Summer 2022
Instructor Q&A: Jesus Salcedo
Data Analytics
“The way I teach is through repetition and capitalizing on the
ways that students learn (visual, auditory, reading/writing,
and kinesthetic). I also remove all the unnecessary fluff that
creates confusion or the illusion that concepts are difficult.”
Why did you decide to become an instructor?
When I obtained my degree in Psychometrics, I knew that my career would require three skills: analyzing data, reporting research findings, and presenting results. Of these three skills, my presentation skills were by far the weakest, so I decided to look for jobs that would force me to improve my presentation/teaching skills.
My first job out of grad school was for the statistical software company SPSS. I worked as an Education Consultant and traveled around the country, teaching clients how to analyze data using SPSS products. It was through this experience that I discovered how much I love teaching and presenting information.
What’s your favorite lesson to teach and why?
I know we use computers to analyze data, and we will never again analyze data by hand. Yet I believe it is vital that students understand how algorithms work so that they can comprehend the intricacies behind predictions and how algorithms do their “magic.” Understanding the inner workings of algorithms also provides insights into why models breakdown, as well as identifying model limitations.
What’s unique about your teaching style?
My dad was a chef, and he taught me that there are no bad foods, only bad cooks. For me, there are no difficult concepts, only disorganized teachers. As part of my education, I took many courses and seminars on how to teach. I followed these principles for the first part of my teaching career. Around 2006, I completely changed my teaching style because I knew I could do better.
As a student, I was a different type of learner that took what an instructor taught, digested it, and then translated it back to myself in a way that was meaningful and useful — I try to do that for my students. The way I teach is through repetition and capitalizing on the ways that students learn (visual, auditory, reading/writing, and kinesthetic). I also remove all the unnecessary fluff that creates confusion or the illusion that concepts are difficult.
What do you find most rewarding about being an instructor?
When I first started teaching, I labeled myself a “guide” for the course. Today I still introduce myself as a guide. To me, the challenge of teaching is figuring out how to share what I’ve learned through my experiences so that others can benefit. I think we all learn from each other, and we all have unique perspectives. In every course I’ve taught, I’ve learned something new or pondered something from a different angle based on students’ insights. I love learning from students.
What advice would you give
to anyone interested in pursuing
a career in data analytics?
Most people that go into data analytics focus on the sexy aspects of the profession, namely the algorithms. Although they are fun, the real creative and challenging aspect of data analysis lies in data preparation and manipulation. Here you can create new variables, answer important questions, and reconceptualize the meaning behind the data. Spending as much time as possible on how you can rethink variables so that you can extract that extra little bit of information is extremely valuable.
Also I would say that dissecting the results and predictions from models to determine where they are most useful, where they breakdown, how they can be improved, and for whom they work best, is really, really imperative. I find that the seemingly insignificant tasks tend to be the most important.
Learn more about the Data Science Certificate Program.