How to Make Your Data Science Presentation Great and Memorable
Recall the last data science talk that inspired you? The one you thought that had an impressive impact. Was it only the mathematical…
Recall the last data science talk that inspired you? The one you thought that had an impressive impact. Was it only the mathematical technicalities or the state-of-the-art accuracies that caught your attention?
Surely not. Effective presentation techniques play a major role in taking an idea to a wider audience. And having the skills to deliver a memorable presentation is vital to any researcher.
Great presentations help you to build a brand for your research and yourself, which will guide you immensely in your academic or professional career prospects.
This post guides you through some of the key points that would make a data science research presentation more effective. I start by discussing five generic ideas and dive a bit deeper into one vital point, which is the storyline of your presentation.
Good structure. A good presentation takes the audience on a journey step by step. And at each step as you progress, your ideas should reveal an ultimate goal that is clear to the listener. A common structure always starts with an introduction about yourself and your research problem. It is important to set a clear scene initially so you can build your story from there. The storyline, which is in fact the most important feature of a good presentation will be discussed in detail later in the post.
Professional slides. Slides reinforce your story. You cannot underestimate the influence of quality slides on an audience. Here, it is important to keep in mind that your audience would tend to read everything on your slides while listening to you. So choose wisely what you want on your slides. Otherwise, it can distract your listeners and confuse them in the end. A lot of text on the slides is usually a bad idea. Effective graphics are proven to grab attention and help clear understanding. Keep your slides uncluttered as much as possible.
Technical contributions. The ultimate goal of any research is the contribution you make to an industry or knowledge in general. So you want to emphasise on the technical contributions you were able to deliver with your work. Again this is an important part of your storyline which is discussed further in this post.
Clear and entertaining delivery. No matter how good your material is, the way you deliver it would decide whether your presentation is going to be memorable or not. Clear and correct use of language is important together with good pronunciation and phase. Make sure that you are audible to everyone and do not forget to smile.
Confident speaker. Some might argue that confidence depends on each person’s character, but there are factors that you can use to improve your confidence levels walking into a presentation. Good preparation before the presentation is utmost important here. Make sure you practice delivering the talk at least several times before going on stage. Trust me, it won’t be a waste of time and it would enhance your confidence more than you think!
Storyline in key
Now let’s focus on one of the most crucial points when preparing and delivering your research presentation, the storyline. This decides the number of ears you will have throughout your presentation.
Below are the key areas you want to build around in order. Of course, some topics are interchangeable according to your preference, but this an effective outline if you are looking for one to guide your presentation preparation.
Setting the scene. This should be the first and foremost target. What is the problem you are addressing in your research? And why is it timely, relevant and interesting? Why does it matter? Make this setting very clear, and you have the attention of your audience grabbed. It should form the basis of what you are trying to convey. And the purpose of your efforts. When listeners can relate to your setting, it is hard to ignore you.
Focus on your hypothesis/solution for your setting. Soon following the setting, you can get your audience to focus on your hypothesis/solution for the problem you are addressing. This is vital because now they see instantly what you are proposing, and they are keen to know more. So then you can guide them to the next steps of revealing your methods and procedures.
Methodology/approach/work done. Now you explain your work towards achieving what you claimed in the previous step. Make sure to be concise. Nobody likes math formulas or deep technical details. Also avoid the urge the show-off your math or coding skills during this step. Simply present the steps you have taken on a higher level. If anyone is interesting to dig deep into the technicalities, they will follow up later. Flow charts and graphics are highly effective in this step. Paragraphs of text is a mistake.
Context/related work. Now some might argue that this point should come before the methodology. In some cases, it can be true. But my argument is that the attention span of the audience will be high at the beginning of the talk. And that is where you have to get your work in the spotlight. If you do a good job at it, you anyway have the audience when you go into this step. Since they are eager to know what you have done, presenting related work, in the beginning, might bore them up without cutting to the chase. Nevertheless, context is important and you have to make your approach stand out from the existing techniques and ideas.
Contributions made and results. Highlight your impact. Show your outcomes and results of your applications. Point out the contributions you have made to the knowledge and understanding of the field. This is where you strengthen your stand in the solution you have proposed.
Outlook/open questions/future work. Eventually, keep a note on the broader arena that your efforts showcase. Now one point to ponder upon here is that, do you mention any limitations of your research if any? My opinion is yes. This is the place to convey your weaknesses and this will come out as a positive impression on your work. Also, open up questions for future work with your particular approach and emphasise the potential impact.
I hope this post provides guidance to anyone looking to improve their presentation skills, especially in the highly technical field of data science. Personally, this is something I have spent considerable time on improving myself because I strongly believe in the impact of effective presentations for your research. Executed properly, these skills would help you boost your career as a researcher or data scientist.
I would like to hear your thoughts on this as well. Reach out to me on Twitter or comment below.
Thanks for reading.