Sneak Peek: Practical Machine Learning for Engineers

Check out the first 20 minutes of our previous Practical Machine Learning training taught by Juan M. Huerta, Senior Data Scientist at PlaceIQ.

20:22

Join us for our next 3-day training! November 10th-12th. This course is designed to help engineers collaborate with data scientists and create code that tackles increasingly complex machine learning problems. The course will be taught by Rachit Srivastava (Senior Data Scientist, PlaceIQ) and supervised by Juan.

By the end of this training, you will be able to:


  • Apply common classification methods for supervised learning when given a data set

  • Apply algorithms for unsupervised learning problems

  • Select/reduce features for both supervised and unsupervised learning problems

  • Optimize code for common machine learning tasks by correcting inefficiencies by using advanced data structures

  • Choose basic tools and criteria to perform predictive analysis


We screen applicants for engineering ability and drive, so you'll be in a room full of passionate devs who ask the right questions. Applicants should have 3+ years of coding experience, knowledge of Python, and previous exposure to linear algebra concepts.

You can apply for a seat on our course page.