Springboard

Springboard's project-based, mentor-guided curriculum combined with their helpful and friendly career services and support staff made for a wonderful experience as a student. There is a broad range of skills learned and practiced through projects including statistics, hypothesis testing, data visualization, SQL, and applied machine learning. Through your capstones, you can dive deeper into data science topics that interest you. Since there is a job guarantee, a fair amount is asked of students, including finding additional resources to help complete projects. For me, this meant spending a minimum of 20-25 hours a week, so make sure you are able to carve out time in your day on a consistent basis.

I enrolled in the Data Science career track. I completed my course a couple of weeks back. I opted out of the career assistance because I already had a job which I am not planning to quit any time soon. I completed my course work. I had to interrupt my course twice. Once due to flooding and the other time when I was about to be a father. On both occasions Springboard paused my course and were supportive of me resuming it later. Pros:-
1. Structure: The course is well structured and gives you a good idea of how to progress
2. Exercises: There were a lot of exercises which gave a very good insight about how a data science project progresses. This included basic and intermediate statistical analyses and advanced topics.
3. Projects: Two capstones make you practice a lot. The capstones along with mentor guidance solidified many concepts in my mind.
4. Mentors (Biggest Pro): Having a mentor was the biggest pro. I was matched up to an excellent mentor, an expert in the field and he was extremely patient with me and always pushed me in the right direction. I understand a mentor can be different for different people but if they match you up with a mentor who is helpful, extract every thing from the opportunity. Cons:-
1. I felt that not enough attention was paid to big data and data engineering. Maybe they will fix it in the future.
2. The content was...ok. You can find equally good video materials on YouTube if not better materials. Overall:-
Its a very good program for the amount of money you pay. I am not sure about the job support but based on the quality of my mentors, I am sure that is solid too.

Overall I had a pretty good experience with Springboard. The curriculum was very robust, and I felt like they covered a wide range of topics. I found the homework to take much longer than the suggested time, but the Student Support was very helpful, and gave me specific help and corrections for my work. I got a job a few months after I started the program, so I can't speak much to the job support, but I'm glad I had the opportunity to build a portfolio. The mentor aspect also kept me honest and on task, which was positive. 

I was constantly looking out for a UX course from past 1.5 years or so. I wanted a classroom training but there were limited to no options. I had to settle down for an online course and I can say I made the right choice by opting for Springboard. 
I asked few of the designers to go through the curriculum and give me feedback and everyone suggested that the curriculum was thorough and covered all aspects of the process. I completed the course a few days ago and here is my detailed review :

Pros : 
- The course is self-paced which is exactly what I was looking for. 
- Every student gets a mentor and my mentor was really very helpful in resolving all the issues that I had. 
- The course material covers almost every important aspects written by great authors.
- Additionally, you also get 1 year lynda.com subscription which you can utilize to learn more in-depth about UX processes.
- Very supportive student advisors. 

Cons :
- Mentor calls are usually once a week and sometimes they are busy and cannot get back on time. 
- For countries like India, the fees is a tad bit expensive. 

The last 6 months has been quite the journey and I'm happy to have chosen Springboard to jet-start my data science career. The program covers a lot of ground and includes concepts such as Python programming, SQL databases, inferential statistics, building your resume/cover letter, networking with professionals, machine learning, etc. 

Pros:
- Everything is online so you can learn at your own pace.
- You are assigned a personal mentor who is a data science professional.
- You have access to extra daily mentor calls with one of the other data science mentors.
- The course will help you complete 2 major capstone projects that you will add to your data science portfolio.
- The curriculum is very thorough and presents you with an abundant amount of resources for learning.
- There are many mini-projects along the way that help you practice your learning.
- You can schedule calls with career coaches who will help you prepare for interviewing and beefing up your resume.

Cons:
- Since everything is online, there are no live instructors who give you feedback in-person.
- Getting feedback on your projects may sometimes take a while because the TAs are typically busy.
- Some of the material was confusing, which resulted in difficulty understanding some of the concepts.

Overall, I would give Springboard a rating of 4/5. I definitely recommend it to anybody interested in becoming a data scientist!

The program helped me to better understand what skillsets that are required to become a data scientist. The most helpful resources from the program are from their mentors and career services. The mentors are data scientists or quantitaive positions from the industry, where they can support your personal projects, interview feedback, and questions that benefit your transition in to data science field. The career service is excellent. I finalized my resume and a set of flow for behavior questions from the program. I feel I don't need to worry about my behavior questions in the future anymore since I learn tips and what people like to hear from the interview. 

