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It can be overwhelming if you’re looking into becoming a data engineer as the tools and skills you need to learn can look quite intimidating. If you search for data engineering jobs, the job descriptions ask for a lot, making people look the other way.
However, you should not feel all the requirements as long as you have the fundamentals under your belt. Learning the basis of data engineering can help you navigate your career as a data engineer.
In this blog, I will go through 5 free online courses that will help you learn the fundamentals of data engineering.
Data Engineering for Everyone
Link: Data Engineering for Everyone
As it states in the title, if you’re starting out or if you’re already halfway there – this course offered by DataCamp is for everyone interested in data engineering. This course is a no-code introduction to data engineering, where you will learn everything about data engineers.
You will learn how data engineers lay the groundwork and how it allows data scientists to complete their tasks. Understanding the difference between a data engineer and a data scientist is important. 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 you need to feel like you’re in a classroom setting. This 3-hour data engineering course for beginners is offered by freeCodeCamp.
You will learn the essentials of data engineering in this course for beginners. You’ll learn about Databases, Docker, and analytical engineering, explore advanced topics like data pipeline building with Airflow, and engage in batch processing with Spark and streaming data with Kafka. The course culminates in a comprehensive project, putting your skills to the test in creating a full end-to-end pipeline.
ASUx: Data Engineering
Link: ASUx: Data Engineering
In 5 weeks, at 1-9 hours a week, you will get introductory insights into data engineering offered by Arizona State University. In this course, you will have interactive videos to help you understand both the analytical concepts and the software.
It focuses on working with databases in data engineering and how to interact with them using SQL. From learning about database structure and how to join data from multiple tables, you will be able to build a solid foundational knowledge of data engineering where you can later be able to create reports with 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 data engineering career. A very popular programming language and library, respectively – having these skills down-packed will elevate your data engineering journey.
In just under 4 weeks, you will learn how to set up development environments, manipulate data, and efficiently solve real-world problems. You will also learn core Python syntax and data structures, pandas DataFrames for data manipulation and alternatives to Pandas for big data.
IBM Data Engineering Professional Certificate
Link: IBM Data Engineering Professional Certificate
Let’s say you’re the type of person to commit 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 commit 10 hours a week.
In this course, you will learn the most up-to-date practical skills and knowledge data engineers use in their daily roles. You will then dive into creating, designing and managing relational databases & applying database administration (DBA) concepts to RDBMSs such as MySQL, PostgreSQL, & IBM Db2. Over time you will develop a working knowledge of NoSQL & Big Data using MongoDB, Cassandra, Cloudant, Hadoop, Apache Spark, Spark SQL, Spark ML, and Spark Streaming.
By the end of the course, you will be able to implement ETL & Data Pipelines with Bash, Airflow & Kafka; architect, populate, and deploy Data Warehouses; and create BI reports & interactive dashboards.
Wrapping Up
In this blog, I aimed to walk you through learning the fundamentals of data engineering from bite-sized courses to the complete certification. Everybody learns at different levels and we all learn in different ways too. Choosing a course that is right for you is important in learning the fundamentals of data engineering.
Nisha Arya is a data scientist, freelance technical writer, and an editor and community manager for KDnuggets. She is particularly interested in providing data science career advice or tutorials and theory-based knowledge around data science. Nisha covers a wide range of topics and wishes to explore the different ways artificial intelligence can benefit the longevity of human life. A keen learner, Nisha seeks to broaden her tech knowledge and writing skills, while helping guide others.
