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Machine Learning Engineering Career Track

Training overview
Professional Course
6 months

Course description

Machine Learning Engineering Career Track

A unique approach to a machine learning curriculum. Knowing machine learning and deep learning concepts is important but not enough to get you hired. According to hiring managers, most job seekers lack the production engineering skills to perform the job.

More than 50% of the Springboard curriculum is focused on production engineering skills. In this course, you'll design a machine learning/deep learning system, build a prototype and deploy a running application that can be accessed via API or web service. No other bootcamp does this.

Who should attend?

This Machine Learning bootcamp is designed for people with strong software engineering skills and industry experience, who want to become Machine Learning Engineers.


  • 1+ year of professional experience working in software engineering and development OR data science using a general-purpose OOP language, such as Python, Java and C++
  • OR A Master's or PhD degree in CS, Math, EE, Physics, Data Science, Informatics, Economics, Operations Research, Financial Engineering, Applied Stats or other degree that involves extensive programming experience.

Training content

The curriculum is split into 11 units covering the topics below:

  • Battle-Tested Machine Learning Models
  • Deep Learning
  • Computer Vision and Image Processing
  • The Machine Learning Engineering Stack
  • ML Models At Scale and In Production
  • Deploying ML Systems to Production
  • Working With Data


The full tuition of the program is $8,940. If you pay upfront, you will get an 11% discount. Remember, if you don’t get a job within 6 months of completion, you’ll receive a full refund.

About Springboard


Springboard is an ed-tech company based in San Francisco. We’re on a mission to bridge the world’s skills gap by helping as many people as possible access high-quality, affordable education that they can translate into new-economy roles. We offer online...

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22 Battery Street
Ste. 1100
94111 San Francisco California

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