I also appreciate immediate service from the program everytime I email them, especially thanks to Kane Li, she is super responsive and helpful. I feel to be taken care of and being supported from the program. 

The only cons for the program is overall the materials are easy and are limited in shaping your ability in becoming a "real" data scientist. The only way that enable you to become harnessing in data science field is by doing capstone projects. I learned a lot from the capstone projects. You can choose an easy dataset as the capstone project, yet I think it would be beneficial if you choose dirty dataset to work on, while it is very time consuming but I think that's what people are looking for as a data scientist in the real world. I am still revising and optimizing it even after I graduated from the program. 

In summary, the program prepare you well in basic skillset and directions to become a data analyst/ data scientist. You will have a clear head of how and what to work on to transitioning to this field. 

The curriculum has probably changed since Oct 2017, some of the criticisms may no longer apply.

The strongest part of the course is the mentor(s) and the career coaches. 

The curated course content overall is very good, though some lectures are from 4-5 years ago.
The main focus is the two capstones and the mentor interaction to keep you moving forward on them.
The Python Datacamp courses (at the time) were mostly useful, though at some points I used other materials from courses like Udemy or LinkedIn Learning where the curriculum fell short of the coursework being asked.
Why the coursework at many points had incorrect time-estimates for the (2-4 hrs suggested but actually needing 10-20) is confusing. We constantly posted about it in the forums but nothing seemed to happen.

Also, some coursework questions and worksheets were out of date or missing. If you have a full-time job then staying on a schedule based on the course completion time then you will falling behind.

The most common observation on the forums was the poorly supported statistics element, with insufficient course material for a crucial element of data science and insufficient study material for the coursework.

Since graduation, I have work every week or fortnight with my career coach to refine my resume, profile etc. I am getting invitations to on-site interviews and phone screens. I have placed my focus on Data Analyst roles instead of Data Science roles, as even a junior data scientist role is a senior position.

I only have good things to say about the online UX Design class offered by Springboard.  I just completed the course.  I am a Product Manager and was looking for a class to really give me an in-depth look at what UX was.  I got that and more.  A very well organized class, great materials to read and watch (videos).  You choose a website or smartphone app to design, and they step you through the project as you progress in the units of the course.  Best thing of all - an assigned, experienced mentor with whom you interact with once a week via a video chat.  Priceless advice and guidance from somebody who is in the business.  Phenomenal!

I honestly can't speak highly enough about Springboard. I feel like I received an amazing value for the cost of the course. The course is self-paced, and you can complete it as quickly or as slowly as you like. I finished the course in about 2 months, which I've heard is pretty quickly — I had just graduated from college when I started the course though and was only working part time. I imagine someone with less time on their hands might take between 4 and 6 months. You're also paired with a mentor, whom you meet with once a week for 30 minutes to discuss any projects you've turned in and any questions you have about the curriculum. These sessions are hands down the best part about the course; anyone can just find a variety of content about UX online and teach themself how to design, but the mentor helps validate a lot of that learning and encourages you as you go. 

The content of the course is an amalgamation of various sources online about UX design, from Lynda courses to Skillshare to articles on Medium and other sites. The quality of the materials tends to be great, though there are a few pieces that I skipped over. You only need to complete 60% of the course and all 13 projects in order to receive your certificate, so if you already feel well versed in an area then you can cut straight to the area's project and move on. 

I'm excited for more of Springboard's in-person events, too! As of this review, they have hosted one conference/meet-up at their headquarters in San Francisco earlier in September, and meeting with other students, staff, an faculty really cemented for me that I chose the right course. I'm excited to see if there will be more of these events, and potentially in various areas of the country. 

I have tried many MOOC data science courses on edX, coursera, udemy and udacity. I got to know the Springboard for almost 1.5 year but kind of doubtful about will it be really useful with associated cost and time commitment. 

After reviewing lot of comments carefully from CourseReport/SwtichUp, I decided to enroll in the course. Another reason is that Springboard is one of the most fair online DS bootcamp companies out there. They offer a full refund if you don't like the curriculum and not meeting the requirements within a week (timeline).

I gave it a try and turns out it was one of the best decision I have ever made in my career movement! The curriculum covers the contents in following order:

intro to data science --> data wrangling --> data exploration/inferential stat. --> machine learning modeling --> capstone.

