I’m very proud of it and very scared at the same time – next week I’m going to give a lecture for the first time. The lecture is a part of the Advanced Pattern Recognition course for PhD students and my own lecture will be about the dissimilarity representation and multiple instance learning – topics I should be familiar with 🙂
Right now I’m spending a lot of time in preparing for the lecture. I’m guessing that 30 hours will be a good estimate for how much time I will spend in total. Right now I will try to explain my progress and how many of these hours I am spending where.
I spent an hour or two searching for information on how to prepare your first lecture. I found helpful tips here and here. The main messages for me is: pick a few core topics and explain them well, rather than skipping over all the possibilities.
With that in mind, I started thinking about the actual content. Although the topic is very related to what I’m doing in my PhD, I want to talk more about the general techniques rather than the specific parts that I am doing. Therefore, I could not use the typical structure of my conference presentations. I started out with a mind map (or at least, a bunch of words with arrows between them) of both topics to see what exactly I would need to cover. In my head, I was already preparing the connections between different topics and thinking of nice examples, so in the end, this process costed me about 2 hours.
Then I looked at which topics I feel comfortable explaining (most related to my own research), and which topics I don’t have experience with / haven’t tried explaining to others. For instance, with a dissimilarity representation, there are two main possibilities to improve upon nearest neighbor classification: embedding the dissimilarities, or training a classifier in the dissimilarity space. In my research, I only do the latter, and although I understand the concept behind embedding, I don’t feel as comfortable with it. Yesterday I spent most of the day reading about it and at the same time trying to revise last year’s slides so I could actually use them in my own explanation. This turned out very time-intensive (+/- 7 hours), but also very helpful.
I still need to prepare the slides for my more “comfortable” topics, revise the whole story and practice. I’m not really into practicing the whole thing before presentations, but here I’m especially worried about the timing, because I have never talked for 1.5 hours before. Also, as my lecture is only on the fourth day of the course, I plan to attend the other lectures and see how the experienced people are doing it. So, probably I will revise a few things after that as well.
The last, somewhat more optional part, is to go over the exercises that “go” with my lecture. Because the content and slides that I’m using changed from the previous years, I have to check whether the exercises are still useful, and update them if necessary. I’m actually very looking forward to this, but I’m afraid I won’t have the time to come up with my own exercises, test the code, etc, so I might have to leave that for next time 🙂
To be continued!