Over the last decade, many companies have undergone complete digital transformation producing unimaginable volumes of new types of data. While it was previously apparent that data scientists were needed to make sense of it all, it was less apparent that data engineers are the ones ensuring data's quality, security, and availability for the data scientists to do their jobs.
With the onslaught of completed corporate digital transformations, the Internet of Things, and the race to become AI-driven, many international brands need data engineers in abundance to provide the foundation for successful data science initiatives. That being said, data engineering requires a complete understanding of technologies, tools, faster execution of complex datasets with reliability. In this post, we're here to discuss some of the best date engineering courses on the internet. From beginner to advanced, we've got everything in one spot just for you!
In order to help our readers in taking a knowledgeable learning decision, TakeThisCourse.net has introduced a metric to measure the effectiveness of an online course. Learn more about how we measure an online course effectiveness. What is Data Engineering?
Data engineering is the complex task of making raw data used by data scientists and groups within an organization, data engineers gather, prepare, and create raw data analyses to provide predictive models by showing trends for the short- and long term. Simply put, it is a software-based engineering approach for designing and developing information systems. Data Engineers design, manage and optimize the flow of data with those databases throughout the organization.
Best Data Engineering Courses & Classes
If you're looking to become a new data engineer in the town then Takethiscourse will never abandon you in exploring great options for yourself. If you've been living under a rock, data is the new oil. Get ready to focus on advanced analytics of data that is stored in a company's database. Data Engineering converts Data Science more productive. There are some great courses listed below. Let's have a look!
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- IBM via Coursera
- 5 Months (3 hours weekly) of effort required
- 4,559+ already enrolled!
- ★★★★★ (345 Ratings)
Since data engineering is the fastest-growing field these days, this specialization helps you acquire exclusive knowledge regarding data engineering. In this course, you will learn about working knowledge of the data engineering ecosystem and lifecycle. Get to know the viewpoints and tips from data professionals on starting a career in this domain. You will learn basics in python programming including data structures, logic, working with files, invoking APIs, using libraries such as Pandas and Numpy, and even doing ETL. Learn all about relational database fundamentals that involve database design, creating schemas, tables, constraints, and working with MySQL, PostgreSQL & IBM Db2. Here, you'll master SQL query language, select, insert, update, delete statements, and database functions. Following that, you'll understand stored procs to work with multiple tables, joins, & transactions.
Without a doubt, this course was supported by a simple but detailed, easy-to-understand explanation of concepts and laid the groundwork for a proper introduction to Data Engineering. The instructors' real-life examples/scenarios were excellent! The journey is worthwhile; there is no turning back! Thank you to the instructors (Jade, ★★★★★).
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- Google Cloud via Coursera
- 3 Months (5 hour weekly) of effort required
- 37,267+ already enrolled!
- ★★★★★ (11,292 Ratings)
This course will help anyone interested in pursuing a career in data engineering by learning database skills to get started in this field. In this course, you will learn how to identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud. You will learn how to use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud. Once you take the course, you will be able to employ BigQuery to carry out interactive data analysis. Learn how to choose between different data processing products on Google Cloud. This course provides all the skills you need to advance your career.
I strongly recommend this course to data engineers based on my own first-hand experience. In addition to an introduction to data engineering, this course raises awareness of data warehousing and does so in a very user-friendly manner by demonstrating the entire process on the GCP. Of course, programming in SQL should be learned through a dedicated course on the subject, as this course includes all of the necessary code (ARVIND K S, ★★★★★).
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- Kim Schmidt via Pluralsight
- Course Type: Self Paced
- ★★★★☆ (22 Ratings)
This course will thoroughly guide you about AWS machine learning. Data Engineering with AWS Machine Learning teaches you how to select the best AWS service for each of these data-related machine learning ML tasks in any given situation. First, you'll learn about the various data storage solutions available on AWS, as well as what each type of storage is used for. Following that, you'll learn about the various AWS services used to ingest data into ML-specific services, as well as when to use each one. Finally, you'll discover how to convert your raw data into the formats required by the various AWS ML services. When you complete this course, you will have the skills and knowledge necessary to provide data solutions for storing, preparing, and ingesting data needed to architect data engineering solutions on AWS for Machine Learning.
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- Loony Corn via Udemy
- 44,126+ already enrolled!
- ★★★★☆ (6,447 Ratings)
This course will make you a master of using Google Cloud Platform. In this course, you will learn how to deploy and manage Hadoop apps on the Google Cloud. Learn how to build deep learning models on the cloud using TensorFlow. Then you'll be able to make informed decisions about containers, VMs, and AppEngine. This course will enable you to use big data technologies such as BigTable, Dataflow, Apache Beam, and Pub/Sub. This course is for anyone interested in architecting compute networking, loading balancing, and other solutions using the GCP.
I decided to take this course, but some sections of it (for example, networking) are very procedural, with little explanation as to why. This makes passing the test more difficult. Overall, the course is beneficial (Musab Saleh, ★★★☆☆).
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- IBM via Coursera
- 12 Months (3 hours weekly) of effort required
- 4,831+ already enrolled!
- ★★★★★ (317 Ratings)
Take this course and you will acquire the essential skills you need to work. Using a range of tools, databases to design, deploy, and manage structured and unstructured data, here you have every aspect available. In this course, you will learn RDBMS fundamentals including the design & creation of databases, schemes, tables. Further, DB administration, security & working with MySQL, PostgreSQL & IBM Db2, you've got it all. Learn SQL query language, select, insert, update, delete statements, database functions, stored procs, working with multiple tables, joins, & transactions. Understand NoSQL & big data concepts including practice with MongoDB, Cassandra, IBM Cloudant, Apache Hadoop, Apache Spark, SparkSQL, SparkML, Spark Streaming and ETL, Data Pipelines. The list goes on and on so sign up for this course right away.
