School:Langara College
Duration:6 weeks
Locations:Online
Date:Mar 8-Apr 12
Commitment:Part-Time
School:WeCloudData
Duration:10 weeks
Date:Aug 20-Sep 24
Duration:14 weeks
Date:May 23-Aug 19
Commitment:Full-Time
School:BrainStation
Duration:12 weeks
Locations:Toronto
Date:Apr 19-Jul 8
Duration:12 weeks or 8 months
Locations:Antigonish
Date:Feb 27-Oct 28
Locations:Vancouver
School:University of Toronto School of Continuing Studies
Date:Feb 15-Feb 15
School:Juno College
Duration:8 weeks
Date:Mar 20-May 8
School:Lighthouse Labs
Date:Mar 7-May 27
Duration:24 weeks
Date:Feb 16-Jul 30
Duration:5 weeks
Date:Mar 6-Apr 3
School:University of British Columbia
Duration:10 months
Date:Sep 5-Jun 28
School:General Assembly
Duration:12 Weeks
School:The G. Raymond Chang School of Continuing Education, Ryerson University
Duration:1 year
Date:May 3-May 3
Date:Jul 12-Aug 10
School:Southern Alberta Institute of Technology (SAIT)
Date:Feb 28-Apr 4
Duration:2 weeks
Date:May 9-May 20
School:Canadian College of Technology and Business (CCTB)
Duration:70 weeks
Date:May 2-Sep 1
School:Springboard
Duration:6 months
Date:Mar 7-Sep 7
Date:Jun 15-Dec 10
Data engineering is all about collecting, storing, analyzing, and grouping data that exist within a company. This data comes from various sources and is available in different formats. A data engineer's job is to manage data and make it usable and applicable in practice, which includes interpreting, getting rid of errors, removing duplicates, and building data pipelines.
This field is growing very fast, and almost every company looks to have skilled data engineers and data scientists on their team so that they can design data models and help businesses to navigate through a huge amount of information that is circulating around the business.
Data engineering solutions would be valuable to any business because it is of utmost importance to any company to make use of the data that can help predict future trends and optimize already existing processes.
Data engineers and data scientists often go hand in hand to streamline the processes inside a company, but the question is, what is the difference between the two? We are going to give you a brief answer to it below.
Data science is about working with raw data and extracting the most valuable parts from it. A data scientist needs to process data and understand how everything works together. On top of that, these specialists are usually asked to present their findings to stakeholders and prove that their analysis has value to the business.
Data engineering relates to building systems that collect and store data, as well as maintaining them. In other words, data engineers need to build systems that will allow a data scientist to get the necessary information. The role of a data engineer is to design data models and create data pipelines, together with being responsible for data storage and building cloud data warehouses and data lakes.
All in all, both data engineering and science mean working with a data ecosystem and massive datasets; they only focus on different aspects of data processing.
If you have set your mind on learning data engineering skills and working in the field of big data, data transformation, and data structures, you can sign up for a course that will take a certain amount of hours per week and will make it possible for you to get the grasp of data engineering.
Most courses do not ask candidates to have a degree in computer science, but there is certain prior knowledge that those who wish to have a data engineering career are required to have, and that is the following:
Different courses might have prerequisites that are necessary exactly for them, so do not forget to check the list of required skills and knowledge before you enroll in a program.
If you are ready to start your data engineering journey, it is time to have a look at the study options that would fit you personally and meet your learning goals. In general, data engineering courses comprise some basic skills and processes that, or data engineering fundamentals, will help you get an overview of what working in a big data ecosystem is like.
Usually, data engineering courses include the following:
Some online data engineering courses not only offer a chance to learn data engineering in theory but also give the opportunity to work on a capstone project at the end of the learning process.
These real-world projects will show your potential employer that you are ready to become a successful data engineer and can apply your skills in building cloud-based data warehouses, supporting machine learning models, navigating through a data engineering ecosystem, and implementing data engineering solutions in real life.
We can suggest a few criteria that will make it a bit easier for you to single out what exactly you need:
It is easy to get lost in a wide variety of information and find it hard to make the right choice, especially in terms of learning courses. Consider the options carefully, scale up the benefits and effort needed and pick the right course you prefer!
Of course, you can. With the development of online education, it is possible to take almost any course online, and a data engineering course is not an exception. In the course of study, you will learn data analysis and get familiar with big data tools and big data concepts, data modelling, and data infrastructure. You will also have the chance to work on your data engineering portfolio project that will showcase your skills.
If you have good skills in computing and mathematics, you can learn them yourself. However, if you want a professional tutor to guide you and monitor your work, we recommend browsing through the best data engineering courses available. They usually take up to 10 hours per week and will provide you with career services such as access to some necessary tools.
Every program has its distinctive features; for example, if you take the Data Engineer Nanodegree Program, you will learn all the skills that are a must in the world of data. If you enrol for a Professional Certificate in Data Engineering, you will focus on some basic skills that will allow you to take your first steps in the field, whereas the Google Cloud certificate will center around the Google cloud platform. But as a core, you will definitely learn to extract data, deal with a data pipeline, build data warehouses and work with data lakes.
The cost of the program depends on many factors, whether you wish to audit the course or take advantage of working together with a mentor, whether you desire to finish with a capstone project, or whether a certificate is enough. Different schools and platforms have a range of options and courses to choose from, so it is your choice to compare and analyze them in terms of price, too.