19 June 2019
9 Months, Online
6-8 hours per week
*Payable in 2 equal installments
Non-refundable application fee: USD 50
PRE-REQUISITES: The diploma requires an undergraduate knowledge of statistics, (descriptive statistics, regression, sampling distributions, hypothesis testing, interval estimation, etc.) calculus, linear algebra (vectors, matrices, derivatives), and probability.
Artificial intelligence (AI) and 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 and Artificial Intelligence, 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.DOWNLOAD BROCHURE
John has a PhD from Duke and has been a postdoctoral researcher in the Computer Science departments at....More info
Ansaf received her PhD in Computer Science from the University of Orleans, France....More info
Carleton Smith is a Data Science educator and practitioner in Chicago, IL. Carleton has taught several data science courses at General...More info
James H. Faghmous is a visiting assistant professor at Stanford University where he researches and mentors...More info
Jacob is a mathematics educator, with a PhD in mathematics education from Columbia University. Currently, he teaches...More info
David holds a B.S. in Finance, Information Systems and Statistics from the University of Florida, has served...More info
*Course Leaders are subject to change
In addition to Course Leaders, industry experts focusing on data science share their knowledge and experience through periodic guest lectures.
Note: All product and company names are trademarks™ or registered® trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.
Upon successful completion of the diploma, participants will receive a verified digital diploma from EMERITUS.Get Certified
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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.
Ansaf received her PhD in Computer Science from the University of Orleans, France. She was an Associate Research Scientist at the Columbia University’s Center for Computational Learning Systems and served as an adjunct professor with the Computer Science department and the Data Science Institute. Ansaf’s research interests lie in machine learning and artificial intelligence. She has done research on frequent patterns mining, rule learning, and action recommendation and has worked on projects including geographic information systems and machine learning for the power grid. Her current research interest includes crowd sourcing, medical informatics and education.
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.
James H. Faghmous is a visiting assistant professor at Stanford University where he researches and mentors on applying artificial intelligence to emerging population health problems.James received his PhD in computer science from the University of Minnesota where his dissertation on AI and climate change received the Outstanding Doctoral Dissertation Award in Science and Engineering.
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.
David holds a B.S. in Finance, Information Systems and Statistics from the University of Florida, has served as an AI Fellow, and is finishing his PhD in Advanced Technology Research Methods at Capitol Technology University. David is currently authoring "Applied Artificial Intelligence: Getting Started with AI in Python" for Packt Publishing, and he is the host of the "HumAIn Podcast", a speaker series that explores practical ways to bridge the gap between humans and machines in the Age of Accelerated learning.