Springboard vs. DataCamp: Which Is a Better Online Learning Platform?
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Ready to kickstart a new career in tech but not sure which online learning platform is right for you? Learn more about the main differences between MOOCs and mentor-led online bootcamps in this guide.
As the cost of higher education continues to rise, online courses and bootcamps have in recent years become a viable alternative for those who want training in highly technical and well compensated fields—without the steep price tag or years-long time commitment.
Spurring the e-learning revolution is the growing demand across all industries for software engineers, UX designers, data scientists, and cybersecurity professionals, which has resulted in courses and bootcamps that promise to prepare students for those roles—often from the comfort of their home, at the student’s own pace, for a low cost.
The rise of online bootcamps has been a good thing, with The New York Times reporting that virtual learning has been a “great equalizer” for adults and has made training and upskilling more accessible. During the Covid-19 pandemic in particular, research found that e-learning has the potential to close a longstanding skills gap and democratize user engagement. Many courses, designed specifically with a bootcamp-to-workforce pipeline in mind, have also optimized their programs to focus on the skills students need in order to land the job they want, thus maximizing efficiency and giving graduates a competitive advantage.
What Is Springboard?
Springboard is a San Francisco-based edtech company that prepares students for some of today’s more competitive and coveted careers, all while offering a first-of-its kind job guarantee. Every student gets a six-month runway after graduating to secure a role in their industry—if they don’t, students receive a refund on 100% of their tuition.
Springboard offers bootcamps and short courses in UI/UX design, data science, data analytics, software engineering, machine learning, and cybersecurity. All Springboard bootcamps are 100% online, self-paced, and take six-nine months to complete. During each bootcamp, students are matched with an industry mentor who guides them throughout the program through regular one-on-one video calls. A Student Success Manager is also available to handle logistics queries, create study plans, and help students stay accountable to their learning goals.
Before and after graduation, Springboard’s career coaches support students in their job searches and networking, help prepare them for interviews, and facilitate their transition into the workforce.
What Is DataCamp?
DataCamp is a New York-based edtech company that hosts hundreds of massive open online courses (MOOCs) related to data science. The platform is unique among edtech platforms in that its career tracks and skills-based courses are geared solely towards data-related professions such as data analyst, data engineer, machine learning engineer, quantitative analyst, Python programmer, and R programmer.
All of DataCamp’s courses are 100% online and, like most MOOCs, take a hands-off approach to instruction, with courses consisting of video lectures and coding exercises.
Students can choose to approach DataCamp by career track, which involves taking a series of courses curated by DataCamp that, when strung together, amount to a technical education, or they can choose courses based on skill. For example, if a student enrolls in the data analyst career track, they would take a 77-hour course that covers the programming language R, data manipulation with dplyr, data visualization, importing data in R, cleaning data in R, and relational databases in SQL. If they choose to enroll by skill, they could choose from hundreds of hyper-specific courses, such as statistics fundamentals, text mining, and string manipulation.
Springboard vs. DataCamp: What Are the Main Differences?
There are a few fundamental differences between Springboard and DataCamp.
- DataCamp offers MOOCs, which are optimized for the highest number of enrollments possible. This means that there’s no limit to the number of students who can enroll in a course and most of the courses take a hands-off approach to instruction because it’s not possible for a single instructor to keep up with every person in the course. Students learn at their own pace, have minimal to no interaction with instructors, and on completion of a program are usually left on their own to determine next steps. DataCamp is also limited to data-related courses, with students having the option to hop around between courses and chapters.
- Springboard follows a bootcamp model, which means classes are capped to ensure a manageable instructor to student ratio and follow a structure that ensures that students understand the fundamentals of each profession before they advance to more challenging skills. Springboard’s bootcamps—which span the most in-demand tech professions such as software engineering, data science, machine learning engineering, cybersecurity, and UX design—also take a more holistic approach to education, combining a comprehensive curriculum with self-paced instruction, video lectures, readings, capstone projects, work sprints that mimic the real-world work experience of a profession, and one-on-one regular calls with an industry mentor.Springboard students are often looking to upskill or change careers, which is why every student is given access to a built-in support network of mentors and career coaches to keep them accountable during the course and to help them move into the workforce upon graduation.
