About the Waseda University Data Science Competition
Since 2019, Center for Data Science has been hosting the Waseda University Data Science Competition (hereinafter referred to as the DS Competition) every year in collaboration with each academic faculties (organizations including undergraduate and graduate schools). Any student at Waseda University, including graduate students, can participate in the DS Competition. Participants form teams of 2-4 people and spend several months analyzing and summarizing a given theme each year, which they then present at a report session.
In the first DS competition, we made predictions for the House of Councillors election. Rather than a hypothetical election, we used a real election as our subject, and predicted the results of candidates based on data. Although the objective was clear - to predict the results - we were free to use any data we wanted. Participating teams used a variety of data they had devised themselves, such as focusing on party approval ratings or photos of candidates.
In the second competition, we used marketing data provided by ADK Marketing Solutions Inc. This was actual data used by companies. This time, the data was given to the participants, and the format of the competition was different from the first competition in that the participants were given the opportunity to set their own analysis themes.
DS Competition as a place of practice
The DS Competition has a different theme every year, but it has the unique feature of using real data for analysis. It can be said to be a place to put into practice what you have learned in class. Whether it is sports or music, I think that having a real performance as a goal is what makes you work hard at your regular practice. On the other hand, some people may want to test their abilities and show off their results somewhere, since they have practiced so hard.
The same goes for studying data science. If everyday study is practice, then the DS competition is one of the places where you can really put your knowledge into practice. Many Waseda students have participated in the DS competition so far.
As mentioned earlier, the DS Competition uses real data. Since it is different from the processed data often used in classes, you may not get the analysis results you want, or you may not be able to perform the analysis well. There are many difficulties, but the joy of overcoming them is great. In particular, since you participate in a team, solving problems using real data with your peers is a great experience.
Characteristics of Waseda's competitions
When you hear the term DS Competition, many people may have the impression that many students from the Faculty of Science and Engineering participate. In fact, if you look at the breakdown of participants in the fourth DS Competition held in 2022, students from the Faculty of Science and Engineering and students majoring in Science and Engineering (graduate school) made up about 20% in total. You can see that many students from faculties and graduate schools in the so-called liberal arts fields participate. This is related to another characteristic of Waseda's DS Competition.
Another feature of Waseda's DS Competition is that data analysis is conducted based on knowledge learned at various undergraduate and graduate schools. I would like to explain this in detail using the 4th DS Competition held in 2022 as an example. In the 4th DS Competition, statistically processed finance-related data that did not contain personal information provided by Mizuho Bank was used. Participating teams were free to decide on an analysis theme for this finance-related data, and knowledge learned at undergraduate and graduate schools was used when deciding on this analysis theme.
For example, a team that studied disaster prevention at undergraduate and graduate school dealt with a theme related to disaster prevention. Similarly, a team that studied public policy set a theme based on that and conducted an analysis. There were also teams that used their knowledge of algorithms to come up with their own analysis method. In this way, participating students are making use of what they learned at undergraduate and graduate schools in the DS competition. In data analysis, it is very important to set the purpose and analytical method. In order to decide on these things, deep knowledge and consideration of the problem are required, and this is where the specialized knowledge learned at undergraduate and graduate schools comes in handy.
Invitation to the competition
In the Waseda DS Competition, which has the above characteristics, all presentations receive feedback from a panel of judges consisting of faculty and business people. In particular, comments from the business perspective are not something you can get in regular classes. There are both warm and harsh comments, but it will be a valuable experience that will surely be useful in the future.
After enrolling at Waseda University, please consider participating in the DS Competition.
On the other hand, I think there are many people who are interested but find it difficult to participate. Some may hesitate to participate because they have just started learning data science or do not understand advanced analysis. For such students, we recommend that they first participate as spectators. Any student at our university can watch. Of course, there are teams that use mathematically advanced analytical methods, but there are also teams that derive interesting results using basic analytical methods learned in class. You will surely be greatly inspired.
