· 10 Min read

13 Free & Stunning Resources to Master Data Engineering

Data engineers are the architects of a data-driven world, building the foundation for effective data analysis and management to empower machine-learning, frontend, and backend engineers with valuable insights and tech.

If you're interested in becoming a data engineer, you can start your journey today with these 13 free and stunning resources. These resources cover all the basics of data engineering, including data ecosystems, big data processing tools, database design methodologies, and more.


1. Introduction to Data Engineering

This course will introduce you to the modern data ecosystem, big data processing tools, the data engineering lifecycle, and career opportunities. You'll also get hands-on experience performing basic querying operations.

Coursera: Introduction to Data Engineering

2. Python

This interactive course will teach you basic arithmetic, Python syntax, data manipulation, and programming skills. You'll gain experience with feedback directly in the browser.

DataQuest: Introduction to Python

3. Computer Science Basics

This course will give you a broad understanding of computer science, including algorithms and data structures. You'll learn algorithmic thinking, algorithms and data structures, encapsulation, resource management, and security.

Harvard: Introduction to Computer Science

4. SQL

In this set of five self-paced courses, you'll learn about relational databases, SQL, database design methodologies, and more. Databases are essential in today's tech world, making these courses beneficial for anyone seeking a strong understanding.

Standford: Relational Databases and SQL

5. Git and GitHub

This course will teach you how to track different versions of code and config files and collaborate using remote repositories. It's perfect for data engineers who want to boost productivity and learn essential version control skills.

Coursera: Introduction to Git and GitHub

6. Linux Basics and Bash Shell Scripting

This course will teach you how to navigate through Linux systems and manage directories and files. You'll also learn how to automate tasks using Metacharacters and I/O Redirection.

Coursera: Hands-on Introduction to Linux Commands and Shell Scripting

7. NoSQL

This course will teach you NoSQL database technical knowledge, including the architecture and features of MongoDB and Cassandra. You'll also gain hands-on experience managing data, permissions, indexing, and sharding.

Coursera: Introduction to NoSQL Databases

8. Big Data with Spark and Hadoop

This course covers Big Data's characteristics and applications, Hadoop and Hive features and limitations, Spark for data insights, and learning about Resilient Distributed Datasets for parallel processing.

Coursera: Introduction to Big Data with Spark and Hadoop

9. AWS Cloud

This course covers the basics of AWS cloud architecture, including key AWS services, designing solutions, and data lakes. It includes 15 hands-on labs for applied learning and focuses on expertise in AWS technology and optimizing solutions.

Coursera: AWS Cloud Solutions Architect Professional Certificate

10. Data Warehousing

This course teaches essential skills for Data Warehouse Engineers, covering RDBMS, SQL, ETL tools, and BI. Learners gain hands-on experience managing data warehouses and building a job-ready portfolio through applied learning projects.

Coursera: IBM Data Warehouse Engineer Professional Certificate

11. Data Build Tool (DBT)

This course teaches DBT, the transformation tool that supercharges SQL and collaboration. You'll learn how to structure and organize data pipelines, write complex SQL queries, leverage community-packages, and gain a deeper understanding of data modeling.

DBT: Tutorials

12. ETL and Data Pipelines with Shell, Airflow and Kafka

This course covers ETL and ELT approaches to convert raw data into analytics-ready data. You'll gain skills in extracting, merging, and transforming data, verifying quality, and recovery mechanisms.

MaximeHeckel: Building the perfect GitHub CI workflow for your frontend team

13. Data Mesh

This video teaches the challenges of centralized data platform architectures, principles of modern software engineering and internet-scale solutions, and how data mesh can unlock the potential of enterprise data.

Youtube: Data Mesh

In conclusion

becoming a data engineer is a highly valuable and rewarding career path in the tech industry. With the rise of data-driven decision making and machine learning, data engineers play a critical role in building the foundation for effective data analysis and management.

By leveraging the resources above, you can gain the technical skills and hands-on experience needed to build amazing products and change the world.