Springboard offers online, flexible, mentor-led courses including the Data Science Career Track with a job guarantee, and UX design workshops. While learning cutting-edge digital skills entirely online, students receive teaching and mentorship from industry experts. Springboard offers a number of self-paced, mentor-led workshops, plus a full Data Science Career Track program designed to place students in data science jobs. The Career Track program has a job guarantee, where students who don’t get hired within six months of graduation, get a 100% tuition refund.
Each Springboard student gets paired with an industry mentor, who works with them one-on-one. Students start with the basics and work their way up to an industry-worthy capstone project they can add to their portfolio, and showcase to potential employers. Throughout the course, students receive support from their industry mentor, as well as Springboard's resident advisors, and student/alumni community.
Springboard also helps graduating students with career advice and job readiness – e.g. portfolio review and interview preparation. Career Track students will have a career coach and do mock interviews with professional data scientists.
Recent Springboard News
- Meet the Data Science Career Track at Springboard
- Episode 10: January 2017 News Roundup + Podcast
- Alumni Spotlight: Kristoffer Daniels of Springboard
Recent Springboard Reviews: Rating 4.89
Foundations of Data Science
Launch your Data Science career with this introductory course. Build a solid foundation in R and start exploring data-related careers with a mentor who is working in the field.
- Payment Plan
Data Science Intensive
Data Science Career Track
Get a job, or your money back. Introducing Career Track: An online, mentor-guided bootcamp, designed to get you hired. Enroll in Data Science Career Track, and you’ll get hired within 6 months of graduating, or we’ll refund 100% of your tuition. In this bootcamp, you will master the data science process, from statistics and data wrangling, to advanced topics like machine learning and data storytelling, by working on real projects. With the guidance of your personal mentor and career coaches, you will graduate with an interview-ready portfolio and a network of data scientists. We won’t stop there. We know that career transitions are hard, and we’ll support you every step of the way — until you get hired.
- Payment Plan
- Minimum Skill Level
- Comfortable programming and comfortable with statistics.
- Placement Test
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I recently completed the Foundations of Data Science course. It took me a little less than 3 months to complete the curriculum and capstone project.
The best part about Springboard is the mentoring. I loved my mentor--she was extremely generous with her time and knowledge and her interests and mine aligned very well. She was always quick to respond and really encouraged me to push forward with coding and analytics that I felt usure about. I really miss my mentor!
I came to Springboard with no coding background , but with a graduate degree and some knowledge of statistics. Springboard does not make ANY of their own curriculum and they don't craft any tie-ins or connections between the different lessons. A large part of the curriculum is based off of Data Camp to learn R. Learning through Data Camp has it's own set of challenges and none of these are addressed by Springboard. Other components of the course include the EdX Analytics series and dplyr videos through Data School. Many of these resources are good on their own, but none is complete enough to give the student (or at least one w/o a coding background) sufficient foundation to tackle the assignments. Often the assignments are so disconnected from the curriculum, that they are difficult to complete w/o help for your mentor--which is OK to a degree, but given that each mentor session is 30 minutes--often time runs out before addressing the capstone and other project concerns. I really feel that more attention should be paid to the curriculum---it is certainly OK to use resources from other sites, but there should be reinforcement of key concepts like..writing functions...through either supplemental videos created by Springboard, or focus lessons during the office hours.
With regard to job assistance--there is none and the career materials provided, again are brief You Tube video clips or books that are not presented in any kind of way to give the student a view of the field, options for careers or even guidance in terms of moving forward with skills, once one completes the course. In fact, after completing the course, there is zero follow up or transition. I never received any certificate or any kind of "next steps if you want to keep learning" email. Once I finished and got my rubric from my mentor (and stopped paying the monthly fee), Springboard went off the radar.
Compared to other online data science training programs, the best part of the SpringBoard is the mentor system in which they assigned a prominent Data Scientist working in the industry as your mentor. Using google search, everyone can easily find thousands websites for the data science courses. However, for the people without data science background, like me, it is very hard to know what kind of knowledge and skills for the data science in the real world. This training equipped with both theoretical and practical skills to solve industry problems. With the mentor system, I was assigned a mentor to learn first hand how to think like and solve problems like a data scientist. At the end of the training, I finished a project to solve a data science issue in the real world. The feedback from the expert is extremely important for those people want to find a data science job but have no experience on that. The only one thing to complain is my mentor knows too much, it is hard for me to digest all of them in a short time. Except for the mentor system, I also enjoyed the data science community. In the community, you can post questions or share experience with others. I always learned a lot of update information about data science there even after finished the training program.
