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Below is our recent interview with Jonathan Heyne, General Manager, Data Science and AI Programs at Springboard:
Q: Could you provide our readers with a brief introduction to Springboard?
A: Springboard is an online school for learning 21st-century skills in fields like data science, AI, UX design, digital marketing, and business analytics. We’ve served thousands of students around the world through a combination of expert-curated curricula and one-on-one mentorship.
In all of our self-paced courses, Springboard students develop job-ready skills that they display in industry-worthy capstone or portfolio projects. And throughout the entire process, students receive personalized support from their industry expert mentor, as well as Springboard’s resident advisors and the larger student/alumni community.
Q: You’ve recently launched the first AI / Machine Learning course with a job guarantee; could you tell us more about this?
A: This course is designed by and for engineers. In particular, this is a course for people who want to become Machine Learning Engineers (MLEs).
MLEs are people who actually build the large-scale Machine Learning (ML) and Deep Learning (DL) systems that we all use: whether that means Amazon’s recommendation engine or Google’s language translation. In some companies, MLEs start with prototypes built by Data Scientists and do the engineering work to take them to production. In other companies, MLEs do both the work of prototyping and deploying AI systems. As a result, production and deployment engineering skills are at least 50% of this role.
Three years ago, to be an MLE you could be a software engineer who knew some ML concepts. Today, that bar is much higher. An MLE today is a strong software engineer who not only understands the latest ML and DL algorithms, but who is also able to deploy applications into production in a stable, scalable, and reliable way using sophisticated large-scale tools such as SparkML, TensorFlow and PyTorch.
In this Springboard course, we teach ML and DL techniques: not just “old-school” ML such as regression and random forests, but new algorithms such as XGBoost and Catboost, and DL architectures such as RNNs, CNNs, and LSTMs.
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Q: But what really makes this course different is that it’s the only AI program that teaches production engineering skills?
A: As they work on this course, students will choose a Capstone Project that’s divided into two phases:
1. Build an ML or DL prototype, typically in a Jupyter notebook. This work will be done in Python using tools such as scikit-learn, PySpark, or TensorFlow.
2. Implement all the engineering required to take that prototype to a large-scale production application. That includes designing a solution architecture, implementing the data pipelines, and creating an API. The end result is not just a Jupyter notebook, but a running application that can be accessed via API or web service
Springboard will provide all of the cloud infrastructure necessary to build and deploy student projects.
This is also the first (and only) AI / machine learning course with a job guarantee. We’re confident that our students will find a job within six months of completing the course, and are backing this with a promise – if they don’t, we’ll refund their full tuition. Our career services team successfully helped hundreds of students in our Data Science Career Track course find jobs, and have yet to issue a refund!
Q: Other than that, what other courses are available on your platform? Which ones are the most popular?
A: We also offer courses in data science, UX design, business analytics, and digital marketing. Our most popular courses are the Data Science Career Track, UX Design, and the UX Design Career Track.
The career tracks are six-month-long programs with job guarantees, ranging in duration from 350+ to 550+ hours. The job guarantee for all of them is similar – a job in 6 months or your full money back. And as mentioned, we haven’t issued a refund yet.
The UX Design skills track course is a three-to-four-month, 120+ hour program that teaches the foundations of UX design, familiarizes students with different design tools, and helps them build their portfolio.
All our courses are online, self-paced, and mentor-led. We match each student with one mentor, based on the student’s availability and learning goals. The two have weekly calls to discuss coursework, projects, career steps, or anything else of interest.
Q: Why is one-on-one mentorship the best way to learn?
A: Learning with a mentor not only helps you build skills faster, but it also enables career growth. Everyone learns differently. With these mentor calls, students get to focus on what’s important to them. Also, all of Springboard’s mentors are actively working in their respective industries, and share with their mentees real-world insights. Plus, mentors give students networking and career-related advice. Some of Springboard’s mentors have even hired their mentees after graduation!
Q: What does it take to enroll in Springboard’s AI/Machine Learning Career Track? How does it work?
A: To enroll in our AI/ML course, you need to have solid software engineering skills, either by working as a professional software engineer or through contributions to open-source projects and other personal projects. This course is heavily focused not just on learning ML and DL, but on creating actual production-ready applications, so strong engineering chops are a must-have.
The application process itself has two steps. You fill out a short application form (10-15 minutes). Then, if you’re a fit, we’ll send you a challenge to test your software development skills, which takes up to three hours to complete. If you pass the challenge – you’re in and we’ll send you a registration link!
Recommended: Q: What are your plans for the future?
A: We’re currently hyper-focused on launching this course and setting up our newest students for success. We’re also constantly working on teaching our students the most up-to-date skills needed in the market, so we’ll be updating a few of our courses to reflect this as well as our students’ and mentors’ feedback. Other than that, we have a few exciting projects and partnerships in the pipeline… Stay tuned!
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