Each week we spotlight an OMSCS TA, so you can get to know who's behind the screen. Here are four questions for Fermin Ordaz, who TAs CS 7641: Machine Learning.
What do you do professionally?
I work as a platform architect at Ellie Mae, building a big data and machine learning platform for the mortgage industry. I'm glad to be able to use many of the things I learned in the program, such as Apache Spark + Hadoop (Big Data for Health Informatics) and machine learning workﬂows (Machine Learning).
Why do you TA for OMSCS?
First, having to explain things to other students is an excellent way to reﬁne your understanding. Second, grading homework forces you to see different experiment results, analysis, and perspectives, which allows you to revisit the concepts from different angles. Third, the TAs are a crucial part of the program, and I'm especially grateful for their support and help, and I felt like making my small contribution.
What's your advice for future students in OMSCS?
- Manage your time, switch off from "work" into "student" mode on a regular basis.
- Pace yourself, maximize for learning, and don't rush it.
- Create habits and rhythm (when/where/how to study).
- Start projects as early as possible, start small, and iterate.
- When choosing courses, consider these categories: novelty courses, ﬁll in your gaps, refresh your foundation, general interest.
What's your favorite memory from your time in or working with OMSCS so far?
After ﬁnishing the ﬁnal project for Big Data for Healthcare, we realized we've done the whole ML workﬂow from data preparation, feature engineering, model training, tuning, and analysis. We felt like data scientists that could tackle any other project.