Springboard vs. DataCamp: Learning Format
Both Springboard and DataCamp are 100% online and deliver most of their educational materials through video lectures and readings. DataCamp is also known for offering interactive coding challenges that students can do within their web browser.
Students go at their own pace, with the average Springboard bootcamp taking anywhere from six to nine months and requiring a time commitment of 15-25 hours a week to successfully complete the coursework, while the average DataCamp course ranges from 12 hours for a short course on a specific topic (E.g. Image Processing with Python), to 88 hours for the Data Science career track.
Springboard vs. DataCamp: How Much Does It Cost?
When it comes to online courses and bootcamps, the adage that you get what you pay for often rings true. Free or low-cost courses can be accessible, but often lack personalized support from instructors and mentors. Higher-cost courses can have a higher barrier to entry, but typically come with a comprehensive support system.
- DataCamp offers a tiered pricing structure—$25/month grants students access to all instructional videos and a community chat, while $33.25/month gives students access to instructional videos as well as assignments and priority customer support. There is also a free version that gives students access to the first lesson of each course.
- Springboard’s courses are around $10,000, with discounts and scholarships available if certain criteria are met. Springboard’s introductory courses, which give students a taste of a field at a fraction of the time commitment, start from $349.
Springboard vs. DataCamp: Job Outcomes
One of the indicators of an effective bootcamp or online course is whether students land an industry job upon graduation.
- DataCamp doesn’t publish data on how many of its graduates go on to secure jobs as data scientists. However, the platform is popular among businesses who use it to help employees upskill and fill in data-related skills gaps.
- Springboard offers a first-of-its-kind job guarantee for all graduates, with all-encompassing courses that prepare students for the workforce. If a student does not secure a job related to their field of study within six months of graduation, Springboard will offer a full refund on tuition.
Springboard vs. DataCamp: Pros and Cons
In the saturated e-learning market, both Springboard and DataCamp have emerged as significant players because their courses offer many benefits. But what works for one student may not work for another.
- Pros: DataCamp’s courses are relatively low cost, and its interactive coding platform gives students the opportunity to practice programming languages and tackle data wrangling challenges within a responsive web browser. Its data science-centric approach also means that its courses are comprehensive, with mini courses and tutorials on nearly every facet of the technical skills required in the data science profession. This makes DataCamp particularly attractive to businesses and those who already have a background in data science who simply want to brush up on a skill or fill a gap in their training.
- Cons: As with most MOOCs, DataCamp’s courses lack interactivity with an instructor and don’t include mentorship or career guidance, which means if you get stuck during the learning process or want individualized feedback on your work, it can be hard to get the help you need. The lack of support and career development roadmaps can also make the study-to-workforce transition particularly challenging, with research showing that many people who start MOOCs often don’t finish them, and even those who do find it hard to be consistent with their studies.
- Pros: Springboard’s courses are created by industry experts and are designed to meet the end-to-end needs of students, from introducing newcomers to the basics of a profession to offering a project-driven, comprehensive curriculum that teaches the skills students need to land the job they want. Mentors and careers coaches also support students through capstone projects, industry networking, and job searches, ensuring that every graduate is equipped with both the hard and soft skills required to get on a recruiter’s radar and ace the job interview. This approach is applied to all of Springboard’s courses, which extend beyond data science and machine learning engineering to include software engineering, cybersecurity, and UI/UX design.
- Cons: Springboard’s courses aren’t a silver bullet to a career change. Even with a holistic and mentor-supported approach to online education, it ultimately falls on students to put in anywhere from 15-25 hours a week in study and practice in order to successfully complete a course and build a competitive portfolio that will help them stand out from the crowd.
Not ready to enroll just yet? Read more about the factors you should consider while picking a program in our bootcamp criteria guide.
Disclaimer: We’ve worked hard to ensure the information in this comparison guide is accurate and up-to-date. However, mistakes happen. If you spot an error, please get in touch with us at firstname.lastname@example.org and we’ll correct it right away.
Since you’re here…
Interested in a career in data analytics? You will be after scanning this data analytics salary guide. When you’re serious about getting a job, look into our 40-hour Intro to Data Analytics Course for total beginners, or our mentor-led Data Analytics Bootcamp—there’s a job guarantee.