Over the last few years, most enterprises have undergone a digital transformation and produced unimaginable volumes of data. This raw data is insufficient to push data science projects forward in production. As per Gartner, back in 2017, 85% of data projects failed because the data could not be trusted to facilitate business decisions. Gartner predicted these results because earlier data scientists were expected to work on the data before actually using it in the project. However, it has become apparent that “someone” needs to organize and transform this data to ensure quality, usability, and availability so that data scientists do not spend much time before the actual work begins. Data engineers are the ones who get this job done. You can opt for a data engineering course to learn more about data engineering and get one of the most in-demand jobs in the big data world.
What do data engineers do?
A data engineer’s primary objective is to transform the raw data into something valuable and understandable before presenting it to an enterprise. In addition, they must design, construct, test, mix, manage, and refine the data using various tools and sources. The goal is to build data pipelines that operate efficiently. Additionally, data engineers work closely with the infrastructure teams to automate several steps in the data engineering procedures. In addition to all of this, they create challenging queries to make the data available.
Top Data Engineering Courses
Several data engineering courses are available, and selecting the right one is challenging. This article has enlisted some knowledgeable courses for a data engineer. Have a look.
- Professional Certificate in Data Engineering Fundamentals (IBM)
Professional Certificate in Data Engineering Fundamentals (IBM) is an excellent introductory data engineering course if you are interested in venturing into data engineering. Since data engineers are the core of a data science project as they create pipelines guiding the workflow, it becomes inevitable not to know the fundamentals. This course provides a comprehensive theoretical and practical introduction to building pipelines, managing data, and engineering work ecosystems to lifecycles.
The certification includes three sub-courses:
- Data Engineering Basics
- Python Basics for Data Science
- Relational Databases and SQL.
The course will span over 4 months and take an average of 4-6 hours per week.
- Data Engineering with AWS Machine Learning (Pluralsight)
Storing data for complex machine learning projects is tedious because of varying data formats. This data engineering course focuses on how to store data and leverage machine learning on the AWS platform. In this course, Data Engineering with AWS Machine Learning by Pluralsight, you will learn how to select the appropriate AWS service for each data-related activity for any given scenario. Initially, you will investigate data storage options and the purposes of each type of storage. Finally, you will learn to transform raw data into usable formats.
The course will cover several topics that will introduce you to data engineering with AWS.
- Typical Data Flow for ML on AWS
- Database Storage Options for ML on AWS
- Data Warehouses and Data Lakes
- Batch Data Ingestion
- Data-driven Workflow
It is a short course that you can finish within 3 hours and will bring you one step closer to using AWS machine learning services with ease.
- Data Engineering Learning Path – Coursera
Data Engineering Learning Path is an excellent umbrella course offered by Coursera with which you can learn essential skills that a data engineer needs. Coursera suggests a combination of sub-courses that will aid you in moving towards a full-fledged data career. The following courses are recommended for a data engineering learning path:
- Business Intelligence Analyst – Power BI, Tableau, SQL
- Business Intelligence Developer – Software development, SQL, Javascript
- Data Engineering – Python, Big Data, ETL
Coursera recommends a Coursera Plus subscription to guide you through multiple courses in a career learning path, with access to over 3000-course options.
- Become a Data Engineer: Mastering the Concepts – LinkedIn Learning
If you are looking for a data engineer course online, LinkedIn Learning offers an extensive beginner-level course, Become a Data Engineer, for those who wish to learn the fundamentals of data engineering from scratch. You will study the core principles of data engineering, DevOps, trade-related tricks, and how to use them in platforms for project work. The course discusses Big Data, SQL, and NoSQL coding for analysis. Moving forward, you will understand how Apache Sparks work with Big Data technologies.
The course will cover
- Data Science Foundations
- NoSQL Essentials
- Apache Spark Essential Training
- Architecting Big Data Applications
- Cloud SQL and SQL Essentials
- Advanced NoSQL for Data Science and SQL Professionals
It will take approximately 13 hours to cover the entire material, and you will get a certificate on completion.
- Data Engineering – ETL, Web Scraping, Big Data, SQL, Power BI (Udemy)
If you are looking for a big data engineer course, Data Engineering – ETL, Web Scraping, Big Data, SQL, Power BI is a beginner-level data engineering course that will teach you how to interact with data. It covers ETL, Web Scraping, SSIS, SQL, and Big Data.
The crash course is divided into twelve sections covering 134 video lectures covering the following topics:
- ETL, or Extract, Transforms, and Load, a data pipeline using which people can extract data from several sources, transform it according to the requirements, and load it in a data store.
