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Christian is an Engineer with eight years of experience and working towards a Master’s degree in Applied Science. Christian began working in consulting and experienced first hand the value you gain from learning how to effectively utilize data. He’s now looking to build his own application using transportation data. We asked Christian about how he intends to use the skills learned in his Data Science course to complement his engineering background.
BrainStation: What is your education and/or career background?
Christian: I graduated from the University of Ottawa in 2010 with a B.A.Sc in civil engineering. Between 2010 and 2012 I did civil asset rehabilitation for the National Capital Commission, website migration for the Department of Foreign Affairs and International Trade, and completed the course requirements for my M.A.Sc in civil engineering.
In September 2012 I moved to Yellowknife to work as a Junior Project Officer for the Highways division of the Government of the Northwest Territories. In 2013 I began working as a Project Officer for the Structures division. The positions took me all over the Northwest Territories to deliver challenging projects, including winter road work.
While in Yellowknife, I designed and implemented an experiment to test a new technique to stabilize permafrost in a cost effective manner. I published and presented two papers on the subject.
In 2015 I moved to Vancouver and began working for a consulting company. We were hired as the technical advisors on the George Massey Tunnel Replacement Project. I spent most of my time as Project Manager of all traffic data survey and forecasting services. I developed an interest in using technology to manage data and extract value from it as efficiently as possible.
How did you first hear about BrainStation?
Through a barista at Quantum coffee.
Which course are you currently enrolled in?
The part-time Data Science course at BrainStation’s Vancouver campus.
What gave you the push or sparked your decision to register for the course?
If oil was the commodity of the 20th century, data is the commodity of the 21st century. Crude oil requires refinement to become valuable; “crude” (or raw) data also requires refinement to become valuable. Data science is the best way to “refine” data.
What aspects of the course are you most excited about?
I am excited to become more equipped to design solutions to big data problems and to meet and learn from industry professionals and others. The unit I am most excited for is the Machine Learning unit.
How are you hoping to apply these skills in the future?
I am developing an application platform to bring value to the public through transportation data. The platform will process all kinds of information, including vehicle counts, travel time, and parking data in order to efficiently deliver useful insights to executives and analysts. Data Science will allow us to extract and deliver additional value.
Learn more about the Data Science course.