The flexibility to effectively present complex topics to a corporation is a skill that clearly sets data professionals apart within the working world. It’s vital to distill intricate information into clear explanations when working with convoluted topics, and the success of this effort hinges on the power to bridge the gap between complexity and comprehension. This is especially true when talking concerning the difficult topics present in data science, for instance deep learning algorithms, Bayesian inference, and dimensionality reduction (to call a couple of).
This text is the primary in a series on preparing material for presentations, by which I would like to run through the strategies and techniques I take advantage of when creating presentations to rework high-level topics into easy summaries. This series will walk through the assorted methods I take advantage of when considering easy methods to structure my presentations to be clear, concise, and effective.
The recommendation I give on this series will be broken down into 3 easy tenets, which I actually have laid out below:
- Know your audience
- Guide your audience
- Anticipate and prepare for responses
All of those points are interconnected and interdependent — a successful presentation will incorporate all three, allowing the audience to understand your key message, take away information relevant to them, and have their queries and concerns answered in a satisfactory manner. With these 3 key guidelines, you may be assured of success in technical presentations.
In this text I’ll deal with the primary guideline — easy methods to gain a sufficient understanding of your audience to give you the option to gauge their key concerns, base level of understanding on the subject at hand, and expectations for the presentation you’re about to provide. This level of preparation is crucial when coping with any large audience composed of various stakeholders with…