STEM Student Spotlight: Tobiloba Omooba, York University
Welcome to our STEM Student Spotlight series, where we showcase the remarkable initiatives and achievements led by STEM students in Canada. Our mission is to empower and inspire the next generation of engineers and innovators by celebrating the achievements of student leaders. In today’s spotlight, we are featuring the experience of Tobiloba Omooba, a student attending York University!
In this program, Tobiloba focused on Data Science and Machine Learning (ML), where they learned about applying advanced data visualization techniques using Python libraries. Tobiloba also concentrated on creating informative and visually appealing data visualizations. Tobiloba learned different skills involving enhancing data visualization — such as data manipulation and filtering.
“I learned how to manipulate data that then alters the displayed data [and used] my understanding of the grid functions to manipulate how the graphs are displayed. This project taught me how to make the viewing experience of my displayed data more natural and comfortable.”
Tobiloba acquired skills in using different tools and interactivity methods to enhance data visualization, expanding their knowledge in adding tools and interactivity methods.
“This [project] taught me more great ways to make visualizations interactive.”
Tobiloba also had the opportunity to learn about JSON and how to work with data in this format.
“[The projects] showed me ways to select specific data from JSON and use it in the visualization process.”
“I make a request for a different type of data, then use JSON to produce it. I learn how to filter through the data set and use JSON to request and process the specified data. It helped me better understand how JSON works and the ways to use it on my own.”
These insights reflect Tobiloba’s hands-on experience with JSON and its application in data visualization projects.
Tobiloba also delved into machine learning and clustering, gaining knowledge about different types of machine learning and how each may be used in various contexts. They also learned how K-Means clustering works.
“I learned the different types of machine learning and how each may be used in different contexts. I also learned how K-Means clustering works.”
Finally, Tobiloba shared thoughts on how these projects helped build confidence in manipulating code and solving problems, emphasizing the importance of this aspect of the course in gaining coding proficiency.
“This aspect of the course helped me gain confidence in changing code and problem-solving.”
Reflecting on the program, Tobiloba explained how the skills acquired will benefit their studies in the field of Criminology.
“I am in the Criminology field, and this kind of code can help in statistical documentation/presentation. Being able to provide an interactive and visually appealing view of data helps in so many ways. This also helps in finding ways to access different forms of data that may need to be used to connect to government-owned databases.”
Tobiloba concluded by emphasizing the broader impact of opportunities like these for young adults, providing space for technological literacy and a toolbox for their respective fields.
“Having the opportunity, as a young adult, to learn how to code is incredibly beneficial. For me and those my age, having opportunities like these gives space for technological literacy in a time when technology is becoming more prominent in all work fields. They also give us the toolbox that we can take to our respective fields, providing better chances of acquiring jobs.”
This encapsulates Tobiloba’s journey, showcasing how they’ve harnessed data science and machine learning skills to contribute to their field and beyond. Stay tuned for more inspiring stories in our STEM Student Spotlight series!
