Data Science Career Track

 I wanted to change career and industry for several years and I chose Springboard's Data Science Career Track to do so while I had just been laid off “thanks to” the Covid-19 and oil crises. Great timing for a career change, I know... 
I studied the Data Science curriculum, the Career curriculum, followed the great advice given by my Springboard Career Coach and my Springboard Mentor.  I did everything Springboard told me to do to become a successfull, skilled Data Scientist with a great professional network and high visibility. The results of all of that is I was hired as a Data Scientist on week 13 of the program in a certified "Great Place To Work!" international company,  which leads its industry in the US. 
 

Pros:

100% online curriculum with great resources and lectures from Harvard, Stanford...etc...  All interactions with advisors, mentors, coaches are online and on a flexible schedule.
You'll get enrolled in DataCamp and have access to extra practice/project work to master your skills (Python, SQL, Pyspark, Github...). I love DataCamp and will remain a member. 
You'll have access to LinkedIn learning, Medium, Towards Data Science.
Weekly presentations (career sessions, business hour Q&A, guest presentation).
Weekly meetings with your assigned mentor. You can schedule additional sessions if needed. 
You can select your own career coach from a long list of Springboard career coaches (their background and skills are diverse which makes the coaching experience invaluable). I personally chose one career coach and followed up with him throughout the program. 
You'll get to work on a lot of projects (40ish), 3 capstone projects to apply what you've learned and your work will be reviewed by TAs who have a great sense of humor.
Springboard conference (Rise!) and seminars (wellness, career...) during which you can interact with fellow students, alumni, employers... etc...
Because the program is online and always accessible you can do it in 6 months as planned or in 4 to 5 months. I am now on week 16 with 84% completed. It is really up to you. 

Cons: There are no cons as far as I am concerned however you need to know that the program requires drive and self-discipline because there is a lot to do and so little time... You'll get help and tips from your student advisor, the career services, your career coach, your mentor, the TAs, and even from other students. The bottom line is that you need to stay on task and have the time to work on your projects. 
The program is worth more than you pay for. There is a steep learning curve but it remains fun all the way and it works! If you are afraid of not 'being good enough', start with the Data Science Career Preparation which will give you a taste of the level of statistics and Python coding you need. It is only 4 week-long, about $500 which will be credited towards your Data Science Career Track tuition upon successfull completion.  

I didn't know what pandas was when I started the Data Science Career Track program, and now I feel mostly confident while applying to jobs.Because I have not experience in data science, I'll probably work up from a data analytics role.Biggest Pro: Excellent Mentorship. My mentor was competent, kind, and genuinely wants to help people achieve their goals.Biggest Con: Didn't communicate I need to be practicing on websites like HackerRank or LeetCode. I wish they had recommended it from the start. For beginners, I suggest Edabit.com.

I just finished the course last month and start job hunting for two weeks. I did not have any tech background and I was searching for all the available options for in-person and online DS bootcamps in NYC. After careful comparison and considering the situation of pandemic, I chose Springboard and it has been a rewarding journey. There are several aspects I like about the experience: 1. the course material is well-selected and covers all the basics for a junior data scientist. 2. My mentor has been very helpful through the whole process and I think it is a good training for me to find the best questions to ask and communicate in the limited time. 3. Springboard tries to support me with all kind of tech support(code review, weekly Q&A meetings) to make up for the difficulty of online learning. 4. Springboard offers job guarantee and the career coach is the best I ever had and Springboard is trying hard to prepare the students with job market from day 1. There are things to consider as well: I was doing it full-time and it took me 8 months to finish. If you are very busy schedule with your life and have no coding experience before like me, it needs a lot of efforts to stay on track. Also,  you have to be able to learn independently because there are no TAs around you all the time. Overall, I like the Springboard community and I believe they are doing a great job in preparing their students for the future jobs.

Learned the fundamentals of data science. Mastered level of coding in python, SQL, and how to address a problem in the data science world.

I was looking for a professional course on Data Science to make my career transition and I found Springboard. I must say this Bootcamp is one of the best things that happened to me in this pandemic. The whole curriculum is designed very systematically. Though Data Science is a very vast domain but this course covers almost all topics,  right start from basic python, statistics, machine learning model, SQL, Pyspark etc.  There were many exercises given after every topic so that one can practically implement those concepts. Additionally, more than 30 mini projects and two capstone projects imprint every data science concept in your mind.Career coaches helped me in all possible way to improve my visibility to recruiters. There were four Mock interviews at the end of the course which helped me to prepare for the actual interviews. Springboard Community channel and Weekly office hours were very informative. Last but not the least, MENTOR!  He was the backbone of this course. I was lucky that I got a great mentor. He was there with me at each and every stage of this course whether it was about exercises, mini-projects, final project or any other difficulties in the curriculum.  He always helped and motivated me to do the best in the course. Even after writing this much about the course, I am sure that I have missed many things. So in my opinion, if your looking for a good professional Data science course you must consider the Springboard. 

