Machine Learning Mini-Course

This program is provided by Biostatistics, Epidemiology, and Research Design (BERD) in collaboration with the Data Science Institute.

Overview

In this mini course we’ll cover the fundamentals of machine learning. We’ll learn what machine learning is and what are its basic concepts including the different types of machine learning approaches which include classification and clustering. We’ll also cover the typical steps that are part of the machine learning workflow such as task definition, data collection and preparation, model development, and deployment. Along the way we’ll learn about the common terminology and the challenges in machine learning. 

Spanning three sessions, the classes will focus on the following areas:

• April 26, 12 - 1 pm - Part 1 will focus on defining what is machine learning, deep learning, artificial intelligence and related terminology.
• May 3, 12 - 1 pm - Part 2 will cover appropriate and inappropriate uses of machine learning.
• May 10, 12 - 1 pm - Part 3 will highlight machine learning applications in public health and medicine and delve into machine learning’s future potential in research.

Eligibility

The mini-course is open to the Columbia University community. In-person spots are limited. Non-affiliates may request registration but may be waitlisted.

Cost

There is no cost to attend the online mini-course.

Register

To register for the machine learning mini-course, click here. 

Cite it, Submit it, Share it!

If your research has benefited from one or more Irving Institute resources, please remember to:

• Cite our CTSA grant, UL1 TR001873, in any relevant publications, abstracts, chapters, and/or posters.
• Submit your publications to PubMed Central (PMC) for compliance with the NIH Public Access Policy.
• Share your research updates with us by sending an email to: irving_institute@cumc.columbia.edu