Springboard

I took Springboard's Career Track Data Science course, which was exactly what I needed to transition my career.  I'm pretty self motivated, which you'll need as the course is self-paced (you can also choose to pay per month which is an extra motivation to complete the course as fast as you can!), but wanted some sort of defined path to teach myself data science.  There are a ton of online resources for free but it's pretty much impossible to know where to start without guidance.

The course does a great job of starting you from basics but they move you on pretty quick from there in case you already have a foundation in CS or statistics.  They match you with a mentor who can give feedback on your projects or answer any questions you might have about the material or the industry.  

The job guarantee is a big reason why I chose this course.  It was pretty much a win-win.  I started looking for a job about a month from finishing the course and got a job offer in about two months.  I absolutely LOVE my new job and what I'm doing now.  

There seriously isn't a better deal out there.  I recommend this program to anyone who wants to become a data scientist.  The ROI here is unbeatable.

I was a student of Springboard's Data Science Career Track between July and November 2017. Completing the track has been one of the most fulfilling experiences of my life. The track was extremely streamlined and sufficiently challenging to keep you involved for the entire duration.
The biggest take away of the program was the mentorship. My mentor, Baran, taught me skills that you will never find in a book or a publicly offered MOOC. He also gave me invaluable glimpses into the world of professional data science. With his constant guidance, I was able to participate in Data Science Hackathons, publish and gather traction for my kernels on Kaggle and  develop a proposal for a talk on Inferential Statistics which was accepted in SciPy India 2017.
Another huge benefit of the program is the network you get to build. Springboard mentors and alumni work at amazing places. I connected and interacted with more than a dozen people doing inspiring work. My mentor personally introduced me to Data Scientists at Airbnb (my first capstone project was on Airbnb User Bookings) and Amazon.  They, in turn, gave me a sneak peak of their work at their respective companies.
As part of DSC, I completed over 15 technical projects and 2 major Capstone Projects. With the help of my mentor, I was able to channel my work in the right places. My analysis on TED Talks caught the eye of the Kaggle CEO who then submitted my notebook to the official TED Team. My second capstone project on Movie Recommender Systems had me publishing a dataset that was trending at the top for 3 straight days. 
The material I learnt from Springboard also helped me in performing reasonably well in Data Science Competitions. My bachelors' thesis project on Fake News Detection is also based on the knowledge I acquired from the program. 
Finally, DSC prepares you for the non technical aspects of getting a job. There are intensive, personal evaluations of your LinkedIn Profile, your resume and mock interviews. These exercises prepare you well for evaluating, applying and eventually interviewing for various data science jobs.
All in all, DSC is a great investment if you want to switch careers or get started with the field of Data Science. It prepares you for entry level Data Science jobs and equips you with enough expertise to jump into more advanced material after the program. Highly recommended!

 

My 12 weeks experience with springboard was excellent. My weekly mentor calls helped me to find the right way to analyze data and go beyond the actual case study. The learning material is easy to read and understand, not that the course is too easy, but the layout and structure of the course is very good and makes it a pleasure to learn. Catherina from student support is great to deal with. I had one small problem, none of springboards fault, but my first assigned mento wasn't available any longer, so  Catherina went beyond her normal hours of work and found me a new mentor over the weekend. I was really impressed with the support she gave me and any other questions, were answered right away, even though we had like 16 hours time difference between Western Australia and San Fran. 

A special thanks to Chinmay , my mentor, who was always available and even so we had to change sometime our time of call, he was always flexible and guided me through the course plus gave me some great insights from his past experience and working as BA. 

 

 

 

 

I took the Foundations in Data Science course from Springboard. I have had some introduction to statistics and programming (quite a bit of stats in my MBA program and took many datacamp certificates for R and Python programming).

Really enjoyed the foundations course from Springboard. Have tried using many MOOC`s (massive online open courseware) to learn data science but to no use. Springboard`s mentor driven and community driven coursework is a lot better. Setting up the R Studio environment, Github, writing code on R, R markdown etc, all take quite some effort, if you are from a non computer science background (I am not a CS major but had some coding in high school and undergrad). This is where the mentor and community are most useful. 

The $ 500 per month fee is very reasonable for the community, mentor interactions and curriculum that you get in the course. 

My advice to prospective students who have no background in statistics and programming is as follows:

1) First learn statistics from online resources like Khan Academy, Saylor.org etc. Topics may include descriptive statistics (mean, median, mode, variance, standard deviation, types of distributions, probability), inferential statistics (p-value, Z-scores, hypothesis test, t-test) and machine learning (linear regression, logistic regression, some simple classification algorithms etc). Even datacamp.com has many good coding courses built around statistics.    

2) Learn some R, Python and SQL from datacamp.com. Take a total of 10 certificate courses from datacamp in these 3 programming languages. This will really help develop your coding skills. In R, take introduction to R, intermediate R, dplyr, ggplot, statistics with R etc. In Python, learn numpy, pandas, seaborn etc. 

