UofT Data Science Workshop: Intro to Clustering with R

May 2, 2017 @ 6:00 pm – 9:00 pm
Department of Computer Science Innovation Lab at U of T
2nd Floor
Sigmund Samuel Library Building 9 King's College Circle, Toronto

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This meetup is only for students at the University of Toronto. Due to space constraints, we can only accept 90 students in the room on a first-come, first-serve basis.

What is clustering and how is it used in unsupervised machine learning?

Come to this workshop and learn and try out k-means and hierarchical clustering in R.

The agenda of the workshop will be the following:

1. Lecture – Overview of Clustering Algorithms

2. Lecture – Hierarchical Clustering

3. Hands-on – Hierarchical Clustering

4. Lecture – k-means Clustering

5. Hands-on – k-means Clustering


Please bring your laptops to take part in the hands-on session. Please sign up for an account on https://datascience.ibm.com before the event.

Meetup is limited to 90 attendees, to optimize the experience of the attendees.

Livestream will be available on a best-effort basis.

University of Toronto students:

This workshop is for UofT students, to provide skills and training for two upcoming hackathons sponsored by IBM Big Data U:

1) ASA DataFest 2017 – May 5 to 7, 2017

DataFest is sponsored by the American Statistical Association (https://www.amstat.org/education/datafest/).  The event is like a hackathon, for undergraduate students, except the problem is a data analysis problem, rather than a programming problem.  Teams of students get a dataset on Friday afternoon and work on the problem until Sunday afternoon where they present their results.  After two days of intense data wrangling, analysis, and presentation design, each team is allowed a few minutes and no more than two slides to impress a panel of judges.

2) Stem Fellowship Big Data Challenge 2017 – May 1 to 30, 2017

The BDC, in association with IBM Big Data University, will take place in the month of May, with the morning and afternoon of May 1st marking the BDC’s Orientation Day. The remainder of the month will involve teams working independently on their projects at their own respective paces; participants will also be invited to ongoing workshops for data science tools over the course of the competition, as well as talks from leaders in industry and academia.


Alex Aklson, PhD., Data Scientist, IBM – Alex is a data scientist at IBM Canada. Before joining IBM, Alex worked as a data scientist at Datascope Analytics, a data science consulting firm in Chicago, IL. Alex received his Ph.D. in Biomedical Engineering from the University of Toronto.

Polong Lin, Data Scientist, IBM – Polong is a Data Scientist at IBM Canada.