Learning programming languages
Starting October, we stepped into a regular term to learn analytical tools and techniques in order to gain solid fundamental knowledge and to explore the marginal uses of management analytics. Focusing on big-data analysis, we became proficient with two of the most popular programming languages for data: R and Python. We used them to establish models and tried some machine learning techniques on clustering, classification and prediction. We used essential basic tools such as Excel and Tableau to get a quick understanding of the data through simple calculation and visualization. Additionally, SAS and SQL were useful to effectively manage the dataset and generate the derived factors as key indicators for data-based decision making.
In addition to coursework, we had a lot of opportunities to learn through workshops, such as Creating a Professional Online Presence via LinkedIn, Effective Communication & Workplace Professionalism, etc. We learned insightful ideas from professionals of over 10 companies in the first MMA Industry Reception event.
Finhub, the Data & Analytics Lab, and the Self-Development Lab
Rotman has interesting extracurricular activities for anyone interested in learning more after class. FinHub, the Data & Analytics Lab and the Self-Development Lab offered us help in improving our technical and soft skills. We also had the opportunity to attend Rotman and club events, allowing us to learn and meet new people. As a graduate research assistant, I was able to help a Rotman professor research the real-estate market of the Greater Toronto Region.
Yes, I still have a lot to learn as an analyst, but the MMA program has enormously improved my skillset. What counts is that Rotman is there to support me on whatever I want to do, so that I can become whoever I want to be.
The Master of Management Analytics is designed to give students the advanced data management, analytics and communication skills needed to become an analytics professional.