Springboard's Data Science Intensive is a great blend of self paced study, practical coursework, and mentor led training. As part of my mid-career self improvement, I had begun looking at post graduate data science programs at nearby universities. During my research I came across Springboard which was offering a course of training that covered all the same topics as the university programs with better cost and schedule, and complete with access to a data science mentor currently working in the industry.
Having completed the program in early 2017, I feel I came out with a solid technical foundation in data science techniques and tools. On top of that, the practical advice from my awesome mentors was highly valuable with insights into day to day responsibilities and expectations. And, while the sense of community may not have been directly integrated into the course, Springboard does provide the infrastructure of slack channels and office hours for support and communication among students.
Hey everyone, I want to let everyone know that this workshop has changed my life.
As a student in software engineering... Sticking with the discipline and the kind of learning I went through, it didn't give me a wider range of knowledge i wished to seek.
There was no design or human interaction involved out of school. There was no vibe of control over the things you want to do. Everything was structured and it just wasn't my taste.
So, I decided to take UX Design in hope that it would play along side with my Engineering/Programming background and build a more diverse portfolio.
In the workshop, I finished it in 3 months. Depending on how much time you want to put in it, how fast you want to complete it is all up to you. Obviously the more effort you put into the workshop the more you get out of it. It was very flexible to my time but also intimidating to the point where you're not making use of all your money if you decide to miss a week or even 2 weeks. I honestly could've finished it faster if i put my full focus into the workshop. And that's the point of this program, you work at your own pace and you figure out when you can subsidize it with your daily routine.
I've learned quite a big chunk of stuff and used it to my advantage for my school courses(depends) as well as outside business work.
Do you think I recommend this workshop? I definitely do. You will also get a mentor that will guide you through the course and make sure you succeed with satisfaction. Heck, I already miss my mentor :c
I signed up for this class to help me make data driven choices in my client experience role and I can say that the desired result was acheived. I loved being able to work at my own pace and focus on aspects of the coursework that were particularly useful to me while still having the accoountability and support provided by weekly mentor calls.
I have taken the data science intensive course which is python based and it really helped me gain a proper understanding on how to deal with cleaning data, pre processing data, doing exploratory data analysis and machine learning. The course material is great. It is simple and easy to learn. The 1:1 mentor sessions every week was super helpful combined with an entire community of data scientists helped me engage in several things. The youtube videos on career and interview prep helped me a lot as well. The topics discovered were very much aligned to what they would expect in a data science interview. I even had a couple of mock interviews. In overall, a great experience, definitely recommend it.
My experience with the UX Design course at Springboard was incredibly pleasant. The materials gathered and provided to the student are thorough without being overwhelming. Being able to work at my own pace has always been the best way to learn for me and the mentor calls provided insight that you wouldn't be able to receive in a traditional classroom setting. My mentor encouraged and helped me set proper goals for our next calls and in the end I had a great portfolio to use for future positions. I would definitely recommend this course to anyone wanting to further their UX knowledge and build a portfolio.
I really enjoyed the Springboard UX design program. It's self-paced, so you do have to have some motivation to finish / get work done, but I found the curriculum to be a great overview of all aspects of UX. I thought all the info was relevant and interesting, and confirmed that I want to work in UX for a career!
As for timeline, I was able to finish the program in one month while also working a part time job. I only felt a little pressed for time at the very end when I was finishing up the final project.
The mentor calls were particularly helpful, especially for career and portfolio advice. Overall I thought this course was great and would recommend it to anyone who is interested in UX.
It was a pleasure and I enjoyed it very much! Upfront I read that former students found Springboard to be so effective because of the mentor calls. That is, for sure, a very important reason. But I want to add that I find the current curricular also very well thought through. I noticed how I was able to put more and more pieces together and create a complete picture of what the course was promising. Well done guys! Thank you very much and all the best to you! I can definitely recommend Springboard!
This is a review of the Foundations of Data Science course through Springboard. I've found the course to be very thorough and specifically catered to an individual with little to no knowledge of the basic tools of large data compilation, analysis and presentation. Real-life data is messy and the course caters to the basic process of cleaning and compiling data that is then suited for hypothesis driven analysis.
