It's been almost years since I began pursuing my Bachelor's in Information Technology at York University, and I'm expected to graduate in
years and months.
The unique IT BComm program at York gave me a great opportunity to expand my business knowledge alongside essential IT and computer science courses.
However, as someone passionate about data, I’ve also expanded my knowledge in data science and data analysis to combine what I’ve learned from IT and commerce with more advanced statistical models, machine learning and deep learning to extract actionable insights from raw data.
I believe the way we think, act, and solve daily problems generates meaningful footprints in the mess. These everyday choices, when studied and analyzed, form patterns that reflect how we live and adapt.
The emerging patterns depend on two factors: internal factors related to conscious and unconscious human behaviours, and external factors, including the choices presented to us.
When patterns are extracted, they give us a better understanding of what the optimal choice architecture should be and what humans’ responses are likely to be.
That’s the beauty of data science. It’s not just about numbers; it’s about using data to better understand human nature, to help those who set up the available choices and those who make them.
Awarded to the highest-achieving students in the Faculty of Liberal Arts and Professional Studies.
Awarded to undergraduate students with outstanding academic results.
Core business courses cover financial accounting, economics, and management. Key classes include Financial Accounting, Business, Microeconomics, and Macroeconomics, focusing on financial reporting, economic principles, and business operations.
Technical courses focus on programming, data analysis, and information systems. Highlights include Object Oriented Programming, Analytical Programming, and Information and Organizations, emphasizing software development, data modeling, and IT’s role in business.
Developed the current version of bio website using HTML, CSS, and JavaScript.
Developed a Python-based system to process and analyze real-time financial data, focusing on the microstructure interactions.
Developed a classification tree model in MATLAB to predict wheat seed varieties using kernel geometry, handling data analysis, cleaning, preprocessing, and machine learning to enhance accuracy.
Analyzed and cleaned sales and cost data to evaluate financial performance, create pivot tables, perform calculations, and generate insights on retained earnings, gross profit, and regional/product line trends.