Springboard gets it! 

I had an extremely great experience with the Data Scientist career track and put had multiple jobs offers before I completed my curriculum with Springboard. The curriculum is complete and takes a significant amount of focus and coding work. The online format is very convenient and the help sessions along with the mentors are world-class. I particularly appreciated the weekly calls with my mentor who was/is an industry specialist in Data Science. It was beneficial having a mentor to seek feedback on exercises, questions about the curriculum, and or about insight about the role of Data Science in industry. The calls with career coaches were also constructive to guide in job search efforts, including mock interviews. 

One of the things that stuck out to me was the two comprehensive capstone projects. I thought these were important in solidifying your work and expressing what we learned to more significant audiences. I utilized my capstone projects to answer real-world problems at work that were met with much praise and helped to solve and or better under pressing business problems!

I highly recommend this impactful bootcamp!

The mentor sessions were great and very flexible for times I was unavailable. My mentor was very understanding and super helpful whenever I had questions outside of our mentor calls. The curriculum was also easy to understand and helpful with both videos and reading material. I'd say the only con for me was just time-management. I was working full-time as a UI Designer and studying this UX course, which definitely did get hectic and limited my studying time. When trying to manage the work-life balance, organizing your time and sticking to a goal to finish the course is so important--especially for online courses! 

I had a wonderful experience with Springboard. The 1-on-1 mentor experience truly helped me so much to be able to talk to a person that was in the field and pick their knowledge base. I especially think that the capstone projects made the program special. I was able to gain such good hands-on experience through these projects.

I had a good experience learning the Data Scientist job with Springboard. The curriculum is very complete and takes a lot of work. The online format is very convenient. I particularly appreciated the weekly calls with a mentor in Data Science. It was really helpful for feedbacks on exercises, for questions about the curriculum or about the job but also to guide us in the development of 2 capstones projects. The calls with career coaches was also very helpful to guide us in our job search, including mock interviews. I haven't found a job yet but based on my experience so far, I recommend this bootcamp. 

I used it as an entry into the analytics career path.  Great mentors and curriculum.  Career coaches could use some work, though. 

Overall great Curriculum and Mentorship experience. My Mentor guided me through all the challenging projects very clearly.

Curriculum was industry based and quiet challenging.

Student Advising was very freindly and responsive.

I had a great experience learning at Springboard.

The course curriculum was very advanced. The best part about the course was the mentor calls. I worked with 2 mentors (Branco Kovac and Vivek Kumar). Both of them have helped me a lot with my curriculum and capstone project. Branco helped me choose my topic for the Capstone project and Vivek helped with with the further progress of curriculum and capsyone project.

During the mentor call one can discuss any doubts regarding the curriculum and the capstone project. The mentors are readily available to help and assist.

I'm also happy with the student advising team. They are always available to respond to all the queries that we have.

Honestly, I had a great experience in Springboard's UX career track. Going into it, I was nervous because the program was at an early stage and didn't have any data on the success rate of alumni landing jobs. But I am glad I did it and it was a great experience!

The mentorship and Industry Design Project are the greatest parts of the program! My mentor really helped me to grow as a UX designer and IDP gave me an opportunity to pair with a real company and work on a real-world project. 

I am still nervous because the true test is landing a UX job! I hope it will be all worth it in the end ... 

Springboard was honestly a great experience. I didn't expect it to be as in depth as it was and I feel like the money was definitely worth it. Springboard always helped me when I needed it and my mentor was a complete angel. The mentor suppot makes the program a million times better. I'd say definitely take the course if youre interested, you wont regret it.

I'm currently enrolled in the UX Career Track program and I love it. Going into it I wasn't sure what to expect, but so far, I'm very satisfied with the skills taught throughout the course. The course has a capstone project that sits as the backbone of the overall curriculum. With each unit you complete, you add to your capstone project. This style gives you an immediate opportunity to apply the skills you learned during the unit and solidify the new knowledge. Even though I'm only partially through the course, I've already been able to apply lots of the skills and tools I'm learning to my current. For me, it's been a really effective means of growing my skillset.

Tip: make sure you're making progress each month. Like many, I probably procrastinated longer than I should have and have been left cramming a bit towards the later months. The staff has been very accommodating with the course freezes though.

I enrolled in Springboard's UX Career Track in April 2019. I was able to finish in eight months and still get the job guarantee. What I liked the most was the one on one weekly mentor calls and the community on Slack. With those tools I was able to have any of my questions answered. Springboard also really prepares you to work in the industry, since in order to be eligible for the job guarantee, you need to pass a behavioral mock interview and a portfolio walkthrough, which are the two types of interviews you have to go through when applying for UX jobs. I am now excited to start my job search and look forward to keeping in touch with everyone on the Slack community.