It is expensive and well worth if only individuals have substantial time allocated in the day to completed both learning of concepts as well as implementation of the code. One can avail of several shortcuts during the course , which would severly handicap the learning experience. Hence the onus lies on the individual to put an honest effort to work through the datasets in conjunction with the instructors to get the best out of the course.
The self paced learning and the help of the instructor helps busy individuals like me to get a grasp of odd concepts and move through the course. Along with my assigned project I was able to apply concepts to my personal work which is doubly satisfying.
If I were to repeat this course, I would go through the courses in Datacamp, complete them and then join the Foundations course.
With a wonderfully-planned curriculum, an extremely helpful support staff and continuous guidance from a professional mentor, I have learned so much! And I actually had fun while learning. Springboard has cultivated an active community of students and graduates. I would recommend this course for anyone interested in a UX career or anyone who just wants to add UX Design to their skill set. Ongoing mini projects help you apply what you have learned, and they add up to form a thorough capstone project. I would recommend giving this course 2-3 months, so projects have a chance to fully form and are not rushed. Overall, a fantastic experience.
I took the Data Analytics for Business course this Fall, and it was easily the best career decision I've ever made. Nearly one month after the course ended I recieved a job offer to do data analytics at a consulting firm. Here's why I'm prepared for this job:
First off, my instructor was an analytics expert whose passion and patience is remarkable. All of the feedback I recieved was constructive, positive, and timely. Additionally, his advice on the job application/interview process made all the difference for me.
Second, the course material is challenging, applicable to "real world" analytics work, and surprisingly fun. I found myself wanting to do even more case study work when I completed the course material.
Finally, the Springboard team is a group of happy professionals who truly, sincerely want to see you succeed. That's awesome.
I would recommend this course to anyone looking to make a career pivot into analytics, or to those who simply want to add analytics concepts into their current position.
I discovered Springboard through the Philly design community and it's been a great decision. I've been working as an agency designer for close to 10 years and was at a point in my career where I knew I needed to make some changes to stay relevant with the rapidly evolving industry. Grad school wasn't looking like the best option, due to its expense and timeframe. For these reasons, Springboard is an excellent alternative to a long-term degree. You get a solid understanding of the core principles of UX design, and their curriculum provides you with a good range of articles and videos from top sources. This is especially helpful since, if you just do a search of UX articles without having any real background in it, the sheer amount of information out there can be overwhelming. By curating a collection of content, Springboard makes it easier to navigate learning about UX design. It was exactly the type of program I was looking for, and I'm glad that I'm able to apply what I'm learning in my office. My student advisor, Catherina, is always pleasant, responsive, and helpful, and my student mentor, Emily, is fantastic. Super knowledgeable, friendly, and supportive. It makes a difference speaking directly to someone who knows the ropes and can provide input. So glad I enrolled!
First, let me say that this isn't an easy course. At least it shouldn't be if you're pushing yourself. It is worth your time and money if it's something you're serious about. If you're not sure, be aware of that before investing.
With that out of the way, I can say with confidence that this is a very good way to get started and branch out into the world of User Experience Design. You'll complete a couple of projects that will walk you through how to approach problems in order to solve them accurately with the added tutelage of a skilled UX professional at your side. It will teach you to fail quickly and be okay with it. You'll learn to find and interview users within a targeted demographic, synthesize patterns and solutions from the data collected, and create quick, iterative prototypes to quickly check to see if you're solving your specific problem well or not. It's a good class.
If you're a working professional in the field, consider asking your company to cover or help cover the tuition. What you learn from this course will end up helping them in return. I worked very hard in this course for four months and got a lot out of it, and by completing it you'll retain access to the material (even as it evolves and changes) for life. It's a very solid investment in yourself, you just have to be a good self-motivator in order to make it through to the end.
This was a great start to my foray into Data Science. I got acquainted with the tools and methods of the trade, and completed interesting assignments and projects. I took the course to see if Data Science was something that I wanted to pursue further, and now I'm enrolled in a Masters program. The mentorship was especially helpful, and I think Springboard was well worth the time and money.
I am currently a student of the Foundation of Data Science course. I must say, the course is excelllent! The mentor I have is an awesome person.
This is an great experience for me. I definitely recommend the course for those who are interested in becoming a data scientist. I await the job assistance is the reason for low rating at the moment. However, I am absolutely confident Springboard will place me on my dream job as a data scientist.