This may be simple for someone with more experience, but it was difficult for a newcomer like me, and it took me a long time to complete and understand the questions. When you get stuck, there is support, but they only respond with the answer, not an explanation (Christian R, ★★★★☆).
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- Microsoft via Coursera
- 13 Months (2 hours weekly) of effort required
- ★★★★☆ (8 Ratings)
Want to become a Microsoft Azure data-engineering associate? Then enroll in this course right now. This Specialization will assist you in developing expertise in the design and implementation of data solutions using Microsoft Azure data services. Learn how to integrate, transform, and consolidate data from various structured as well as unstructured data systems into suitable chunks for building analytics solutions. In this course, you'll have access to various data platform technologies available, and then you'll know how to take advantage of this technology to increase revenue. Learn the basics of storage management in Azure and create a storage account by choosing the right model for your data. Master using Azure synapse analytics to build data warehouses with modern patterns. Needless to say, gain all those analytical skills for developing Azure compute solutions, storage by connecting to and consuming Azure third-party services.
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- Dan Sullivan via Udemy
- 40,728+ already enrolled!
- ★★★★☆ (1,645 Ratings)
The demand for data engineers is increasing all the time, and certified data engineers are among the highest-paid certified professionals. Data engineers must be able to design systems to ingest large volumes of data, store data cost-effectively. Learn to process and analyze data efficiently using tools ranging from reporting and visualization to machine learning. Earning a Google Cloud Professional Data Engineer certification validates your knowledge and abilities to design, tune, and monitor high-performance data engineering systems. In this course, you will learn how you can prepare for the Google Cloud Professional Data Engineer Exam. You will learn how to build scalable, reliable data pipelines, how to choose appropriate storage systems, including relational, NoSQL, and analytical databases. Finally, you'll be able to apply multiple types of machine learning techniques to different use cases in machine learning models.
I can say that after taking the course, I have a good understanding of GCP services, Data Engineering, and even some Machine Learning. In terms of certification preparation, I found the course author's book to be more useful because it delves deeper into the exam topics, which you can't expect from a 6-hour video course (Ivan Boyaryn, ★★★★☆).
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- Eshant Garg via Udemy
- 26,188+ already enrolled!
- ★★★★★ (4,692 Ratings)
This course welcomes beginners in the Azure platform, database developers, database administrators, (DBA) business intelligence (BI) developers, or any database field aspirants. The course will enable you to identify the right Azure SQL server deployment option, purchasing model, and service tier according to requirements until successful deployment in the cloud. Learn to deploy Azure Synapse Analytics (formerly known as Azure SQL Data warehouse) in Azure Cloud environment and have a good internal MPP architecture understanding. Once you take the course, be ready to create an Azure Data Lake Gen1 storage account, populate it with data and analyze it using U-SQL Language after understanding Azure data's factory key components and advantages. Schedule, monitor simple pipelines and using HDInsight, you'll be able to fetch data from Data Lake, process it through Hive, and later will store data in SQL Server. If you are interested in this domain, seize the opportunity.
This course is worth its weight in gold!! I'm an aspiring 'cloud' data engineer, and this course has taught me a lot of new things. The best part is the balance between theoretical and practical explanations (demo). As a result, you can actually learn by doing. I wholeheartedly endorse this course (Mayank Ahuja, ★★★★★).
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- Google Cloud via Coursera
- 4 Months (4 hour weekly) of effort required
- 57,119+ already enrolled!
- ★★★★★ (5,662 Ratings)
This program provides you the skills you need, to advance your career. In this course, you'll have instructor-led training to support your preparation for the industry-recognized Google Cloud Professional Data Engineer certification. By taking this course, you will be able to identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud. You will learn how to employ BigQuery to carry out interactive data analysis, how to use Cloud SQL and Dataproc. Further, learn to transfer existing MySQL and Hadoop/Pig/Spark/Hive workloads to 'Google Cloud' and choose between different data processing products on Google Cloud.
Apart from the pub/sub/stream and bigtable modules, I believe the course has great techniques for sharpening your BigQuery SQL skills by approaching query investigation in a tactful way that will massively reduce query overhead while achieving optimization (Peter N, ★★★★★).
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- Ramesh Retnasamy via Udemy
- 11,259+ already enrolled!
- ★★★★★ (2,128 Ratings)
The course follows a logical progression of real-world project implementation with technical concepts explained in a step-by-step manner. Using data pipelines in Azure Data Factory (ADF), the course has been taught with implementing a data engineering solution using Azure Data Factory (ADF) for a real-world problem such as reporting Covid-19 trends as well as prediction of this virus. Here, you will acquire good Data Engineering skills in Azure using Azure Data Factory (ADF), Azure Data Lake Storage Gen2, Azure SQL Database, Azure Blob Storage, and Azure Monitor. Learn how to ingest data from sources such as HTTP and Azure Blob Storage into Azure Data Lake Gen2 using Azure Data Factory (ADF). From loading data to its transformation even how to schedule data pipelines in Azure, the instructor teaches you all. With a real-world project, learn how to monitor pipelines, build production-ready pipelines & practices.
This is an excellent course. In-depth and straight to the point. I enjoyed it and learned a lot about ADF, which helped boost my confidence as a new ADF user. I'm looking forward to more data engineering courses from this instructor (Sharat Nundoo, ★★★★★).
Checkout MOOC Options from Top Universities/Organizations in various domains
Final Thoughts
These were the details of the best public speaking class & courses. Now all you have to do is read the description of each of these courses and then choose the one which is more suitable and never stop learning.
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