to-date knowledge that data engineers use in their daily roles. You’ll then dive into building, designing, and managing relational databases and applying database administration (DBA) concepts to relational database management systems (RDBMS) such as MySQL, PostgreSQL, and IBM Db2. Over time, you’ll develop a working knowledge of NoSQL and Big Data using MongoDB, Cassandra, Cloudant, Hadoop, Apache Spark, Spark SQL, Spark ML, and Spark Streaming.
By the end of this course, you will be able to implement ETL and Data Pipelines with Bash, Airflow, and Kafka; design, populate, and deploy data warehouses; and create BI reports and interactive dashboards.
Ending
In this blog, my goal is to guide you through learning the fundamentals of data engineering, from short courses to full certification. We all learn at different levels and in different ways too. Choosing a course that is right for you is important to learn the fundamentals of data engineering.
Nisha Arya Nisha is a data scientist, freelance technical writer, and KDnuggets community editor and manager. She is especially interested in providing career advice on data science or tutorials and theoretical knowledge on data science. Nisha covers a wide range of topics and wishes to explore the different ways in which artificial intelligence can benefit the longevity of human life. Nisha is an enthusiastic learner and is looking to expand her technological knowledge and writing skills while helping to mentor others.
