Garrick Chu was living in a city without convenient in-person data science bootcamps, so he decided to explore online courses, eventually finding the perfect match in Springboard’s Data Science Career Track.
The flexibility of the course was a major draw, but online learning also presented a challenge: a lack of offline connections. So Garrick took matters into his own hands, setting up a Slack channel to foster real-time conversations with fellow learners and to coordinate in-person events to build relationships.
When Springboard began establishing official offline events for students and alumni, Garrick came onboard as the first head of community for the San Francisco Bay Area.
“While I was going through the program, I created my own mini-community of other students and found so much benefit from having a close network to ask questions, get help, share ideas and local events,” Garrick said. “I believe the community element positively augmented my learning and set me up for success. It seemed only natural to scale up and be inclusive of students and alumni (compared to just one or two cohorts) in order to create the same opportunities to learn from peers, make life-long friendships, and support one another.”
Before beginning the Data Science Career Track, Garrick was a senior data analyst in the investment management industry. He was interested in exploring more efficient and accurate methods of deriving intelligence and insights, as well as moving away from traditional finance roles, where opportunities to grow and apply advanced analytics were increasingly scarce, he said.
Beyond the flexibility of online learning, Garrick was attracted to Springboard because of the human support, most notably the one-on-one mentorship. “My mentor was attentive, extremely knowledgeable, and compassionate to my needs as someone entering the field for the first time and from a non-technical background,” he said.
Garrick also welcomed the opportunity to develop capstone projects that he was passionate about.
His first was an analysis of bitcoin (predicting price and economic crash) and his second focused on identifying dog breeds from images using convolutional neural networks.
Garrick’s mentor, Paul, praised his high-quality work, noting that he “stretched” in his initial learning, “went the extra mile” in validating his work, and showed “creativity and drive” throughout the process.
Garrick currently spends his days as a contract data engineer at Facebook. As a member of the applied machine learning organization’s speech team, he supports efforts to implement and improve products leveraging natural language processing and understanding.
