How to select a data science bootcamp? Tips?
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I work for online learning startup [1]. Here are some pointers:
1. Lambda School has some great reviews, high % of students employed and great community. It's very intense though (9mo full-time or 18mo part-time).
2. Try reading some of the reviews on review sites yourself and see if it sounds objective. I find major part of reviews to be helpful, so don't dismiss a big data source without validating its quality.
3. Reddit Data Science communities have a lot of detailed reviews and advice on bootcamps. I recommend looking through some, although Reddit users are a bit biased towards heroic self-learning.
If you elaborate a bit why you want to go to DS bootcamp, I could give you a more specific recommendation :)
[1]: practicum.yandex.com
If you elaborate a bit why you want to go to DS bootcamp, I could give you a more specific recommendation :)
[1]: practicum.yandex.com
Hey, what are your thoughts on going through the DS track at Yandex with the goal of landing a data scientist position in a competitive job market like San Francisco? Is this a realistic goal?
I have a bachelor's degree in a non-quantitative study. I recognize that job descriptions for data science, more often than not, stress their minimum requirements to be a Master's degree (PhD preferred) in a quantitative discipline like physics, math, statistics, etc. I feel this to be much more strictly enforced than compared to software engineering positions where you're much more likely to come across self-taught devs. I work on the product side and the data scientist attached to my team holds her M.S. in Statistics so that seems to hold up from everything I've observed. Essentially, I don't want to rush into studying and learning statistics/data science if the effort is futile or just not likely from the beginning.
Also does the job guarantee apply to students in the US? Or is that for Russian students? Does your program have any US employers as hiring partners?
I have a bachelor's degree in a non-quantitative study. I recognize that job descriptions for data science, more often than not, stress their minimum requirements to be a Master's degree (PhD preferred) in a quantitative discipline like physics, math, statistics, etc. I feel this to be much more strictly enforced than compared to software engineering positions where you're much more likely to come across self-taught devs. I work on the product side and the data scientist attached to my team holds her M.S. in Statistics so that seems to hold up from everything I've observed. Essentially, I don't want to rush into studying and learning statistics/data science if the effort is futile or just not likely from the beginning.
Also does the job guarantee apply to students in the US? Or is that for Russian students? Does your program have any US employers as hiring partners?
Also, do you know of anyone who has successfully full-time self-studied for a few months to obtain a entry-level position in the field (or a related title such as data analyst/ data engineer)? If so, it would be great to hear about their approach.