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Avg Rating:4.89 ( 58 reviews )

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Recent Springboard Reviews: Rating 4.89

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1 Campus

Online

Learn to design great products by focusing on the user. Go from beginner to launching a UX portfolio with a UX mentor in the field helping you create a real-life capstone project.

Course Details

Payment Plan
$399/month
RIn PersonFull Time

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.

Course Details

Payment Plan
$499/month
Python, Data Science, GitOnlinePart Time15 Hours/week

Course Details

Minimum Skill Level
You should have a strong background in Probability & Statistics, and should be very comfortable programming in at least one language.
Data Science, SQL, ExcelIn PersonFull Time
Python, Data Science, Git, SQLOnlinePart Time

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.

Course Details

Payment Plan
$1000/month
Minimum Skill Level
Comfortable programming and comfortable with statistics.
Placement Test
Yes

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Our latest on Springboard

  • Meet the Data Science Career Track at Springboard

    Liz Eggleston5/8/2017

    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).

    Q&A

    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!

    Read more Springboard reviews and be sure to check out the Springboard website!

    About The Author

    Liz pic

    Liz is the cofounder of Course Report, the most complete resource for students considering a coding bootcamp. She loves breakfast tacos and spending time getting to know bootcamp alumni and founders all over the world. Check out Liz & Course Report on Twitter, Quora, and YouTube

  • Episode 10: January 2017 News Roundup + Podcast

    Imogen Crispe1/31/2017

    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 →
  • Alumni Spotlight: Kristoffer Daniels of Springboard

    Imogen Crispe10/27/2016

    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!

    Q&A

    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?

    Yes.

    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.

    Find out more and read Springboard reviews on Course Report. Check out the Springboard mentored UX design workshop.

    About The Author

    Imogen crispe headshot

    Imogen is a writer and content producer who loves writing about technology and education. Her background is in journalism, writing for newspapers and news websites. She grew up in England, Dubai and New Zealand, and now lives in Brooklyn, NY.

  • March Coding Bootcamp News Roundup

    Harry Hantel12/15/2016

    Welcome to the March News Roundup, your monthly news digest full of the most interesting articles and announcements in the bootcamp space. Want your bootcamp's news to be included in the next News Roundup? Submit announcements of new courses, scholarships, or open jobs at your school!

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  • Learn Data Science at These 20 Coding Bootcamps

    Harry Hantel5/22/2017

    You don’t have to be a data scientist to read into these statistics: A McKinsey Global Institute report estimates that by 2018 the US could be facing a shortage of more than 140,000 data scientists. The field of data science is growing, and with it so does the demand for qualified data scientists. Sounds like a good time to pursue data science, right? No kidding! Data scientists make an average national salary of $118,000. If you’re looking to break into data science, or just trying to refresh and hone the skills you already have, Course Report has you covered. Check out this comprehensive list of the best data science bootcamps and programs in the U.S. and Europe for technologies like Hadoop, R, and Python.

     

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