Diana Xie had just earned a master’s degree in neuroscience from an Ivy League university and was on the Ph.D. track when she decided that she wanted to change careers.

Although her thesis topic was not related to data science, she found herself picking up skills like data wrangling, visualizations, and presentations. She realized she loved coding and data analysis.

diana xie“Much of the work I did set the groundwork for entering a data science bootcamp,” she said.

But which one was right for her?

I researched lots of review sites,” Diana said, and she ultimately chose Springboard’s Data Science Career Track “because of the flexibility and excellent student reviews. I liked that there was a human factor, which was readily available advisers and coaches, a weekly session with my mentor, and lots of other avenues to reach out to another person.”

That human element was particularly important as she adapted to the self-paced structure of the course.

“Deadlines push me to become more productive, and the self-paced curriculum didn’t really have any. That was a challenge,” she said. “It helped that I verbalized my goals to my mentor and felt somewhat more accountable as a result.”

The weekly mentor calls were a highlight, she said. “Even though the sessions were 30 minutes each, I felt supported and helped along the many months I was working through the bootcamp.”

One of the things she liked most about the Springboard experience was that she was learning something new every day. And what she was learning was directly applicable to her career goal.

As part of the course’s hands-on learning, Diana built a recommendation engine of music journalists for consumers to follow, based on their Spotify music preferences.

“I picked this project because it combined my interest in music and quantifying subjectivity in music journalism, while incorporating many incredibly useful techniques and ML methods I had recently learned in the course,” she said.

Diana went on to turn that project into a Flask app that you can check out here.

After completing the course, Diana got a job as a machine learning engineer for a health information and clinical research company.

“I’m still learning, expanding my skills, and now getting industry experience,” she said.

Diana’s advice for anyone interested in online learning:

  • Consider what motivates you and your style of learning, especially with the self-paced nature of this course.
  • Thoroughly prepare for the weekly mentor calls to get the most out of the experience.
  • Take advantage of the Springboard-curated resources, but also go beyond them as you network and prepare for interviews—Google interview questions and how to prepare, etc.

This Springboard alum transitioned to a data science career and you can too. Learn more about the Data Science Career Track. It’s a flexible, mentor-led course with a job guarantee.