- Secondly, you will also learn about SQL Server Integration Services for data integration, transformation, and solving business problems.
- Big Data, including numbers, audio, images, text, and other kinds of data with high volume, variety, and velocity.
- You will become familiar with SQL, a standard programming language for managing databases.
- Lastly, you will learn Power BI, a robust business analytics solution that helps with data visualization and business insights.
The course content is about twelve hours long and can be completed flexibly. On completion, you will be able to implement ETL with SSIS, scrap web data with Python, Beautiful Soup, and Scrapy, connect web data with Power BI, and model with Power BI.
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- Professional Certificate in Data Engineering (IBM)
After learning data engineering fundamentals, proceeding with another course, like Professional Certificate in Data Engineering by IBM, will be a significant next step. This is one of the best data engineer course in India, designed for people who want to advance their interest and knowledge in the field. It advances the basics while teaching you application development, more complex pipelines, and data warehousing.
The course is divided into 14 sub-courses that will give you an insight into cloud-based relational databases (RDBMS) and NoSQL databases. Some of these are:
- Python for Data Engineering
- SQL for Data Engineers
- Building ETL and Data Pipelines
- Big Data Engineering, Hadoop, and Spark Basics
- Data Engineering Capstone Project
The course spans over one year and two months, with an average of 3-4 hours per week. On completion, you will have acquired skills in Hadoop, Big Data, PostgreSQL, Bash, Data Warehousing, and other related technologies.
- Microsoft Azure Data Engineering Associate DP-203 Exam Prep Specialization
It is not a standard course like other data engineering courses. However, opting for Microsoft Azure Data Engineering Associate Exam Prep Specialization will give you a different insight into data engineering. It is a rewarding path to being an associate with Microsoft, where you will learn about basic theoretical concepts and get hands-on experience with real-world scenarios.
The specialization program will cover the following sub-courses:
- Data Engineering with Microsoft Azure
- Data Storage and Integration
- Data Warehousing and Engineering
- Preparation for Data Engineering on Microsoft Azure Exam
It will take approximately thirteen months to complete, with an average of two hours per week. On completion, you learn about Azure Synapse Analytics, Apache Spark, Modern Data Warehousing, Azure Data Lake Storage, and other related technologies.
- AWS Solutions Architect Associate Certificate Prep
A data engineer must know at least one cloud service provider and its services. Amazon Web Services (AWS) is an industry leader in cloud computing. Data engineers acquainted with an AWS Certified Solutions Architect – Associate (SAA) have better chances at career profiles and high earnings. In this intermediate-level course, AWS Solutions Architect Associate Certificate Prep, you will get expert guidance on how and what to prepare for the examination.
The first week talks about multi-tier data solutions and storage technologies. The following week talk about flexible and scalable computing solutions and database networks. In week three, you will learn how to secure your data and database network. Lastly, the fourth week will teach you computing and database services cost optimization.
The month-long course comes with flexible deadlines, sample certification questions, and skill-based hands-on exercises on data structures and architectures.
- Taming Big Data with Apache Spark and Python
This Big Data engineering course, Taming Big Data with Apache Spark and Python on Udemy, focuses on Big Data analysis using Apache Spark and Python. With more than 20 hands-on examples with large data sets, you will learn to use DataFrames, structured streaming with Spark 3, and MLLib for ML-driven data mining and other related concepts. The course is divided into eight sections, covering 66 video lectures. These sections are structured to cover the following concepts:
- Introduction to Spark and RDD interface
- SparkSQL, DataFrames, and DataSets
- Spark Clusters and Spark ML
- Spark Streaming and Graph X
The course will take approximately seven hours, with access to a personal Windows/Linux computer and some prior scripting experience.
- Data Structures and Algorithms Nanodegree (Udacity)
In this data engineering course, Data Structures and Algorithms Nanodegree from Udacity, you will be acquainted with more than 100 data structures. Data engineers should know their way around multiple data structures and algorithms to be proficient in managing and sorting data. Knowing about data structures also makes them capable of understanding patterns in data and deciding appropriate operations. During the course, industry experts will deliver online lectures on Udacity’s platform and provide personalized project reviews. Once you finish the course, your project will undergo a strict review process to get certified.
The certification will cover three sub-courses:
- Data Structures
- Basic Algorithms
- Advanced Algorithms.
You need to have a basic knowledge of Python and Algebra to enroll in the course over 4 months, with an average of 10 hours per week.