I really like the online course. It use multi-media which is very clear. My mentor is so nice and patient. He is very smart to guide me throng the whole design process. I also like the interaction in the student community, which allowed us to learn from each other.
i am currently enrolled and definitely think this a great course for UX! From the curriculum that helps you learn the basics of UX to the mentor calls with someone working in UX, to the weekly office hours I have learned a lot about the UX field! It seems to be preparing me well for the UX field because I am finding that the course contact has prepared me for the UX networking that I have done so far! I am confident after I get through the course I will have a good portfolio and base for getting into the field! I would definitely recommend the course to anyone looking to see if UX is the field for them and to develop a portfolio and basic UX knowledge!
At my job, we noticed a big need for someone with UX Design experience to fully vet out projects and ideas prior to pushing them into development. I was granted the ability to take the UX Design course through Springboard and instantly loved the setup. I was able to log on whenever, have tons of curriculum to go through. Lessons were easy to follow along and the project I did was extremely useful in my own life. Each week I met with Dave Hawkins who is a very talented mentor and made complex items very easy to understand. I have seen an improvement in my work, my clients happiness and am able to attack problems better after completing the course. I would recommend this to anyone interested in a career in UX design.
The Data Science Intensive course at Springboard turned out to be exactly what I was looking for. It brings together a good collection of content and exercises to allow students to adapt a technical background to current data science skills and tools.
When I applied, I didn't appreciate how beneficial the mentoring structure is in building both knowledge and confidence. Besides being very helpful with the technical curriculum when I get stuck, we also spend time talking about the data science industry as a whole to help prepare for my job search once I get through the rest of the course.
The Data Analytics for Business course had :-
1)Great content- the case submission every alternate week kept me on the track. Being an analytical thinker,I read the material and jumped straight to the case assignment due.
During the weekly mentor call, I discussed my problem solutions and approach with my Mentor who was very helpful.She gave me great feedback and examples from her job which I inculcated in my final submission.
2)The weekly mentor calls kept me accountable to always be working on the course content. That is the best part about this course.
Great experience. Would highly recommend this course!
Our latest on Springboard
Springboard recently launched their new Data Science Career Track, an online, mentor-driven course that promises graduates a job in the field or their tuition back! We chat with the Director of Data Science Education, Raj, to learn why he’s passionate about helping students make career changes, why their curriculum focuses on Python, and exactly how Springboard’s students are landing jobs when they graduate (hint: it’s not by blasting out resumes).
Tell us how you are involved with Springboard’s new Data Science Career Track.
I’m the Director of Data Science Education at Springboard, which means that my job is to create and maintain our data science curriculum, including launching new courses like our Data Science Career Track.
Why are you passionate about helping career changers become data scientists?
I actually changed careers through online education. I have a Master's and Ph.D. in Computer Science from Rice University. However, after a couple of years of working in the industry as a developer, I wanted to transition to data science. I tried out a data science class on Coursera, and then spent two years teaching myself through online classes at Stanford with their Continuing Education department, and then changed careers to data science. Before Springboard, I was Chief Data Scientist at a very prestigious startup in Atlanta called Pindrop Security. I had been mentoring for Springboard’s Python course, and when this opportunity came up to take over the data science curriculum, I jumped on it.
I’ve been through that career change using online education, so helping others and encouraging them to switch careers and upskill is something that I’m really passionate about. Working with Springboard is a way to have that kind of impact on a bigger scale.
What’s the difference between past Springboard courses and the new Data Science Career Track?
We teach three other Data Science courses: Foundations of Data Science (which is based in R), Data Science Advanced (which is based in Python), and Data Analytics for Business (which is based in Tableau and business case studies).
The Data Science Career Track is our first foray into providing career services. We've hired a full-time career services lead to take over the career aspects of the course, and I’m maintaining the technical curriculum.
What are the admissions requirements for the Data Science Career Track? Can someone start as a total beginner?
Because we offer a job guarantee for the Career Track, we’ve found that having some technical background does help students get jobs. So our admissions process involves a programming challenge and a statistics challenge.
For total beginners, we recommend one of our Foundation courses depending on their background. If they have no tech background whatsoever, then we typically recommend Data Analytics for Business. If they have a little bit of programming background or technical background, then we tend to recommend Foundations of Data science.
