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Meet a few of our alumni

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Data Science Career Track

  • Python
  • Data Wrangling: Pandas, APIs
  • Statistical Inference
  • Machine Learning (Supervised & Unsupervised)
  • MapReduce, Spark, NoSQL, MLlib

Want to learn about hiring a Springboard graduate? We'll reach out. No placement fees.


What is your admissions process?

Springboard takes great pride in the caliber and skills of our graduates. To ensure that students are adequately prepared for the rigor of our curriculum, we have a comprehensive application process that assesses their technical and communication skills. Springboard students complete a take-home skills assessments and engage with our Admissions team for an additional screen that evaluates their communication and motivation.

This process helps us ensure that all admitted students have the aptitude, background knowledge, and motivation to succeed in our bootcamp programs.

What are your student backgrounds? Do they have college degrees?

All Springboard students who are eligible for the Job Guarantee have completed secondary education and hold at least a Bachelor's degree from an accredited college or university. 50% of our students select us instead of pursuing a graduate degree.

What is the Springboard experience like? 

Springboard provides rigorous 500+ hour programs in Data Science, UX Design, and Software Engineering. The programs typically take students between six to nine months to complete. We enable students to go at their own pace as most of our students work part-time or full-time jobs outside the program.

Springboard students work with 3 individuals throughout the course: 

  • Industry Mentor - every Springboard student is matched with a top professional that works with them 1:1 on a weekly basis to assess progress, facilitate introductions in the industry, and provide them with valuable context on how the material they’re learning applies in industry.

    • Fun fact: We screen 12 mentors for every 1 that we hire, so it’s a competitive pool of top talent. We have more Data Science and UX Design talent in our mentor pool than any faculty at any university around the world.

  • Career Coach - every student works with a Career Coach to learn how to best tell their story when applying for jobs. Career Coaches help them improve their interviewing skills and application materials. 

  • Student Advisor - students get support from Student Advisers who help them plan out the course work and ensure they’re meeting their coursework goals.

The majority of our coursework is project-based, enabling students to demonstrate their mastery of subjects in their portfolio. Each course is completed with a Capstone Project that showcases their skills in a real-world application.

Our curriculum, alongside the mentorship students get, ensures that our graduates are ready to hit the ground running when they join your company. 75% of our students who make a career transition from our program get employed while they’re in the program - so we’re confident that we’re only teaching what you’re looking for.

Where are Springboard students located?

Springboard students are distributed across the world, but the majority reside in the United States. The greatest number of students reside in (or are willing to relocate to) the 22 major cities in the country.

What does your Placements process look like?

After you submit a request with what you’re looking for, someone from our team will reach out to you. We’ll learn more about your business and hiring needs, and then send you the profiles of students we think best match that. Interview them as you normally would and let us know what you think!

Is there a cost associated with Springboard Placements? 

No, there are no fees associated with Springboard Placements. We’re in it to ensure that you assemble the best team possible!

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Data Analytics Career Track

  • Descriptive Statistics, Correlations, Regression, Confidence Intervals
  • Excel, SQL, Mode SQL
  • Python, Jupyter, Seaborn, Matplotlib
  • Tableau, PowerBi
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Machine Learning Career Track

  • Machine Learning Engineering
  • Pandas, scikit-learn, Keras, TensorFlow, Spark/PySpark, Luigi, Containers, AWS
  • Data Wrangling at Scale
  • Deep Learning
  • Keras, TensorFlow, PyTorch
  • NLP, Computer Vision 
See curriculum

UI/UX Career Track

  • Design Thinking 
  • User Research
  • UI Design
  • Interaction Design 
  • Wire-framing
  • Design Sprints
  • Sketch, Adobe XD, InVision, Figma, Principle
See curriculum

UX Design Career Track

  • Design Thinking
  • User Research 
  • Wire-framing 
  • Design Sprints
  • Tools: Sketch, Adobe XD, InVision 
See curriculum

Software Engineering Career Track

  • Web Development
  • JavaScript
  • jQuery 
  • Python, Flask, SQL 
  • Node and Express
  • ReactJS & Redux

What skills our students learn

Our students gain the job-ready skills by working on real life projects

"I liked that there was a human factor, which was readily available advisers and coaches, a weekly session with my mentor, and lots of other avenues to reach out to another person."

Diana Xie

Got a job as ML Engineer at

Got a job as ML Engineer at

Diana Xie

"I liked that there was a human factor, which was readily available advisers and coaches, a weekly session with my mentor, and lots of other avenues to reach out to another person."

Got a job as ML Engineer at

Diana Xie

"I liked that there was a human factor, which was readily available advisers and coaches, a weekly session with my mentor, and lots of other avenues to reach out to another person."

No placement fees. Hire our students now

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Why you should hire from Springboard?

Our students are..

  • Ready to deliver - Our graduates’ skills and job readiness have been assessed through their course projects and mock interviews, which are set to standards required in the workplace. 
  • Diligent and passionate - Our graduates have shown a commitment to making a career transition by successfully learning a new skill set and completing a rigorous program that requires discipline and persistence. 
  • Adaptable and have a growth mindset - Our graduates know that technology is constantly changing and approach their learning and work with that expectation.

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Data Engineering Career Track

  • Big Data (Hadoop, Spark)
  • Cloud Data with Azure (Data Factory, CosmosDB, HDInsight, Databricks)
  • Data Pipelines with Airflow
  • Virtualization and Containers (Kubernetes, Docker)
  • Streaming Data (Kafka)
See curriculum

Cyber Security Career Track

  • Identity and Access Management
  • Information Security Audit
  • Network Security
  • Physical Security and Authentication
  • CompTIA Security+ Certification