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	Reviewer Name	Review Body
	Jhonsen Djajamuliadi	This is my review of METIS Data Science (DS) Bootcamp experience in Seattle, winter session, Jan-Mar 2019. I really enjoyed my bootcamp experience! I was pretty much coding daily, learning new concepts, and implementing machine learning (ML) algorithms into various projects pertaining to my interests. It was a blast!!! Some things that I really enjoyed: (1) The format emphasizes creating design-to-product pipelines for data science projects. Having done 4 independent projects, I felt ready to tackle new problems, (2) my instructors, Chad and Cliff, provided a good mix of academic and pragmatic approaches to learning data science and completing DS projects, (3) after completing the bootcamp and reviewing class material for a couple weeks, I felt ready for interviews, (4) we practiced pair programming on a daily basis, (5) I felt a sense of camaraderie with my peers. (6) in terms of career support, our counselor (Marybeth) was very helpful. She helped me with everything I needed, from resume/cover letter review, job hunting strategy, connecting with other recruiters, etc. Some things to improve (perhaps only for my cohort): (1) having code reviews or detailed project reviews with students would help I think, (3) I would’ve wanted to have more whiteboarding practice (this one didnt come up until the end, during mock interviews), (3) learning more DS use cases for various business problems would’ve really helped. Advise for future students: * The bootcamp provides sufficient (elementary) overview of fundamental machine learning algorithms, at least enough for entry-level data jobs. However, I’d advise future students to also spend some time learning from external resources (books, blogs, etc.) to get a deeper understanding of each concept. * If you intend to join the bootcamp, look up the curriculum ahead of time and think about what kinds of projects you might want to tackle based on your interests. * Unless you already have previous programming experience, it would be good to learn python programming and other CS fundamentals yourself. * Just keep in mind that career transitioning is not as easy as you might imagine. If you are trying/planning to do it, I think your quickest way to getting a DS role is to leverage the domain knowledge you have from your previous career and then implement DS/ML into your field. Also, I learned that becoming a data scientist is more like a marathon, rather than a sprint.

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