I am rewriting my review as it has been 6 months and still no job. The problem is that the career coaches are always booked up and you cant book a time that works for you. I booked 2 career coach calls within a 2 week period and canceled one of them because I had one booked already. Sometimes the career coach has to reschedule, thats why I did 2 schedules. Not a month later the school emails me that I am no longer eligble for the money back guarantee because I canceled one of my 2 calls. The problem with this Bootcamp school is they dont have enough resources for you and your set up for failure. Also you should try and stick to one career coach as multiple people have different ideas and it messes you up. Like, one said to do this on your resume and the other said to do this. Stick with one that you like. 

This course gives an extremely broad foundation for getting into ML/AI/DS careers. The weekly mentoring is perhaps the best part, and having weekly meetings with an experienced member in the field pays huge dividends, especially as you find yourself changing jobs or feeling like some impostor to the field.
You will become extremely knowledge about the math and proof of concept stage to getting machine learning-based projects off the ground. I think this is helpful, but could improve in many ways for 2020.
1. More emphasis on deploying systems and system design. The curriculum delves very little into cloud services (AWS, GCP, Azure), preferring a more open-source based model. I think this is good in general, but machine learning engineers are inevitably going to be using one of these services in their careers. The course gives you credits for AWS, but little attention is paid in the curriculum to its use cases. Given all the time spent in the course, reading other paid material like "Grokking the System Design Interview" shouldn't be necessary if the curriculum is better formed. 
2. Techniques other than machine learning. It's kind of ironic to ask a course like this to do something other than ML, but knowing when ML is useful and when other techniques are appropriate (from heuristics to Deep RL) does not really get much attention.
3. More work on data collection. It would be much more helpful if the course explained more further up the pipeline on how to collect, ETL, and store data to make ML possible. It might be an old school way of thinking, but many companies have older data  systems that need to be understood in order to get to the interesting ML portions.

This course covers a lot of info in a very detailed manner. You get a wide variety of topics, and you will get a nitty-gritty view of it, too. I appreciate the mentor they give you to get you through it. I had a very helpful one that I met with every week and was very good about answering my questions. You even get some career help, and you can't graduate from the course unless you do some practice interviews. This is were my negative comes in. It was very difficult to even schedule these interviews (and other career advisor meetings that are separate from the mentor ones). The slots were few and filled very quickly. For one practice interview, the person that I was supposed to do it with didn't even show up, so I had to reschedule that one. That was frustrating to me and a mar on an otherwise good course. Other than that, I would recommend it.

Springboard did a really good job in putting together all the coursework and materials together. The materials and topics were up to date and quite relevant to the latest trends in machine learning. Even though the coursework and videos might have come from different sources and might seem unstructured, the content was useful and pointed you in the right direction in case you wanted to delve into that subject using resources you found on your own. Hands-on mini-projects for certain topics were crucial in helping gain a practical understanding of the subject matter. The one-on-one weekly meetings with the mentor were an invaluable experience.

The coursework and videos will take up a lot of your time and sometimes it is hard staying on track, especially while trying to work on the capstone project in parallel.

Overall, it was well worth the time and effort!

Springboard definitely got the job done. Their mentors and career services really make the entire experience.

I had done my research into choosing this course, and it is the best school to sign up for if you are working full-time. The curriculum is well-paced and offered a lot of technical coursework to supplement my existing knowledge of product design. The support I received was absolutely fantastic. Everyone was gracious and understanding to my needs. I've also noticed the community has been growing quickly since I've last signed up.

I just completed the Data Science Career Track with Springboard. I had a good experience overall. My mentor was very helpful with the two capstone projects. I felt that the curriculum was pretty in-depth, although it would have been nice at some points to get more practice with some of the concepts because it is a lot of information to digest and I feel like over the course of the last few months I have forgotten a lot of what I've learned.

I do feel like the career support is good because they are actually invested in you getting a job because of the job guarantee. I don't have a job yet but I have had a few phone interviews, and I am optimistic about my prospects.

Pros:
Nice and organized curriculum, with mini hands-on projects.
Continuous help from the mentor (real Data Scientist working in industry)
Remote and part-time. So you can maintain your present job while working on this.
Opportunity to work on two capstone projects with the help and support from your mentor.
Career coaches are there to help with your resume/LinkedIn profile, networking, and soft skills.
Mock interviews to prepare.