For me, it was very practical and useful since the curriculum contains basic assignments for data wrangling and basic ML modeling (i.e., regression, cluster analysis and etc.). However, the best part is choosing your own personal project to build your own portfolio with your assigned mentor. Mentorship was the best thing which made Springboard stands out from other DS bootcamp competitors. 

From my own experience, I had my 1st mentor assigned. After my 1st video chat, I realized that my mentor did not meet my expectations. So I had a call with Springboard course advisor and he helped me to find a new mentor which suits my interests and learning goals. 

I really recommend anyone who is new to data science and enroll in Springboard for accomplish your dream career. 

Here are my few tips for being successful in Springboard DS Python track:

1) Prepare your background knowledge: basic math/stat courses from Udacity and other text books.

2) For learning python, if you subscribe to DataCamp and finish 10 courses from their Python data scientist track, you will be more comfortable working on Springboard's assignments and capstone project. This is due the fact that this curriculum has some overlap with DataCamp's Python data scientist track since they are doing collaborative partnership on this curriculum.

3) Carefully review your own time table and get matched on a mentor. Springboard assign your mentor based on your time availability and potential mentor's time availability. So it is important to pick time that works out for you. Another thing to note here is that if you don't get along well with your mentor ask for help from Springboard student advisor. They will help you tremendously in any shape or form to help you get successful.

4) Take a break: if you feel overwhelming sometime due to your schedule, I think they let you freeze account once and can reactivate it in which I did it once for a week or so. Make sure to check out Springboard FAQ section do NOT trust what I am writing here as I don't exactly recall how long you can take a break.

5) Partial refund: let say if you made a full payment (3 months?) and finished the whole curriculum earlier, they will give you the partial refund on whatever remaining portion. Ask Springboard student support on this.

Overall, it was the best online data science bootcamp with following:

A. Great mentor-mentee relationships

B. Support from Springboard community manager and fellow students

C. Flexibility to work at your own pace

D. Affordable and reasonable cost compared to other online bootcamps out there. 

E. There is no job lead on this track but you can get some helpful free resources from Springboard on how to prepare data science interviews. Or you can have a option to enroll in data science career track!

Cheers,

I completed the Springboard Digital Marketing for Professionals course over the summer. I appreciated the self-paced, web-based coursework that was available when I had time to tackle it. I was impressed with the content that was curated and made available to me as a student. It was clear that the curriculum was created by experts who want to educate others to be successful.

My two favorite features of the course were the mentor and the capstone project. Each student is paired with a mentor who provides useful, candid feedback through weekly calls. The calls and time with the mentor are worth their weight in gold! The capstone project allowed me to assemble all that I had learned and have a final product that I could show to a future client or employer. All around a great investment and fantastic customer service experience. 

Springboard was a great experience. Though the concepts and assignments were definitely hard and required heavy investment on time especially as I worked full time, the support was definitely there to help me through, especially from my mentor, Alex. I gained a lot of knowledge through his real life experience and through the support of my career advisor, Allison, I was able to get a job by the end of the program as a data scientist and I am grateful for all the support. Definitely worth investing and going through the bootcamp. 

I just completed the Digital Marketing for Professionals course and am very pleased with the outcome. I was already a seasoned digital marketing professional but I wanted to upskill in areas that I didn't feel I had as much experience or foundation in. The curriculum is structured in a very neat and organized way whereby you build upon your skills and knowledge in each chapter. You work on real projects (and spend actual dollars) culminating into your final Capstone Project. You gain exposure to all areas within the digital marketing spectrum. As a student, you get weekly one-on-one mentoring with an industry expert. The student advisors and community managers were amazing, responding quickly to any questions I had. At the end of the program, you have a portfolio of projects that you could include on your resume or LinkedIn profile. I highly recommend this course for anyone new to digital marketing or looking to broaden your skill set.

My experience with the intro to data science course was great and it is a good decision for anyone looking to get a (great) basic understanding of data science or if you are interested in taking the data science career track. 

If you work at a company that is going to hire data scientists or if you need to be able to work with and understand data scientists, the intro class is for you. It gets into the weeds of data science just enough to not scare you away but enough to give you the ability to understand what data scientists do.

If you want to pursue data science as a career, the intro class gives you a basic understanding of R and R studio and gets into the meat of data science enough to help you decide on if data science is the career for you. You also can apply the first 2 months of the course tuition to the data science career track if you decide to pursue further education.

You also have a mentor you can email and talk with via skype once a week. This is an invaluable service and really allows springboard to stand apart from the other schools.

I highly recommend the data science into class at Springboard.

Anthony Stachowitz