TBD
11 Months, Online
6-8 hours per week
$3,300*
US$50 application fee
Machine learning algorithms are transforming systems, experiences, processes, and entire industries. It’s no wonder that business leaders see these data-driven technologies as fundamental for the future—and that practitioners fluent in both fields are in high demand.
At Columbia Engineering, we are fascinated by their world-changing potential, and we’ve created the Postgraduate Diploma in Machine Learning (E-Learning), in partnership with Emeritus, to help students understand the fundamentals of AI and machine learning and how to apply them to solve complex, real-world problems.
The average Teacher-Student ratio in the program is 1:300.
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John has a PhD from Duke and has been a postdoctoral researcher in the Computer Science departments at Princeton University and UC Berkeley.
John Paisley’s research focuses on developing models for large-scale text and image processing applications. He is particularly interested in Bayesian models and posterior inference techniques that address the big data problem.
Jacob is a mathematics educator, with a PhD in mathematics education from Columbia University. Currently, he teaches mathematics and computing in the Department of Natural Sciences and Mathematics at The New School in Manhattan, New York.
He loves all kinds of problems in mathematics and computing, but especially those dealing with Natural Language Processing and pedagogical problems in the mathematics classroom.
In addition to Course Leaders, industry experts focusing on data science share their knowledge and experience through periodic guest lectures.
Upon successful completion of the diploma, participants will receive a verified digital diploma from Emeritus Institute of Management, in collaboration with Columbia Engineering Executive Education
Get CertifiedApplicants must be at least 21 years of age and will be required to submit:
ENGLISH LANGUAGE PROFICIENCY REQUIREMENT
All candidates who have received their bachelor’s or other degree or diploma from an education institution where English is NOT the primary language of instruction are required to demonstrate English language proficiency through ANY ONE of the following methods
Carleton Smith is a Data Science educator and practitioner in Chicago, IL. Carleton has taught several data science courses at General Assembly and has served as the Lead Data Science Instructor for a number of corporate training engagements. Before becoming an instructor, Carleton worked on data projects in the finance, health care, and medical research domains. Carleton has an MS in Predictive Analytics from DePaul University and a BS in Entrepreneurship from Indiana University’s Kelley School of Business.
Jacob is a mathematics educator, with a PhD in mathematics education from Columbia University. Currently, he teaches mathematics and computing in the Department of Natural Sciences and Mathematics at The New School in Manhattan, New York. He loves all kinds of problems in mathematics and computing, but especially those dealing with Natural Language Processing and pedagogical problems in the mathematics classroom.