 I did the Data Science Career Track with Springboard.
Pros:The weekly mentor calls are immense. My mentor has strong experience as a data scientist and he was able to answer every question I had along with providing great feedback for my projects.The career coaching is fantastic. The amount of recruiters reaching out to me via LinkedIn since they helped me retool has been very noticeable. Additionally they also helped change up my resume.The mock interviews were also incredibly helpful. Interviews were always something I had struggled with and their interview prep has definitely helped me in my current interviews.
Cons:I think their curriculum could be better. I had to supplement a lot of it with books, YouTube, and courses on LinkedIn Learning. 

If you are not at the last month of the job search, everything is going well. At the last month, if you still apply and follow instructions of the career coach, and his/her strategies do not work out. They will try to find any reason to kick you out of the eligibility of job guarantee. I had frequently call with career coach every 2 weeks, as required, then the support team from Springboard reach out and said I'm not show up and do not meet their requirement. I had to show the email/proof that I had a call with the coach. The second time, after that 2 weeks, the team tried to kick me out again, say Hey, you had no-show call for coaching sessions 3 times, you will be kicked out of the job guarantee program. Again, I had to dig my Skype history of calls and show the proof with the calls for every 30 mins I had with the coaches. The third time, (this is when I have some weeks left on the gurantee program, while they have to refund me money if they cannot help me to have a job). I had a data analyst position with average income >10$/hour, which is mostly manual administration job, that is not apropriate to qualifying jobs that Springboards teach you, like SQL, coding, Python. I told them that and explain, but they said I don't know about that is qualify or not (so who knows?) because you already got a full time job, you have to report all the jobs that you have, event working as a cashier at mart (It's super weird, not listed on the policy). And the person that I reach out to explain, try to quarrel with me, not shout up, but interrupted and do not let me talk. Super weird again, If they want the program good and reach out to many people, they should have a better support team, listen to customers/students and give the solutions not by saying I don't know, that is my responsiblity, that's the other team decide. It shows to me the irresponsibility of the career support team, and make me so upset with the quality of their service, although I like the cirriculum and my technical coach a lot.

I started Springboard's DSC track in June, 2020. Overall, I had good experience with it. The curriculum is very well designed. I definitely improved my data analytical skills after completion of the course. 

I started the Springboard data scientist career track in Feb 2020, and finished the course in October 2020. I joined other Bootcamp last year but did not receive enough support. The entire program, including weekly 1:1 mentor, career support, office hour, and 2 capstone projects, is really amazing. I have a chance to work with experienced data scientists and learn from them. I highly recommend to anyone who is interested in starting their career or want to improve their technical skills.

I was able to quickly become competent in the python-related related coding tools and practical methods for machine learning model development through Springboard. If this is all you need, I encourage you to use their product to help you achieve that.If however, you do not have a strong theoretical background in linear algebra, multivariable calculus, statistics, probability, and machine learning, you will not find that here. The program's initial screening criteria are permissive and are not sufficient to determine if you know enough theory to work as a professional data scientist. These mathematical skills are important to being able to read ML textbooks and research literature, and to understand ML techniques. I was disappointed by the lack of theoretical rigor in Springboard's data science career track but found resources to study these things elsewhere. After two additional years of part-time study (15 hr/week), I felt ready to work primarily in machine learning professionally and shifted my consulting work to focus on ML.Be ready to learn to the math if you don't have the background, and for that effort to be completely orthogonal from your work in the bootcamp.

I completed the Data Science Career Track Bootcamp in September 2020, after spending 9 months learning to code in HTML, CSS, and Python. I knew some basic data science concepts but, in hindsight, my self-taught tools were haphazard and would not make me a competitive job candidate.Having completed this bootcamp, I have a much more compelling set of data science projects, and can speak much more confidently about using DS tools, whether during a networking event or interview. 

 Good organization course. Good chance to gain some practical experience . 

Duration verses course metirial unrealistic, that's why job ,gurentee is not applicable,  they are using datacamp video, better to use datacamp,  social media you can take help as what the mentor is doing, during sales the mentor which you will speak, and then later the mentor which you will get, you can feel the difference 

Context: During my last year as a Ph.D. student, as I planned to pursue a career in data science, I decided to join the Data Science Career Track of the Springboard program. I was recommended by one of my Ph.D. student friends, who eventually successfully landed a good working position. I therefore decided to follow his footsteps.Overall: I am quite satisfied with Springboard's program. I think it has formed me well to become a data scientist and to quickly land a job. However, I believe there are a few things they can still improve on.Pros:

