From Amazon’s shockingly on-target shopping recommendations to Google’s increasingly sophisticated translation tools, artificial intelligence (AI) is no longer the stuff of sci-fi—it’s become a regular part of every consumer’s daily life.
This mainstream adoption of AI-powered products coupled with ever-bigger bets by tech and tech-adjacent companies has led to an AI talent shortage that many experts predict won’t be alleviated for years. Consider this:
- The global machine learning (ML) market is estimated to grow from $1.4 billion in 2017 to $8.8 billion by 2022. (Source: Research and Markets)
- AI is projected to create 2.3 million jobs by 2020. (Source: Gartner)
- From 2015 to 2018, the number of AI-related job postings on Indeed increased by 119 percent. (Source: Indeed)
- Machine learning is the most in-demand AI skill. (Source: Indeed)
All of that is driving AI pay sky high. Machine learning engineers earn an average salary between $125,000 and $175,000. Salaries at the 10 highest-paying companies for AI engineers start above $200,000 a year.
At Springboard, we’re focused on filling the gaps in the current job market and helping people around the world achieve their career goals through accessible, flexible, lifelong learning. To that end, we’re launching the Machine Learning Engineering Career Track, an intensive program that will equip you to transition into a role as a machine learning engineer.
What makes this course unique?
This is the first AI/ML program with a job guarantee. With support from our career services team, we’re confident that you will find a job within six months of completing the course. But if you don’t, we’ll refund your tuition. (We’ve successfully placed hundreds of students in our Data Science Career Track course and have yet to issue a refund.)
And while graduate programs and other online courses focus on AI/ML concepts, we want you to apply what you’re learning. Yes, our curriculum is rigorous and deeply technical, teaching you the foundations of machine learning and deep learning. But it’s also hands-on.
We don’t just teach you ML, we let you do ML. Of the 400 hours of work we estimate it will take to complete this course, 100 hours go toward capstone projects. You’ll build and deploy large-scale AI systems—with guidance from an experienced machine learning engineer currently working in the industry.
All of our courses include one-on-one mentoring from a professional in the field. In this case, that means AI experts from companies like Google, Facebook, and Airbnb. You’ll get insight into the machine learning engineer interview process and the day-to-day responsibilities.
To be clear, this is an advanced course and it is not for everyone. In fact, to enroll you must have a background in software engineering and meet certain prerequisites.
If you do have that background and want to transition into one of the most exciting, in-demand, and highly compensated tech careers, you can find out more about the new Machine Learning Engineering Career Track here.