In trying to enter the Data Science field, I came to the conclusion that the bootcamp route was my goldilocks option, somewhere between self-teaching (low cost/commitment) and a master’s degree (high cost/commitment). If you come to the same conclusion, I couldn't imagine a better bootcamp experience than NYCDSA. Curriculum: Comprehensive and (more importantly) realistic. NYCDSA focuses on building a strong DS foundation. So instead of becoming a superficial expert on the most complicated buzz-word models, you become a solid expert on DS foundations with experience applying those foundations to projects. This turned out to be hugely important, as many of my DS job interviews focused on fundamental ML concepts, and I could give in-depth answers. Faculty: Top notch. The instructors are experts with years of experience, and they're skilled at breaking down complex topics. This allows them to work with both beginners and advanced students. Further, they're incredibly supportive, and always available to answer questions and help with projects. For me, that alone made the investment worth it - to have experts available to help work through your questions, instead of banging your head against the wall trying to figure it out yourself. Job Support: The Covid job market is tough, but the NYCDSA team does what they can to help. They made introductions/recommendations, hosted events, helped prep for interviews, and met with me many times for career services. Of course, at the end of the day, you’ve got to get the job… but they’re on your side every step of the way. The only issue I have with the bootcamp route is that going in, there’s often this “do a bootcamp, get a job” misconception. More realistically, it’s “do a bootcamp, then study for a few months independently, then commit yourself to interview prep and job hunting, then get a job.” As long as you’re ready for the work, the bootcamp can be a perfect first step. For me, NYCDSA and the self-led study that followed provided the very necessary foundation of my DS career.