Will the coding challenge be in a specific language?
An applicant can choose their language, but the most common are Python, R, and Java.
Can you tell us a bit more about the Job Guarantee? What are the conditions of the job guarantee and why is it important to you at Springboard?
Roughly, our job guarantee means that students who complete all of our curriculum, including all the projects and follow the guidance of their career coach, and meet eligibility criteria are guaranteed a job within 6 months of completion. Eligibility criteria include willingness to live and work in one of 11 major US metropolitan areas, US work authorization, a Bachelor’s degree, and be age 18 or older. In addition, we require that to be eligible for the guarantee students are active in their job search and committed to their own professional success in that area. We have full confidence that if our students commit to the learning in the program, which includes both technical material and job search tasks, they will be successful in meeting their career goals.
Which data science languages have you incorporated into the curriculum?
We've decided to focus on Python. However, we don't really teach Python in this course; we assume that you know the basics of Python. We teach the Python data science stack, which starts with Pandas (a Python library to manipulate data, clean data, wrangle data), and then we teach Python libraries like NumPy, SciPy, scikit-learn for machine learning, Seaborn and Bokeh for visualization. In addition, we also cover Spark, which is one of the most in-demand tools for data engineering and scaling, along with PySpark (a Python interface to Spark) and MLlib, which is Spark’s machine learning toolkit.
Both R and Python are pretty common in data science, but if you're working as a data scientist, particularly if you're working on building machine learning algorithm prototypes, knowing Python is a huge advantage. You’ll find that R tends to be less connected to production systems, so we made a conscious decision to go with Python.
Did employer needs and feedback go into the curriculum design?
Yes. Many of our Data Science Intensive students were interviewing with employers, and we got feedback from those interviews. We had a sense of the gaps between our Data Science Intensive course and what employers were looking for. The Data Science Intensive was getting students 70% of where they need to be in terms of technical skills to find a job. So what was the remaining 30%? Employers said they wanted more experience with real world data sets and portfolios, and they also suggested we work on interviewing skills and job searching.
As a result, we weave career steps throughout our technical curriculum, so students are building their network, working on their LinkedIn profiles, and coming up with their pitch from Week One. Towards the end, when they're done with the technical curriculum, students can set up mock interviews. Some of our mentors have been interviewing candidates for many, many years, and they will give you feedback according to a preset rubric so that you get all the practice that you need for interviewing.
If you wait to finish the technical curriculum and then start your job search process, that's just going to cause a lot of delays.
What is the teaching style like at Springboard? What should students expect?
Our teaching model is completely online and self-paced, so students go at their own speed. First, you’re assigned a mentor, typically someone who currently works as a data scientist in the industry and has worked for a few years. They have not only data science experience, they also have the sense of what industry careers in data science are like.
Students work on the material in the curriculum at their own pace and the material is curated, which means that we collect the best content we can find on a specific topic. Then we assign mini-projects for each topic where students actually work on a realistic problem, and that's the way they learn each specific topic.
Throughout the course, they work on two capstone projects. One can be a little bit more foundational, the other might be more advanced. The capstone project should be as realistic as possible as you should use some kind of real-world data set, and the question that students choose to answer should have some real world value. Students need to write a proposal where they state the question, why they care about it, the value of the answer, and who the client is. In the real world, when you're working as a data scientist in industry, you're never working on a problem in isolation. You are typically working to prevent or solve a problem for a business client.
Knowing how to translate a business problem into a data problem and then communicating the results of your analysis back into a business context is a super important skill for data scientists. It’s highly underrated and something that employers always look for. The way we teach that skill at Springboard is by making sure that every capstone project they're working on has the client in mind. The analysis and deliverables should all be targeted for that client.
How do you keep students engaged while they're learning online?
That's a really good question, and this is something that many online education providers are trying to figure out. Assigning mentors is a big part of this for us, because it means that students are being held accountable. Students meet with their mentors once a week, online as we’ve built video calling into our platform. In their weekly calls, we encourage students and mentors to decide on goals for the following week.
Student advisors will also follow up to check in on students’ progress. If you haven’t made some progress over the last couple of weeks, the student advisor will reach out – that kind of human touch often helps many students. When students accomplish specific milestones, they have prompts to set up calls with their advisors. For example, once they update their LinkedIn profile, they have a call with a career adviser who will review their LinkedIn profile and give them feedback.