Cons:
No in house lectures/ they are tied up with Data camp/Khan Academy/ LinkedIn learning mostly for all lectures.
Everything is remote, so you might lose motivation sometimes, where in-person boot camps are like a real school.
Not all the mentors are equally caring and helpful.

6-month online bootcamp on ML Engineering, which is to put ML models into production, using high software engineering standards for quality, testing, serving, monitoring, documentation, etc.

They are one of the crooked so-called educational institutions. I took their course which ensures money back guarantee if I am unable to secure a job within a time frame. I did everything according to their guideline, and now, they are making false accusations to grab my money. I will not let this organization cheat students like this, and I will take every legal actions against them. All the good reviews on internet are simply generated by their robots. They even pay some employers, so that the employers can do fake advertisement of recruiting their students after the completion of the Springboard career-track program. This is such a deceptive and fishy institution ripping off many innocent students in North America. I would never recommend them.

A little background: I'm currently about 25% through Springboard's Data Science Career Track program. My professional background is in higher education. I recently completed a PhD in philosophy and have experience teaching undergraduate philosophy courses. I have minimal background in math beyond the high school level, but my philosophy degrees have prepared me for the sort of technical and critical thinking skills used in data science. I'm doing the Springboard program to make a career change. I completed most of Springboard's Data Science Prep Course, which I found helpful, before being accepted into the Career Track program.
Review: Overall, my experience in the Career Track program has been pretty good so far. My impression is that the quality of one's experience with the program depends largely on the quality of one's mentor. My mentor was initially pretty poor, and I had a difficult time understanding his accent. But I reached out to Springboard early in the program, and they helped reassign me to a new mentor. Thankfully, my new mentor is excellent and has dramatically improved my experience. I'm in a study group with other students, and I've gotten the impression that their mentors are so-so. I have learned a lot so far in the program, and I've been especially happy with Springboard's "customer support" (very friendly and helpful) and career support (they get you started on job stuff early on in the program). A fair portion of the data science curriculum (so far) has consisted of Datacamp exercises. Springboard partners with Datacamp, and students get free access to Datacamp courses. Honestly, I haven't been that impressed with the Datacamp courses. They are helpful for gaining superficial exposure to tools and skills used in data science, but they don't cultivate a deep understanding. I will say that the time estimates Springboard gives (completion in 6 months, working 15-20 hrs a week) are pretty unrealistic. Most of my study group (including me) is working on the course full time, and we are all on track to finish in 5 months (at the earliest), and probably more like 6 months. Unless you already have significant data science experience, don't expect to finish the program in under 5 months, and possibly even under 6 months.
Overall, given my experience so far, I would probably recommend (pretty highly) Springboard's program to people (depending on their circumstances). I'm happy to discuss my experience with people if anyone would like to know more, especially people with an academic background in the humanities. You can find me on LinkedIn and around the web if you look (e.g. philpeople.org). Feel free to reach out.

I was looking for an intense, well-run program that would help me get a job as a data scientist, and Springboard career track absolutely delivered.

The Springboard Data Science Career Track 6-month course has taught me a lot.  The curriculum is set up very well.  You start by learning Python basics, then go into inferential statistics, machine learning, software engineering, etc.  Throughout the course there are 2 major capstones that you build from scratch.  The links to my projects are below.  I've learned so much but please do not think that you can spend 10 hours a week on the course and complete it.  I spent 3-4 hours every night during the week and some weekend days working on the course.  And I will mention that I did not do the job guarantee since I already enjoy working at my current company so you will need to add more time to do the job guarantee sections.

Overall I highly recommend the Springboard Data Science Career Track.   It is kind of pricy but they do have payment plans.  I personally did not pay for the course as my company picked up the cost but just remember that you get what you paid for.  

I can't wait to start applying my knowledge to the real-world!

Capstone 1: https://github.com/brocknosbisch/Springboard_Capstone_1
Capstone 2: https://github.com/brocknosbisch/Springboard_Capstone_2
LinkedIn: https://www.linkedin.com/in/brocknosbisch/

I enjoyed the Springboard UX Career Track program! Haven taken other UX design curriculums, Springboard’s coursework was much more up-to-date pulling a broad range of resources which I appreciated when thinking about real-world application. My mentor has become a life long mentor who was very supportive of my particular UX journey. I enjoyed that capstone and research projects which were more personalized compared to other UX programs I’ve participated in. This allowed me to stay highly engaged throughout the coursework.

Pros:
- Self-paced and flexible programming
- Optimal Resources 
- Unique project opportunities
- Responsive Staff

Cons:
- It could provide a more compelling and accurate pricing structure that reflects the average completion time for students.