The Text Marketing Analytics specialization is a three-course sequence from the University of Colorado Boulder on Coursera, taught by Chris J. Vargo
Chris J. VargoAssociate professor of advertising and analytics at the University of Colorado Boulder, applying computational methods to social media data. CEO of Socialcontext and editor of The Agenda Setting Journal.LinkedIn ↗.
I worked with Chris on the syllabus and the assessments: what the sequence covers, in what order, and what the graded work asks students to do. Chris delivers the lectures. Coursera credits us both as instructors on the specialization.
The subject is machine learning applied to text at the volumes marketing and advertising deal with: sorting, grouping, and mapping large bodies of writing that nobody can read in full.
The courses
Supervised Text Classification for Marketing Analytics Classifiers for categories known in advance: the supervised workflow end to end, linear models and how to evaluate them, then neural networks and transformer models in TensorFlow.
Unsupervised Text Classification for Marketing Analytics Topic modeling and clustering over unlabeled text, for finding structure when the categories are not known ahead of time.
Network Analysis for Marketing Analytics Building graphs from relationships, computing their statistics, and reading social and semantic networks.
Taught with TensorFlow and scikit-learn, at an introductory level.
The material is close to the work at Socialcontext, where Chris is a co-founder: classifying text at scale for advertising.