We’re also always thinking about how to better design our platform and curriculum to motivate students. For example, a lot of students are motivated by seeing their progress as they go through the curriculum, so we built those rewards into the platform. Student do well when they’re aware of their own learning style because they can work with their mentors and their student advisor to make sure we’re motivating them in the right way.
What have you found is the easiest way to land a job as a data scientist?
When you look for a job, especially in tech and data science, you often get the advice that you need to pump your resume full of keywords and then blast it out as widely as possible. That's really not the most effective way to find a job. Referrals are the way to find jobs in tech, and that means building out your network, and then using your network to find jobs, interviews, or referrals to companies that you've already done information gathering and research on.
Students need to be very strategic in the beginning before they send out a single resume. And we’ve built that idea into our career curriculum. For example, students may be required to find a major data science meetup near them, attend, and make five contacts, take five people out for coffee, or schedule an informational phone interview to learn about their company.
One of our students put his data science skills to the test and ran an experiment where he sent out hundreds of resumes to different job sites, and got an acknowledgement ~10% of the time. When he submitted applications through referrals, he got a phone interview 85-90% of the time.
The next class starts May 29th; how are the current students doing?
We’re teaching a couple of hundred students right now, and we have about 50 mentors in our network. Some of those students are getting close to graduation, and then will be focused on finding a job. We accept applications on a rolling basis: however, admissions are quite selective, with about only 18% of students enrolling after they’ve applied. Click here to see if you qualify!
Great, we can’t wait to talk to a graduate!
Welcome to the January 2017 Course Report monthly coding bootcamp news roundup! Each month, we look at all the happenings from the coding bootcamp world from new bootcamps to fundraising announcements, to interesting trends. This month we applaud initiatives that bring technology to underserved communities, we look at employment trends, and new coding schools and campuses. Plus, we hear a funny story about an honest taxi driver. Read below or listen to our latest Coding Bootcamp News Roundup Podcast.Continue Reading →
Kristoffer has been a graphic designer for six years, but after trying out a few UI projects, he realized he liked it better than his current work. Not wanting to quit his job, Kristoffer decided to enroll in Springboard’s part-time online UX Design program to upskill and pivot towards something he was more passionate about. Kristoffer tells us how he managed to squeeze the whole program into one month, how he balanced it with his other commitments, and his plans for the future. He also shares his screen to show us Springboard’s online learning platform!
What was your background before you decided to study UX design at Springboard?
I went to school to be a graphic designer, and I've done that in a professional capacity for about six years now. Through that, I've done UI projects at work, and that is really where I thought, "Oh, I want to pivot into that and stop doing graphic design." It led me to where I want to be, and pushed me into taking an online course to further flesh that out.
Are you studying part-time or full-time, and are you able to work as well? What's your setup for learning?
I'm finished with the course now, but when I did it, I did it part-time, but I really focused on it. Thankfully my job was flexible enough that I had extra PTO, so towards the end I was able to take a week off and just focus on the course.
Other than that, I would do a little bit after work and then more at night after dinner. Instead of watching TV, I would work on the course and take care of what I could that night and then move on the next day. It was really flexible for me.
How long did it take you in total to do the whole course?
It took me a month, but that was like a marathon run for me. I had committed to only doing it for a month, so I had it in my head that I needed to really focus. I work better that way because it is a monthly thing and you can go at your own pace. I could've easily mentally just stretched it out longer or just say "No, I'll get to it tomorrow."
Knowing that I only wanted to do it for a month helped force myself to just do it as quickly as I could and to get as much out of it as I could. If I stretched it out any longer, I feel like in my own learning I would have lost some of it because it would’ve just taken too long. By focusing on it for just one month, I was able to really take it all in and get what I needed out of it.
What made you decide that you needed to do a bootcamp rather than learn on your own through another online-type of resource?
I had a deep background in the visual design side of UI and UX, but I only had very tangential knowledge of the user persona creation, user testing, and wireframing. I hadn't really touched a ton of that. So when I was reading up on different courses, Springboard stuck out to me because I could learn all of the stuff that I either hadn't touched at all, or barely touched.
In terms of my timeline and keeping that in mind, I was thought, "Okay, well my final project is going to rely heavily on what I know already. So I know that if in the first two weeks I can get the first book done, then the last two weeks will be easy for me because I already know all of the programs that I need to complete the project.”