3) After you have finished above 2 points, you can move to Springboard. You may think that Springboard is also about the first 2 points. Yes, it is. But the most important part of Springboard is the capstone project. Once you have completed point 1 and 2, you can enter the Springboard foundations course confidently and spend most of your time thinking and working on your capstone project. Remember that nothing matches the skills you develop while completing an end to end capstone project. This is only possible on Springboard at a very reasonable price.

Lots of effort and motivation + Springboard + Datacamp is the best formula for becoming a quantitative analyst/junior data scientist, if you do not already have a background in statistics and computer science.

I've been a visual designer (mostly web) for about 10 years. I've done aspects of UX in many of my jobs/projects. But there were a lot of best practices in research and prep that I'd never properly learned to be an official UX designer. I learned and practiced all these textbook need-to-knows and quickly got my portfolio updated to prove it through this course in a matter of a few months. I saved $1000's from avoiding full-time courses that I didn't need since I had quite a lot of on the job training already. Since completing the course I've gotten messages weekly to daily from recruiters on LinkedIn looking to place me in new exciting roles at big and small companies. TOTALLY WORTH IT.

My UX project from the curriculum: https://www.jennlindeman.com/ux-project

I took Springboard's UX Design course, and really enjoyed my experience. The curriculum was engaging, varied enough to accommodate many different learning styles, and was dynamic - Springboard updates their curriculum all the time, so nothing feels out of date. The emphasis on working with other students through the online community made it easy to gather ongoing feedback about your process, and simulated a bit of what it's like to work on a UX team - you never work in a bubble ;) 

The self-paced nature of the class is a bit of a double-edged sword, because you can finish the course while working a full time job, but it does mean you need to be really self-motivated - I work full time, and finished the course in 3 months. Both your mentor and Springboard advisors are extremely helpful and supportive, and can even provide suggested timelines for what to work on each week in order to finish the course in the time that meets your needs.

As I mentioned earlier, each student is assigned a mentor, with whom you work closely, meeting each week to discuss progress, goals, and other, non-course-related aspects of UX design work. This mentor/student relationship was invaluable to my success. My mentor is extremely talented and charismatic and working with her helped keep me on track. 

 

I highly recommend Springboard to anyone looking for a dive into UX Design. 

I would highly recommend the Springboard UX Design course to anyone that is looking to learn UX Design or would like to get a jump start on putting some UX examples on their portfolio. I had worked in UX for about a year but didn't have any personal examples that I could show for on my public portfolio. My Springboard (Sara) was extremely helpful in providing me with feedback and recommending resources that were outside of what the course had listed. 

This course was great because as a freelance web designer, my schedule isn't consistent week to week. Since the course is flexible, you are able to do as much or as little of the work each week to make it work for you. 

I was left with an amazing portfolio piece on the entire process of UX Design and have been offered multiple positions since completing the course. I also felt extremely comfortable in the interviews as I was confidently able to walk through the ENTIRE UX Design process since I had gone through every piece. 

Would highly recommend this to anyone interested in UX!

I had no official IT experience but I was gently let into the IT world through the layer upon layer approach of Springboard. I had hands on to see the concepts in practice. I had mentors, TAs and great support staff who promptly addressed my challenges. 
Springboard is a people centered organization. They worked with me through phases in my private life which required my full attention like the delivery of our son. I could be present with family because Springboard has accommodations for events of life. 
The course materials are so empowering that I felt prepared to take CompTIA with a few weeks of preparation. 
Springboard has a great team of career coaches who have helped me set up a befitting Resume and a LinkedIn page. 
Thank you Springboard.

The Springboard program gave a great survey of the entire data science process before going into various topics. I gained a good handle on Python programming and SQL by the end. The projects were organized in tiers of difficulty which gave me the ability to complete them at any level. By far the greatest part of this program was my technical mentor. She had incredible industry knowledge  and guided me in my capstone projects so I didn't deliver work that was too simplistic or get lost in overcomplicated projects.

The one thing I'd like to see in the future of the program is more time spent on the 'software engineering' side of data science. How do you deliver in the broader context  setting up models and product for commercial use within a company? I think this could be a differentiator in the future. 

I am very glad I chose the Springboard Data Science Track as my first introduction into Data Science.

I recently completed the Springboard certification program, and overall, I found it to be a well-structured and progressive course. The learning path was easy to follow, making it simple to stay on track and build new skills. One of the program's highlights was the active and supportive community, which provided timely help whenever I encountered challenges. This aspect greatly contributed to enhancing my marketing skills.However, I believe there is room for improvement in the mentor-matching process. It would be more beneficial if mentor assignments aligned more closely with the student’s background. Additionally, the tech support could be more responsive to ensure smoother learning experiences.