Overall Quality: the data science track definitely introduces and educates you well to the data science world, used in the industry. It covers most aspects of data science (wrangling, visualization, ML, ... ) and lets you acquire enough experience to land a job in that field. Of course, it won't replace extensive years of professional experience, but it is great way to bootstrap your data science career.
Preparedness: I would argue that the data science track doesn't require advanced programming skills, but it is best to have some Python experience (the software overwhelmingly used in the course). If you don't (like me), the first few months can be a bit of a learning curve. You eventually pass that stage though.
The Capstone Projects: the program is focused on two data science projects that you lead from start to finish. A great learning experience where you put your hands in the dirt, which you accomplish under the supervision of your mentor. These are great accomplishments you put in your portfolio and that you showcase to employers. 
Mentorship: Speaking of which, the supervision by your mentor is probably the greatest feature of the course (and why the price is a bit high). For those who need someone to look over their shoulder, it's definitely a great resource that helps you move forward in the course. The mentorship I received was great and from what I heard, bad experience with mentors is quite rare. Plus you can always change, if it gets really bad.
Career: The career services they offer are equally useful. By helping you build your résumé, your LinkedIn profile, etc... Springboard helps you reach out and makes your profile more attractive to employers. The mock interviews you need to pass in order to complete the course are ideal reflections of real career situations.
Flexibility: While it is not something obvious when you start, you can actually ask for pauses, freezes and extensions if you need more time to complete the curriculum, or if you dealing with too much stuff a time in your professional / personal life (I assume they don't openly advertise that because they prefer you to finish the certification in a reasonable amount of time). I personally extensively used those (mostly because of how busy I was with my Ph.D. work, specially when it came down to my thesis defense). I eventually completed the program in 12 months. However, I DO NOT recommend to do so within such a big time frame.  6-8 months is definitely reasonable if you allocate the proper time each week. If you trail like I did, Springboard eventually starts charging you for additional extensions.

Cons:

Rates: their rates are a bit high in my opinion and I believe it's mostly because of the number of resources they offer (mentors, career advisors, extensive curriculum, access to external resources like DataCamp). It's good to have that many resources, but in my opinion, some parts of the curriculum (maybe less than 10%) are useless or redundant. Therefore, I think the rates (assuming you avoid enrolling in paid extensions) could be 10% cheaper than what they currently are.
Customer Service: this definitely has been the worst part of the whole program. I assume it's because Springboard has considerably increased its volume of students (across all tracks) but their personnel's size hasn't been able to keep up. While I always eventually obtained the information I requested, it takes a while to find and reach out to the proper person. First of, they only allow email communications. Then, their services are split between advisors, support team, finance team, etc... So if you ask for something to someone, they will most likely re-direct you to someone else. And the response time can be a few days. I don't expect every customer rep. to know everything and I assume it takes a while to train them, but it is quite frustrating when you can't get a straight answer immediately, specially for finance-related questions or for deadlines (when you need an answer fast).

Industry mentorship and career coaching are the top perks of Springboard. These two things change lead to visible change after course completion. I would highly recommend.

I enrolled already having some knowledge in Data Science but wasn’t able to find a job by myself. Springboard taught me not only data science knowledge but, more importantly, skills on how to present yourself properly. With my mentor’s help, I started blogging about my projects, which, I believe, helped me immensely. Resume writing tips I couldn’t get from anywhere else are also very valuable. 
Midway thought the course I managed to find an internship. I got a full-time job offer within a month after graduation.
Springboard is an opportunity, but you have to work hard to get the most out of it. Keeping your dedication though the course is demanding, the materials you have to learn are not easy, and you have to do really interesting capstone projects to succeed. But your hard work pays off, and you get support from your mentor and career advisor both during the course and after graduation. 

 My favorite part of Springboard is the ability to learn at your own pace.  I was able to schedule when I was going to go through the curriculum and take as much time as I found necessary. There were weeks when I really immersed myself in the course work, while there were other weeks when I took it easy. Likewise, career coaching truly made the course more than just a skills bootcamp. It really transformed how I view job searching, and the best strategies to get into the industry. 

Springboard provides so much material to help students master Data Science. If you just follow the curriculum, you will be more than fine.  I love the Seat, Crawl, walk, run  model they implement for all the topics. That helps someone who does not know anything about a subject in Data Science to become an expert. You can't find this type of training in Universities because they deal with a lot of theory.  Springboard will make you first of all understand the business aspect of Data Science before bringing you into the technical aspect.  The training with Springboard is very close to working as a Junior Data Scientist in a company, and I think that it was designed that way for companies to have  people that will be less trained to do their job.

Great mentor support.  Career support is good, but can improve. Need more original course contents, and provide data close or like the data you get in a real job for projects.

If you are reading this, you probably know about Springboard a thing or two. So I will just go for the important stuff:The way I see it Springboard gives you a very nice combo: you get to work on a lot of practical stuff and you get to pick brain of a professional. You can't overestimate the value of having your questions by someone who is working in the field that you are trying to get into. These 2 points (practice and mentor calls) are what is great about Springboard. What's not so good about it? I think the curriculum can be improved. But again it's coming back to mentor calls, you can always consult with your mentor what to look for and what things to pay more attention to.Overall it's a great course as it makes the hard process of navigating the first steps in data science way easier.