School:Coursera
Duration:6-9 months
Locations:Online
Date:Mar 14-Dec 14
Commitment:Part-Time
School:CareerFoundry
Duration:8 months
Date:Jan 31-Sep 30
School:Humber College
Duration:1 day
Date:Feb 17-Feb 17
School:Emily Carr University of Art and Design
Duration:2 years
Locations:Vancouver
Date:Feb 3-Feb 3
School:General Assembly
Duration:12 Weeks
Date:Mar 7-May 27
Commitment:Full-Time
School:BrainStation
Duration:5 or 10 weeks
Locations:Antigonish
Date:Feb 8-Apr 12
School:Springboard
Duration:6 months
Date:Mar 7-Sep 7
School:OCAD University
Duration:5 weeks
Locations:Calgary
Date:Mar 23-Apr 27
School:The G. Raymond Chang School of Continuing Education, Ryerson University
Duration:1 year
Date:May 2-Apr 28
Date:Jun 21-May 26
Duration:12 weeks or 8 months
Date:Feb 27-Oct 28
School:LDA (Learn Data Analytics)
Duration:2 or 4 weeks
Date:Mar 17-Apr 7
School:University of Toronto School of Continuing Studies
Duration:24 weeks
Date:Feb 23-Aug 12
School:University of Calgary
Duration:4 months
Date:Sep 5-Jan 6
Date:Feb 28-Mar 21
School:George Brown
Duration:7 weeks
Date:May 3-Jun 14
Duration:4 or 8 weeks
Date:Feb 1-Mar 22
School:Toronto School of Management (TSoM)
Locations:Toronto
Duration:12 weeks
Date:Apr 19-Jul 8
Date:Apr 6-Jun 8
Duration:5 days or 10 weeks
Date:Apr 4-Jun 15
School:Lighthouse Labs
School:WeCloudData
Date:Apr 19-Jul 7
Date:May 3-May 3
Duration:4 days, 5 or 10 weeks
Date:Apr 5-Jun 7
During the last decade, data science, in particular, and the data field, in general, have become the most wanted and widespread fields in the labour market. That is why more and more people annually want to work as data scientists, analysts, UX designers, and programmers. In each of these professions, knowledge of data visualization is essential.
Nowadays, one can find numerous programming languages and software for data visualization. However, do not think that it is as easy as placing several plots, numbers, and histograms on the data dashboards. You must know how the data talks, know how the data analysis is performed, and understand essential metrics and which plots are better used in a particular situation.
All this knowledge about creating data visualizations can be found in numerous online courses. Below, you will find a complete guide on how to find the best data visualization course, so stay with us!
Thinking that people who perform data visualizations only visualize data is completely incorrect. Those people also often work with raw data and do the same work as data analysts. They combine data, interpret data, and finally present data. Thus, it is not enough only to know how to build beautiful data visualizations and work with data visualization tools; it is also necessary to know the basics of data analysis and be aware of the data science field tendencies in general.
The major software and programs that you will have to work with in order to create custom plots and add visual elements to the initial raw data sets are:
As you can see, it is essential to know at least one programming language. If you want to create impactful data visualizations, you must know what data-driven decisions and data-driven findings are, so you will have to interact with some big data on an SQL server, for instance. It is important to know how to perform exploratory data analysis and find the main tendencies in order to present the best possible data storytelling with interactive visualizations.
Most courses in data science suggest all the core concepts of data visualization. Hence, by learning data science, you also discover how to create compelling data visualizations. Note that some data visualization courses also include learning a statistical programming language, which can be extremely applicable to advanced senior positions.
Visualizing data implies knowing essential data visualization principles, which are surely taught in online courses. First, you will work with simple datasets and create only several widely used plots (pie charts, Excel charts, histograms, bar charts), which will let you understand how to interpret data and what is important in information visualization. Then, in order to master visualization techniques, you will learn the principles of creating beautiful plots, discover more different visualizations (viola charts, regressions, stacked plots), and make data-driven findings.
The important thing to note is that a good high-quality course will surely include a final project which you will be able to include in your portfolio and CV.
The majority of data visualization online courses suggest projects connected rather with business analytics or infectious disease trends and world health. You will work with real data and present all the steps of your work and preprocessing – from the preparation of data to the final visualizations. Creating such projects will help you to fully understand and remember data visualization principles and not be afraid to use them fully.
If you succeed in learning and performing major data visualization skills, you really have a high chance of building a successful and overwhelming career in the IT sphere. As was mentioned, stunning data visualizations are not enough to enter the machine learning field, yet it is a good start to understanding how data and information work.
Basically, it is impossible to say that everyone can become a programmer or analyst. Nevertheless, it is still feasible for many people to comprehend this profession. No special communication skills are needed here as well as creativity, since success in data science depends only on your knowledge and cold mind. You shall understand the needs of the industry and a particular client and know how to work with sample code and various visualization tools.
Many modern IT organizations and multinational companies seek proficient analysts and data scientists, which means it is always possible to find job opportunities. Furthermore, some local companies and brands are also in need of their product data analyzed and visualized.
If you still doubt the trustworthiness and legitimacy of online courses, here are some points that you should pay attention to and which you can benefit from.
First of all, many courses invite industry leaders and valuable professionals, for instance, head analysts from Google and Amazon or professors from New York University. Such material includes tons of valuable insights and helpful video content, which you can rewatch numerous times whenever you want.
Secondly, if you think online education leaves students without feedback, you are not correct. The tutors are often available to answer questions and even help with employment. An intensive introduction to any course includes all the essential information about the course and its subject. However, you can always ask for a detailed description of each topic.
Lastly, online education courses are convenient to accomplish. You can combine them with your former education or work, do exercises whenever you like (surely, within the time limits of the course itself) and wherever you like. At the end of the course, you get the ready-made portfolio and the evidence that you finished the professional certificate program, which you can also use in your CV.
There are several online education platforms that suggest free courses on data visualization. Such courses can be found for various programming languages and specified tools or directions, so you can pick the course which targets your unknown topics.
After you succeed in learning data visualization tools and principles, you create several projects that evidence your knowledge and skills. Then, you should make your CV and proceed to the companies that seek data analysts.
It would be really suitable if you knew any programming language along with data visualization programs. What is more, it is better to be cold-minded and be ready to solve difficult issues connected to products and processes. Hence, you should be interested in finding complex solutions.
You never know if the particular field is for you until you try. Do some research on data visualization projects and think whether you could do something similar. If you know how to make a dashboard that will represent the main tendencies of the data, you may suit the field well!