Why Enroll For Postgraduate Diploma in Machine Learning (E-Learning)?
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.
Your Learning Journey
- Regression Basics
- Regularization and Bayesian Methods I
- Regularization and Bayesian Methods II
- Foundational Classification Algorithms I
- Foundational Classification Algorithms II
- Intermediate Classification Algorithms
- Intermediate Classification Algorithms and Clustering Methods
- Clustering Methods
- Recommendation Systems
- Recommendation Systems and
- Sequential Data Models
- Sequential Data Models
- Association and Model Selection
- Classic Search I
- Classic Search II
- Introduction to Neural Networks I
- Introduction to Neural Networks II
- Tuning a Neural Network
- Convolutional Networks I
- Convolutional Networks II
- Natural Language Models I
- Natural Language Models II
- Deep Learning in Practice
John W. Paisley
Associate Professor, Electrical Engineering
Affiliated Member, Data Sciences Institute
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 Frias Koehler
Program Mentor, Emeritus
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
Applicants must be at least 21 years of age and will be required to submit:
- A completed application form
- Minimal educational requirement of a Bachelor Degree certificate or official transcript in any discipline
- An updated CV/resume
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
- Obtain a TOEFL minimum score of 550 for the paper based test or its equivalent
- Obtain an IELTS minimum score of 6.0
- Obtain a Pearson Versant Test minimum score of 59
- Obtain a Certificate of Completion for a Certificate course offered by Emeritus
- Submit a document which shows that the candidate has, for the last 24 months or more, worked in ANY ONE of these countries: Antigua and Barbuda, Australia, The Bahamas, Barbados, Belize, Canada, Dominica, Grenada, Guyana, India, Ireland, Jamaica, New Zealand, Singapore, South Africa, St Kitts and Nevis, St Lucia, St Vincent and the Grenadines, Trinidad and Tobago, United Kingdom, United States of America