AI Marketing Courses

Marketing focus

Unsupervised Text Classification for Marketing Analytics

Python/JSON practicals apply unsupervised text analysis to YikYak sentiment segmentation and Amazon reviews, with TF-IDF/topic models, BERTopic and text networks

University of Colorado Boulder · Coursera

Customer analytics and personalization

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Python/JSON practicals apply unsupervised text analysis to YikYak sentiment segmentation and Amazon reviews, with TF-IDF/topic models, BERTopic and text networks

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Learning decision: Frame one business question; make A report with an interpretation; check Data quality, uncertainty and competing explanations.
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Marketing focus

Text Mining for Marketing

Shared topic: Customer analytics and personalization

O.P. Jindal Global University

Marketing text-mining curriculum applies sentiment, topic modeling, NLP, named-entity recognition, classification, topic clustering and predictive analysis to customer reviews, social posts, feedback and news. Named uses include…

12 modules and 36 assignments. Coursera estimates two weeks at ten hours per week. The public outline does not establish coding or learner-built modelsCheck current priceAsk about teaching language
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Marketing focus

Applying Data Analytics in Marketing

Both mention Python

University of Illinois Urbana-Champaign

Marketing analytics applies causal analysis and AI/ML predictive models to customer behavior, text/sentiment/topic/network analyses to user, firm and AI-generated content, and conjoint analysis to preference, examples address CLV, churn…

Four modules and five assignments. Intermediate. Coursera estimates two weeks at ten hours per weekCheck current priceEnglish
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Related skills

NLP in Python: Probability Models, Statistics, Text Analysis

Both mention Python

Meta Brains , Skool of AI

Build a customer-review sentiment pipeline and ecommerce review analysis combining entity recognition/topic modeling, with probabilistic features/Naive Bayes and model deployment. Broader NLP foundations accompany the explicit…

12 sections • 56 lectures • 6h 24m total lengthCheck current priceEnglish
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