Skip to main content


Course Code: CEBD 1200
So, you want to get into Big Data science and analytics but you’re new to programming. Or maybe you’re a novice user of another programming language. Either way, you’ve come to the right place. In this course, you’ll
acquire the skills and competencies you need to implement a basic but complete data-science project in R, covering core language concepts (variables or loops, etc), as well as visualization and data modelling. There are currently over 2 million people worldwide performing data analytics using R and you can be one of them! Ready to start?

This is a Bring Your Own Device Course. You will be required to bring your laptops to each class and download designated software prior to the beginning of class. Important: you will be required to do 5-10 hours of work per week outside of class time. If you have little or no prior knowledge, you might need extra time to gain familiarity with the concepts. But don’t worry. You’ve got this!

NOTES: Are you new to Big Data or only have the basics? We strongly recommend this course if you’re going into the Big Data IT Stream. But first, read this: If you’re unsure of which programming environment you’ll be working in, start with CEBD 1100—Introduction to Data Analysis and Python. If you’ll be expected to work with R in your professional context, start here.

Your take-away

This course is a great way to help you:
• Configure a functional R environment to program efficiently in R;
• Use R to implement a variety of data-related functions commonly used in the workplace;
• Apply common software engineering best practices to manage R programs throughout their life-cycle;
• Employ a range of analytical skills needed to solve common problems faced by software developers.

Our approach

This course employs student-centered, project-based learning that's focused on the acquisition of practical, real-world skills and not just theory. You'll get close, personalized instruction from an industry pro.

Who benefits the most?

• Anyone who wants to follow the IT stream in the Big Data program.
• Individuals who want to improve the performance of their organization by harnessing Big Data.
• Professionals who want to leverage data for better decision-making.
• Entrepreneurs with projects that could benefit from data analytics.
• Students of geography, biology, psychology, humanities or any other field with big data.
• IT professionals who want to transition to Big Data from more traditional sectors.
• People who are new to programming or are novice users of Python or another programming language.
• People who are genuinely interested in Data Science and Analytics and would like to better understand what they can do with R.

Important details

Here's all the important information you need in order to get ready for class!
During the first class, some time will be devoted to installation troubleshooting and support, but students will be expected to install the R and RStudio software prior to the first class (see instructions below).

1. R > 3.0.1, follow the download and install links:
For Windows:
For Mac OS X: (click on R-3.6.1.pkg)
2. RStudio Desktop > 1.0:
For Windows 10/8/7:
For Mac OS X 10.12+:
3. R packages used in the course: in RStudio, run:
4. Computer requirements:
Operating systems: Windows 7/8/10, or MacOS 10.12+
At least 4GB of RAM
At least 5 GB of available storage

Concordia CCE Loyalty Discount

All students who meet at least one of the following conditions, will receive a 10% discount on their CCE course or workshop tuition fees:

1)   Have completed a CCE, Undergraduate or Graduate course at Concordia University in a prior academic term;

2)   Have completed a language proficiency test (IELTS) at CCE;

3)   Have completed a CCE Professional Development Seminar/Workshop.

This discount is based on the information maintained in the Concordia University student information system.

NOTE: This discount does not apply to a language proficiency test enrollment (IELTS) nor to application fees for admission to a CCE program of study.


Back to top Back to top

© Concordia University