Sharing my recent experience — talking about Data Science
I gave a couple of tips in my two recent blog posts about what a Data Scientist can do to keep focus. Finding an audience to talk about data science was one of them. Recently, I had the opportunity to be the main speaker of a webinar whose objective was to educate non-data people about data science. I found it beneficial to share that experience in today’s post.
A bit of context first…
Speak in public is nothing new for me. Back in the days, I used to be a co-host of a radio show. I participated during my young ages to clubs and associations where I had to speak in front of large audiences. During my professional experiences, I prepared and did a ton of presentations to different levels of staff. Thus, when I got the invitation from Ayiti Analytics to be a speaker for their ‘Meet a Data Scientist’ series, I didn’t think twice before answering. I thought it would be a great opportunity to share my knowledge and help others. Also, that was a huge occasion to prove that I master data science concepts. Explaining complicated information to people that are not necessarily in touch with the domain shows that you understand what you are talking about it.
I was looking for the event as it was my first major talk about DS post my learning experience. I presented my final project in a science fair however the audience was more advised. The webinar was formatted as an interview; the host would be asking questions that I would provide with answers. More or less 15 minutes were dedicated to questions from the public. I was so excited. But I had to prepare first — I got the questions from the host a week before. I got everything ready before the day; it was interesting to see how it can be difficult to translate into layman terms the concepts that you comprehend pretty well.
What was my approach?
I had two objectives in my mind for the webinar: increase the participants’ curiosity about Data Science and improve my communication skills.
The questions were more about definitions, clarification of concepts, areas of expertise of a Data Scientist. It was a good information sharing session and I wanted to use that chance to educate the participants about that hot topic and help them find a new career path. Why not? To do so I had to go through the basics and be as clear as possible. The best way that I thought of approaching it was to illustrate each point that I was planning to develop. And that’s what I did. I made sure that I found a real-life example for each question. By doing so, I imagined that I managed to be closer to my audience and showed them something concrete. They don’t have to think hard about it — they can have a sense of what I am talking about.
To deliver my messages, I had to work on my communication skills as well. It is one thing to have all your talks planned and redacted, but it is another thing to utter it. I had to consider mainly who my public would be. Once I found out, I adopted a specific way for my speech where they would find themselves and be more prone to listen to me. I had to be careful in my word choices. During the presentation, I talked slowly, followed my guidelines and explained at least twice an idea. I decided that along with using a technical word, I would define it as well and use an example to illustrate it. While this helped me take care of the presentation, it was a good exercise for me.
As I recommended last week, that is a good activity that a data scientist should partake in to improve some of his skills. I would do that experience anytime as it helped me. Even though someone is familiar with speaking in public you can’t be too ready. Some preparations are necessary; based on the audience, some extra work will be required.
If you have any tips that you want to share with me, let’s connect and we can discuss. Also, I can share and talk about the questions from the webinar.
