The beginning of November marked the end of our intro term in the MMA program. It was then followed by the most exciting part of November - Practicum project onboarding and the kickoff of our fall term. The second week of November was our dedicated Practicum intensive week where we got to meet with our project hosts and discussed the business problem of the project. After the Practicum intensive week, it was the actual fall academic term.
During the last day of the practicum intensive week, our academic director Dmitry and professor Baron organized a Datathon event for all the Practicum project groups. The main objective of this Datathon competition was to expose us to all the different parts of designing and executing an analytical project. Designing and executing a project with a clearly defined managerial and analytical question is very critical to a data scientist.
The competition was broken down into two parts.
The first part was an individual component where we were asked to define business and analytical objectives, design a modeling and data plan and propose one/multiple project designs.
During the second stage of the project, each Practicum group was given full access to the “raw” data sources at 9 am on the day of the Datathon. We had 6 hours to complete the analysis and prepare a maximum of 20 slides presentation with charts/visualizations to the judges to present our key findings that focus on the managerial insights.
This was an intense day where our team had to act quickly and tune models to find out what factors truly impacted the outcome.
Started Course delivery mode is a bit different this year because of the pandemic. Even though all our classes are taught online, our amazing professors organized the course structure well. There are four core courses in the fall term which is also called tools term! People might be wondering why it is called a tools term. That’s because during the tools term, we will have the opportunity to learn various data analytics software for data analytics, such as Python, SQL, and R. The four courses are: Big Data Analytics, Modelling Tools for Predictive Analytics, Tools for Probabilities Models and Prescriptive Analytics, and Structuring and visualization data for analytics.
I’m personally most excited about the Big Data Analytics course where I get to learn various machine learning algorithms while practicing my Python skills. Developing my technical skills was one of my main reasons I chose Rotman MMA!
Workshop During the month of November, one of the most favorite career workshops hosted by Rotman that I attended was “How to Prepare for Technical Interview Workshop Presented by Prof. Keng.” Prof. Keng explained some common technical and case interview questions, such as ML framework and data cleansing which I found interesting and useful.
November was a busy but rewarding month and I am very looking forward to continuing the journey with all my amazing classmates and professors！
The Master of Management Analytics is designed to give students the advanced data management, analytics, and communication skills needed to become an analytics professional.