How to run a successful Data Science meetup

Posted on October 08, 2020 by Jacky Tea

How to run a successful Data Science meetup

Posted on October 13, 2016 by Raul Chong

Meetups have become very popular in the past few years, but it is not easy to get a meetup community going successfully. Every now and then different meetups just ‘die’. Like many other community initiatives, you need to nurture your community and provide value. Though having some funds to run the meetups definitely helps, it is not necessarily the main factor for success.

The BDU (BDU) Toronto Meetup ( recently surpassed 6200 members! and it currently sits as the #9 largest Data Science meetup worldwide, where the top spots are based out of New York and San Francisco. Most if not all of these Data Science meetups started one to three years before us though, and the audience is not exactly the same.

In the case of the BDU-Toronto meetup, what started back in 2014 as a pilot has turned out to be one of our most successful initiatives in Toronto and other cities in Canada and around the world. Just like BDU itself, the BDU meetup started in a similar fashion to a startup company: Little to no funding, many people opposing to creating it, and no established venue. Our first meetup attracted about 25 people. Today, without any marketing other than posting events in, we get at least 100 people to attend per meetup! Just like a startup, we pivoted a few times, where the meetup name changed, and the topic/interest was narrowed down.

There are several reasons why the BDU meetup has been very successful, especially in Toronto, where it started. First of all, you know a meetup is successful when you see a healthy number of new members joining weekly; but moreover, if you’ve had a chance to attend our events, you will see first hand the excitement and engagement of the community. In most of our meetups, about 90% of attendees stay all the way until the meetup is finished (typically around 9pm). Last week we held our ultimate proof that our meetup is rocking!. On a Friday evening of a long weekend, we scheduled a meetup to discuss *volunteer* opportunities in Data Science. We booked the IBM downtown Toronto venue, and we got 200 RSVPs and probably more than 100 people showing up! We started the event with a big “Wow!

In my opinion, these are the reasons why the BDU-Toronto meetup is succeeding:

  • It focuses on quality of delivery and content.
    Our main presenters, Polong Lin (IBM Data Scientist) and Saeed Aghabozorgi (IBM Senior Data Scientist) spend a lot of time preparing. They are eager and proud to present and share their knowledge. They choose great examples. They also vet any other presenters from the community to ensure they are good presenters and have good materials themselves.
  • It delivers value to attendees: Everyone always learns something
    The person who arrives to our meetup when it starts is not the same as the one who leaves at the end of the event. This person is ‘transformed’ with new skill!
  • It uses a hands-on approach to learning.
    We use the Data Scientist Workbench (DSWB) for our interactive learning sessions. Minor to no setup required!
  • It is held in a vibrant area of the city, with easy access
    The downtown area in Toronto is vibrant and has easy access to public transportation (subway), is close to universities, colleges, startup companies, large financial companies, incubators, institutes, hospitals, research centres, and entertainment!
  • It teaches hot technologies and concepts about Data Science, Big Data, and Analytics.
    These are hot areas these days that everyone, no matter the background, should learn. By the way a quick way to get started is by taking the Data Science 101 course at BDU. In less than a month this course has had more than 8000 registrations!
  • It has an active organizer team
    We are a small team of organizers, but we have almost mastered how to put together these events.
  • Events are scheduled frequently
    Frequent events mean the momentum is never lost
  • We are not afraid to try new things.
    We’ve already supported mini-hackathons, hackathons, a Data Science meetup for developers, and this past summer we sponsored a Data Science bootcamp.
  • We partner
    We have partnered with universities (University of TorontoRyerson U), university data science clubs, colleges (Lambton College), institutions (STEM Fellowship), other meetup groups (R Users Group).
    This helps us with promotion, awareness, and finding other presenters and topics.
  • We attend to community requests
    We get the community going by replying to their inquiries or issues. We have also recently set up a Slack group ( to get the community talking between themselves.
  • We offer free pizza and pop
    We offer free pizza and pop at the beginning of the meetup to encourage people to arrive early and so people are not hungry while learning once the meetup starts!
  • It is free!
    The event, the materials, the software, the food … all free!

People feel attending the meetup is time well spent. We know there is room to improve, especially in finding a good venue with good internet that can host us permanently. We also know our LiveStream is not very reliable, and that our registration system is not the best. We are working on all of these fronts, but our budget is a limiting factor!

We are proud to have started BDU meetups in other cities. The last part of the URLs below tell you were they are located:

If you would like to start your own BDU meetup in your city, please contact me! Having a local active organizer is very important. We can help you get established, but we need your long-term commitment.

If you are in Toronto, I hope to see you at our next meetup this October 20th! We’ve sponsored a Data Science for High School course (with credit in Ontario, Canada) and we will talk about this. As mentioned earlier, we are not afraid to try new things!