Springboard

I'd say the best parts of the Digital Marketing Career Track were the direct experience running Facebook Ads and Google Ads campaigns. You get hands-on experience using $100 budgets and up to $10,000 if you participate in the Google Marketing Challenge where you work with a real non-profit which is invaluable. In addition, you can talk to your mentor each week and they'll help answer any questions you have regarding these projects. I also appreciated the career  services, especially since you have access to the career coaches for 6 months after you complete the course to help you find your perfect job. 

This program has many great resources to help you advance your skills as well as a curriculum that keeps you focused and scheduled in completing your work. There is a community of people looking to help you including career coaches, weekly mentor calls, which I used to discuss the projects I was working on as well as specific questions about coding. And an online forum of students asking questions pertaining to the same types of projects you are working on. The main focus of the course is completing two main capstone projects which are geared towards building your portfolio and are exemplary of work one may do in a data science career. While there are many smaller mini projects included in the course that are also good practice to improving python and sql skills, there could be created content designed for learning the code and applications needed in these types of assignments. A significant portion of the curriculum was just courses on DataCamp and video lectures, while informative, are not particularly useful in grasping the concepts needed. For an expensive course, I was expecting more specialized resources focused on learning the skills needed, rather than just projects that force you to know the material and go out and use it, which is difficult at first and slowed my progress throughout the beginning of the course. I viewed this as being both a good and bad thing, because although I began working on these projects without all the necessary knowledge and skills, it forced me to pick them up as I went along.

Pros:
- dedicated mentor
- can schedule calls with random mentors for problems your having with very open times to choose (super helpful)
- access to datacamp and linkedinlearning (my favorite platform to learn data is from datacamp personally)
- Excellent administrative team
- Excellent career support team with advice well in line with reality, always super friendly
- Show you how to network properly
- Annual springboard rise event
- Involved student community

Cons: 
- too much use of videos and not enough use of reading for many of the subjects. Many of the topics could have been better explained from a book or article than watching many of the webinars from Harvard or pycon in my opinion. Those videos were often very lengthy and hard to follow along with and I found myself skimming through them. They didnt have decent background information before the these videos that would delve into complex subjects sometimes. This is my biggest complaint to be honest. 
- Some of the assignments needed better instructions such as the databricks miniproject. I know trying to figure something out yourself is the best way to learn but when you dont have the 
preknowledge on something so new to you it could be frustrating

Summary:
Springboard was exactly what I needed as someone coming from a background in business and who had next to zero technical skills such as coding. I landed a role as a  contingent worker  at Facebook as a business data analyst. Without a masters degree or more extensive work experience in tech working with data, i still havent been well suited for a data scientist position, so I'm supplementing this with starting a masters degree program in data scientist, but I believe if you already have a masters in any field and or have remotely relevant experience working with data, a masters degree wont be needed to land a data scientist position like I think is needed for me. Springboard is overall an excellent program to learn. 

After getting my Ph.D. last year, I started to study about data science and get some online certificates. However since I had a full-time job as an Electrical Engineer, it was pretty hard to find the right materials to study or build my portfolio in Github. I got lost after a few months, and there was no support and feedback.  When I found the Springboard career track program, I found it a matching base on my interest and my background. The  1:1 mentor calls every week, was excellent support and pushed for me. The other advantages were about the four mock interviews that Springboard provide to get us ready for the real interviews. 
I recommend this course to people who have a good background in coding and have some knowledge about machine learning since it is an intense program and you have to invest proper time and effort in 6-8 months. 

I just completed Springboards Data Science Career Track Bootcamp. Overall I was very satisfied with the experience. The skills I learned are super useful, and make me much more marketable as a job applicant. The 1-on-1 technical mentoring was great, helping me overcome obstacles and prioritize my time. The career coaching was also very valuable, helping me improve my resume, cover letter, etc.

Some of the chapters in the curriculum simply pointed to youtube videos, which often (though not always) excellent at explaining data science concepts. Some of the chapters linked to Datacamp courses, which are often a little too easy but do explain the concepts well. Overall, the miniprojects and capstones were great, and helped me learn all the steps of being a data scientist.

Granted I don't have a job offer yet, but their job guarantee certainly provides some peace of mind. 

I started this program to brush up on my Python skills, as I had worked in financial analysis before and was looking for a data analysis position. Most of my data analysis before had been done in Excel, with some small Python projects.

The 3-month program had a curriculum consisting of mostly third-party materials - Youtube videos, academic videos, code exercises with first-party supplements, and of course a lot of coursework/projects. You also have weekly calls with a mentor who helps you navigate the materials and gives industry insights.

The curriculum definately boosted my Python skills to the next level, while giving a good introduction into Data Science concepts. In my opinion the Machine Learning segment was a little light, but it gives you a good foundation for further research and learning.

And yes, I was able to find a position in the field even before finishing the program!

I had very little knowledge about UX going into this course, which was the perfect fit.  The Springboard UX course took me through each step of the design process, from basic overviews of what UX design is and of job opportunities in the field, to user research, prototyping and user testing.  The curriculum has a nice balance of videos and reading material, and they are good about not throwing too much at you.  Having a mentor to meet with every week was the best part, by far.  My mentor was there to keep me accountable, but never added too much pressure.  He was very understanding that I was coming from basically zero experience, and helped me create a prototype I felt good about.  In the end, I had a project I can build my portfolio with, showing a comprehensive UX design process. The Springboard support team is extremely easy to reach and was responsive when I had questions.  Overall, I'm glad I took the course and would recommend it to others. If you are diligent about making the most out of it, Springboard will serve you well. 

