Owing to the ever-growing demand for data professionals who can effectively manage and manipulate data, it’s no wonder that data engineering skills are highly sought-after by employers in a variety of industries today.
Data engineering is a field that focuses on the design, construction, operation, and maintenance of systems that collect, store, and process data.
- 1. A Complete Course on Data Engineering
- 2. Data Engineer with Python
- 3. Postgres for Data Engineers
- 4. Microsoft Azure for Data Engineering
- 5. Introduction to Designing Data Lakes on AWS
- 6. Foundations: Data, Data, Everywhere
- 7. Google Cloud Big Data and Machine Learning Fundamentals
- 8. Big Data and Hadoop Essentials
- 9. Data Engineering Course
- 10. Data Engineering ETL, Web Scraping, Big Data, SQL, Power BI
Let’s unlock the world of data with courses available online!
1. A Complete Course on Data Engineering
Duration: 2-3 Weeks
The following course covers all the integral aspects of data engineering, from fundamentals to advanced. Overall, it helps develop a strong command of the skill. Moreover, it presents detailed theoretical and hands-on explanations of all the major data engineering concepts.
To enrol, click here.
2. Data Engineer with Python
Duration: 73 Hours
In addition to working with Python, you’ll learn how to build the data architecture, streamline data processing, and maintain massive data systems in the following course. Moreover, you’ll expand your language skills with Shell, SQL, and Scala.
By the end of the course, you’ll master the critical database, scripting, and process skills you need as a data engineer.
To enrol, click here.
3. Postgres for Data Engineers
Duration: 9 hours
This course teaches you how to share data more effectively with the PostgreSQL database management system. Furthermore, you’ll practice implementing a database using best security practices.
To enrol, click here.
4. Microsoft Azure for Data Engineering
Duration: 6 hours (approx.)
This course is part of a 10-course-specialisation for developers who want to showcase their design skills along with their expertise in implementing data solutions using Microsoft Azure services.
The following course is a must for candidates preparing for the Exam DP-203: Data Engineering on Microsoft Azure.
To enrol, click here.
5. Introduction to Designing Data Lakes on AWS
Duration: 10 Hours (approx.)
This introductory course teaches you ways to create and operate a data lake securely. It further provides an in-depth look at the data-lake value proposition, characteristics and components.
To enrol, click here.
6. Foundations: Data, Data, Everywhere
Duration: 22 hours (approx.)
The course works as an introduction to the data analytics realm through a hands-on curriculum developed by Google. The material includes various data analytics topics and gives an overview of what’s to come in the Google Data Analytics Certificate.
To enrol, click here.
7. Google Cloud Big Data and Machine Learning Fundamentals
Duration: 10 Hours (approx.)
A thorough introduction to Google Cloud big data and other products that support the data-to-AI lifecycle. The course explores the process, obstacles and benefits of building a big data pipeline and models with Vertex AI on Google Cloud.
To enrol, click here.
8. Big Data and Hadoop Essentials
Duration: 43 minutes
This course builds an understanding of big data problems and Hadoop as a solution. It takes you through the history of Hadoop and everything about Hadoop Magic. Moreover, it explains the difference between data science and data engineering—which happens to be one of the biggest confusions in selecting a career or understanding what a role may entail.
To enrol, click here.
9. Data Engineering Course
Duration: 7 months
With MITx MicroMasters, the course is designed by top domain experts to help you master core data engineering skills like Python, SQL, AWS, Spark, Kafka, and more. In addition, the course stands out for the real-time projects and top-notch faculty from MIT.
To enrol, click here.
10. Data Engineering ETL, Web Scraping, Big Data, SQL, Power BI
Duration: 12.5 hours
Organisations’ basic problem is gathering data from various sources in multiple formats and moving it to one or more data stores. The course covers topics like connecting to and transforming web-based data sources. In the track, you will learn to publish and share reports and visuals on the Power BI service.
To enrol, click here.
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