Did you look at a few other bootcamps as well as Springboard? What made you settle on an online bootcamp in particular?
We didn't have a ton of options out here in Las Vegas and I had to keep my job so I couldn't really go anywhere for three months to do an intensive course. So I knew I had to stay online. I did research quite a few, and they all sounded wonderful, but a lot of it was either not going to be fast enough, or it was more of "This is a three-month program." I needed something that I could basically do it as fast or slow as I wanted, and that's where Springboard came in handy.
What was the application process like when you were applying?
I think they open it up to everybody who is willing, but I think if you don't have much of a background in it, they will tell you that you’ll need to take your time on each course. For me, I remember I had to fill in an application saying why I wanted to do it, and if I did have any experience, what that was. I put my background in and I linked it to my LinkedIn account. Springboard basically looked at my resume and said, "Oh, okay. He's done this, this, and this. He's good to go."
What actual technologies and subjects does the UX design program cover?
It covered idea creation, minimum viable product, competitive analysis, user persona creation, wireframing, visual design, logo design, and color palettes.
Did they cover any front end programming languages? Did you cover HTML and CSS?
We didn't cover that. I have some knowledge of that just through my work experience, but Springboard didn't cover that in a classroom setting. I think the culmination of your projects would rely on high fidelity mockups, and then some interactive prototypes using invision or something like that, but no HTML was not really gone over. It was mentioned, so it wasn't like it was hidden, but we didn't go over it.
What was the actual learning experience like at Springboard? Did you watch recorded lectures or did you have one-on-one time with a mentor? How does that work?
It's a wonderful blending of both. You get a phone call with your mentor once a week and you can also email them. They're usually pretty open to email, and they're flexible on calls too. For the rest of the learning, it's a combination of PDFs and links that you read through and then go over.
There’s also Lynda.com videos and Skillshare videos, which you don't have to pay for because they are part of the course. Once you get through those, you've got some projects to work through. Each chapter has a project and then at the end you have a culmination of those learnings in a capstone.
How often were you meeting with your mentor? Since you wanted to do it in such a short time, was the mentor able to accommodate that?
Yes, he was very accommodating. I told him at the outset that I was planning to do this in one month. I knew it sounded crazy, but I had looked through the course and when I talked to him I just reinforced that "I'm going to need to do this only for one month,” and he was really flexible. We talked once a week at the beginning and then we talked maybe two extra times at the end because he knew I needed to get things done before a certain date.
Would you like to share your screen now and give me a little demo of what the learning portal looks like?
So here is my back end when I log in and then right here is all of the chapters. You read through all the information and this is your intro when you first sign up. Then as you go through, each of these activities would not be grayed out, and you would just click through to complete them. Once you're done it says completed.
Did you have a checklist where you could see which activity you've finished and which ones you still had left to do?
Yeah. I wrote down on a notepad what I knew I had left so I could extract stuff out. But when you're in the midst of going through the course, it defaults you back to basically where you left off. So it knows what you have completed and then it brings you to what's up next so that you don't have to scroll through every time.
Could you submit your projects or assignments through the portal? How did that work?
Let me find one that has a project. So when I got to this portion of the course, it was not grayed and then instead of "Submitted," the button said "Submit project." When you click that a little box comes up for a link and you just paste the link in there to where you have your project hosted. I used Google Docs for 99% of what I did.
What kind of programs did you use to actually build and create your projects?
For the initial parts where I was submitting ideas and chart based stuff, I did Google Docs and Google Sheets. Then as we got into the more visual side of things, I used Extensio and Balsamiq. Balsamiq was for wireframing, and Extensio lets you build user personas that look really nice. I can show you an example of that if you want.
Yeah, that would be cool if you can show me an example.
So Extensio lets you build something that’s a nice visual, quick overview of a persona that you create. They also have templates in there that I used, for example they let you do empathy maps.
This is my case study that I did for my final my capstone project. I used Illustrator to make my competitive analysis because I wanted it to be super simple. I don't like the way that normal spreadsheets tend to look even once you adjust for cell sizes. It was a fairly fast project.
What was your capstone project?
For my capstone I designed an app that allows users to catalog and keep track of items that they have in their home or apartment for insurance purposes. So in case of fire or water damage, or even robbery, you have a list of your items that you could submit to insurance for reimbursement checks.
Was that an original idea you came up with yourself?