The course materials weren't too difficult to grasp; some were a bit repetitive. 80% of the materials are free – with a few expections such as the Lynda/Linkedin Learning lessons. At the same time, the materials were properly divided among each core topic of UX design. The pace definitely starts off slow but picks up towards the end, with projects requiring more hours and recalling skills you learned in previous modules. It was a good pace for me, someone who didn’t have any professional design or coding background. The course doesn’t touch on any coding languages or skills – but focuses on the research, interpretation of data, and materializing the information into a prototype. Every week, I spoke to my mentor for 30 minutes to go over whatever topics I wanted; ranging from their own professional experience to my course progress. Other than a 1-on-1 mentor, there are also mentors in the community answering and providing feedback to your questions and projects; they listen and care!

Since this course is monthly-subscription based, there aren’t any strict deadlines. However, I suggest doing your best to complete the course over the average 2-3 months. Maybe 5 months at most. I had to take a long break (pause my access and monthly payment) due to fatigue from my full-time job. However, the break was too long and I had to revisit all of the old materials from the earlier modules.

I just completed the course 2 weeks ago and still looking for a job. But I knew it was going to be tough to get a job straight out of any of these ‘bootcamps’ especially since my portfolio consists of just 1 project at the moment. I’m currently working on finding new ‘mock up’ UX projects and also some ‘real’ projects from a few friends, local businesses, etc. This won’t be too bad since I’m currently unemployed. haha.

Overall, a great experience with current course content, mentor calls, and a 6-month job guarantee. The course was organized in a way that it was very easy to learn and follow the design process and master key UX concepts. The mentor calls were extremely valuable! You're paired with the same mentor for the duration of the course and they will offer you insights on your projects, current industry standards and best practices, and help set expectations for your job search. And as an online course, it's extremely flexible, yet intensive. 

This class taught me so much. As a graphic designer, I wanted to further my skills and grow my knowledge base. The course was interesting and compelling but the real WOW factor came from the mentors and advisors. My mentor gave me real life applicable advise to improve on my work, truly constructive critique, as well as commending me when I did things well. The advisors were so helpful as well whenever I had concerns or questions and were very responsive. I would recommend this course to anyone interested in diving into UX! Thanks for everything!

I really enjoyed the Introduction to Data Science course at Springboard.  While the course is self-paced, it is still incredibly challenging.  This course recommends 3-4 months to complete, but I definitely needed the full 4 months.  The mentors at Springboard are great--supportive, knowledgeable, and incredibly generous with their time.
The curriculum itself is tough--some of the programming lessons are in DataCamp, which I found very helpful; some of the stat lessons are in Khan Academy, which I also found helpful; some of the lessons are lectures in a series of YouTube videos, which I found a little bland and hard to refer back to later on in the course; and some of them are articles, which really varied.  The course material is definitely comprehensive, but there is no definitive textbook to refer to, so it's really hard to problem solve when you get stuck (I ended up just going outside the course and Googling for a lot of things).
Completing the course requires a lot of one-on-one mentor time, some of the curriculum, and a lot of determined, creative problem solving when the curriculum just doesn't cut it.  That said, I still found it invaluable for both my current job and my overall career.  I plan to continue with their Intermediate Data Science course next.

The question I always ask myself when providing a review is - could my words make a positive impact in someone's life? I consider concept of Springboard as a leader and pioneers of mentor led UX programs. More than the educational program itself, a genuine and experienced mentor can make all the difference in the world. @Midlife I needed to make the right decision, I did not feel like taking a gamble with time or money.

After 4 months of deep research around the country and even outside of the USA, my resounding selection was the Springboard UX program. Although I did not have the best experience with the first mentor pairing, the immediate correction made all the difference in the world for me. I hit a homerun with an incredible UX professional as a mentor (Andre) for my Springboard UX program. To make it even better was the amazing student support team that was always available to… yes! Great support it’s students.

Pro’s:
- Program Content is very complete.
- Course work can be heavy at times, for good reasons as you immediately get to practice hands-on what’s important.
- Perks as a Springboard Student are excellent and add incredible value.
- Mentor concept and support is probably one of the best features and differentiators this UX Design program.

-  The program has certain custom flexibilities if you are pressed on time or maybe due to other obligations.
- Student support is very agile! They actually listen to students needs.

- Cost is not high nor low. It’s right in the middle. Monthly payments are manageable if you plan ahead and make good use of your time.

- Student community is an asset, it can be slow at times as most students are in fact busy.

Con’s:

• I found none!

What would I make better if I could? The student community could use a more engaging and more dynamic collaboration tool. Is good today, but It can be amazing with the quality of the Mentors/Program and student community the Springboard programs have.

If I would do it again? Absolutely yes!

Robert R  

Overall, the content of the boot camp was directly useful in preparing for data science interviews. I accepted a full-time data science position in the Bay Area recently after 3 months of searching while also having a full-time job. Obviously, you must keep your expectations realistic and be honest about your skill level when transitioning to data science. I had to work on more coding problems via Leet Code and gain speed in completing data science challenges, which was beyond what the course could help me on.

I would certainly recommend the course to those who have technical degrees (I had two engineering degrees up to the masters level) already and just need the extra bump in skills to break into data science. For those from less technical backgrounds, a traditional academic program might be a better alternative because it may be harder to convince those in the industry that you're capable of deeply understanding how the machine learning models actually work from what I've heard.