|From:||San Francisco, USA|
Forget other online courses. With amazing mentors and a curriculum that doesn’t waste your time, Springboard is the serious step into Data Science that you’ve been looking for.
I’ve always had questions about how things work. I started my career as a reporter for the Wall Street Journal, making a living out of asking questions. More recently, I worked on marketing at IFTTT (If This Then That), a technology startup in San Francisco, where I analyzed user acquisition and retention – asking why users wanted our products and how to get them to engage more deeply with them.
The questions kept driving me to our data. We had a vast store of it, and I knew the answers about our users were in there. But I didn’t know how to work with it. I felt like a traveler in a foreign land, who has many questions but doesn’t speak the language well enough to ask them.
Before Springboard, I’d mostly tried learning things on my own. I must have signed up for Coursera’s “Machine Learning” course nearly a dozen times and never made it further than the fourth week. So as I considered ways to learn how to work with data, I knew that I’d need more than purely self-motivated courses.
I signed up for Springboard, half-expecting that I’ll probably ask for a refund within a couple weeks. I wasn’t completely convinced that it was worth it. Then I had the first meeting with my mentor Soups. I was a little nervous before – it was the first time I’d spoken to a real Data Scientist about what I wanted, and I started wondering what I was doing in a land of PhD’s. But my mentor Soups was nothing like what I expected. He was friendly, excited, and very, very encouraging of what I was trying to do. He made me feel like I could really do this thing.
I’m still in touch with my mentor today. In fact, he introduced me to the company where I’m working now!
From the beginning, Soups suggested that I put what I was learning to use on the dataset that I wanted to explore at work. It was a great idea, and I started seeing the value of Springboard almost immediately. Within the first few weeks of starting to learn R, I was running analyses that dazzled my team at work. They were impressed that I had been able to learn so quickly.
The most valuable part of Springboard was the regular weekly call. Having something on my calendar every week made sure I didn’t slack. I knew what I got out of it was entirely up to me, so I made sure I had questions to ask and work to show my mentor when we talked.
Working with a mentor also made sure that I never got stuck. When I was trying to build a scoring algorithm at work to measure different types of user engagement, I couldn’t figure out how to handle the fact that some things had much more data than others. The old doubts started creeping in – “I don’t have a PhD, I don’t know what I’m doing, should I even be trying this stuff…” I was really disheartened. But in our next call, Soups told me a couple things to look up that solved my problems! This wasn’t the only time. He did it over and over again, with just a couple right words to get me over many humps that I wouldn’t have managed on my own.
After Springboard, I built FogOrNot.com, a machine learning powered map that predicts the San Francisco fog. I built and tested my algorithm in R, and I used linear regression on data from 130+ personal weather stations to create my predictions.
That project helped me get interest from companies with open data positions. My mentor introduced me to reddit. I love the community.
I’m grateful that Springboard was the beginning of my data science journey.
Before : Business Analyst
After : Data Analytics and Data Pipeline Consultant
"I left academia almost two years ago, and I have no regrets."
Before : Instructor, MIT
After : Data Scientist, Wayfair
Springboard is a wonderful stepping stone to get to your goals in Data Science.
Before : Research Officer, British Columbia Government
After : Data Scientist, Boeing