Overall, when using the Springboard platform, how did you find it was different from using some of the free self-guided online resources that are out there?
For me it was that old feeling of when you pay for it, you feel like you need to get the value out of it. So if I was just looking at YouTube videos, I could go down a YouTube hole and end up not learning what I wanted to learn. I could just be clicking and then watching the next step in playlist. This guided me down what I know I needed to learn.
With YouTube or other online resources, I would feel like, "I don't like the way that they're teaching these so I'm just going to move on to something else," and eventually that did not work for me. So for Springboard it was a little bit of hand-holding. It gave me the steps I needed to take to fully do user experience research for a new project or a new feature and I liked that hand holding.
I also took online classes when I was in college because some of them were only offered online, and this was so much better than that.
How many hours per week did you find yourself spending on the Springboard curriculum?
Early on I broke it into two separate sets of two weeks. The first two weeks was the main lead up, which was everything up to the wireframing. It was the MVP persona, the competitive analysis, all of that. For those two weeks I probably spent around 10 to 12 hours a week on the course. The third week I was off work, so I was able to put in basically 30 to 40 hours. Then the final week I was back at work but most of my stuff was done. I was just refining my capstone project with input from my mentor and users that had tested it. So that week I probably put in maybe 12 to 15 hours.
How does Springboard help you or give you advice about how you can use this knowledge in your future career?
Throughout the course, they'll mention various Lynda courses, and explain how this will apply in an office setting. They'll say, “you're learning user research where you're having them test it in a room with you and cart sorting and stuff, but it’s not necessarily how everything will go.” Some companies are so large that you will never touch that aspect of it.
It's good for you to know it so that you can talk with those people and understand the data that they're giving you and how it influences what you do. Towards the end, they start explaining, "Here's how you set up a UX resume and here are the programs you need to know.” If you're going to focus more on UI and visual design, you'll want to know Photoshop and Sketch and Illustrator. If you know Sketch, you probably don't need Illustrator. Springboard does say, "Know the Adobe Suite, know Sketch and you'll be set in terms of visual." For the others, it's a lot of Word Docs or Google Docs; anything that you can have a full office suite of spreadsheets, PowerPoints and Word processing.
Did they offer any job placement help if you're wanting to find a job using your new skills?
I think they help you with links in terms of good search engines to use for this particular field. Your mentor can be pretty helpful in that regard too. Even if it isn't necessarily finding you a job, he can help look over your resume, look over your portfolio, make sure that you're hitting the things that need to be talked about.
What was your goal when you decided to go through this program? Were you planning to get a new job or did you want to upskill for your current job?
It was definitely to get a new job. I've been in the same job and the same skill set for about four years now and felt, "It's time for a switch." At the same time, I was realizing how much I enjoyed the UI side, because I had some freelance projects that I was working on that were UI focused. I thought, "This is so much more fun than what I'm doing right now.”
I wanted to pivot and move into a startup role. So I'm currently looking and interviewing, and this is already helping. It reinforces the fact that I do have experience in some of this stuff. Having the course behind that, people see, "Oh, okay he's serious about it."
So what are the types of roles that you're looking for that you would ideally like to get?
I would love to get a UI design role or a visual design role. I still love that aspect of it. I love playing in Photoshop, playing sketch, and doing interactive mockups. I enjoy all of those parts of it building buttons and figuring out how it should look for the end user. That's really where I've concentrated my search. I've had a few interviews for UX based stuff – less on the design side, more on the how it's going to flow side. It's been incredibly informing, but I can see I'd much rather go into UI visual.
What advice do you have for someone who is considering doing an online bootcamp like the one you did? Any tips you might have for staying motivated and engaged?
I think the first tip I have is if you feel like one of the course videos is going to a little too slow, usually somewhere in the settings on the video player there's a way to speed it up and that helps a lot. Because some of them had very intensive talking. It was deliberate talking. So I believed, "Okay, I can speed that up to one and a half times the speed and get done with this quicker,” and it would still be fast enough that I could get through it; but not too fast where I didn't get anything from it.
On top of that, I think you should know how long you want to be in the program, even if it's not a month, just know how long you want to be in it and make sure you work towards that. Don't let it become something that you let just fall off. Focus on it and do it, because even if you don't end up using it in your career, you will at some point. Even if you don't go into UX design immediately, you will use what you learn I think at some point.
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