AI Marketing Courses

Marketing focus

Machine Learning for Marketing in Python

Four chapters (16 videos, 53 exercises) implement marketing ML: logistic regression/decision trees and churn-driver interpretation on telecom data, RFM/linear-regression next-month CLV prediction for an online retailer, and k-means/NMF…

DataCamp · DataCamp

Email and lifecycle marketingCreative visuals and videoCustomer analytics and personalization

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What you’ll cover

Four chapters (16 videos, 53 exercises) implement marketing ML: logistic regression/decision trees and churn-driver interpretation on telecom data. RFM/linear-regression next-month CLV prediction for an online retailer. And k-means/NMF product-purchase segments using grocery data

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Learning decision: Choose one customer moment; make Two email alternatives; check Consent, relevance and a clear next step.
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Marketing focus

Customer Segmentation in Python

Both mention Python

DataCamp

Four chapters (17 videos, 55 exercises) use online-retailer transactions for cohort acquisition/retention metrics, RFM value scoring and custom segments, then prepare and scale RFM features, fit k-means and interpret the resulting…

Intermediate Python, four hours. 17 videos and 55 interactive exercises. Prerequisite: Supervised Learning with scikit-learnCheck current priceAsk about teaching language
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Marketing focus

Data Analytics for Marketing

Both mention Python

Packt

Python workflow covers ETL/Singer and Streamlit, causal/regression analysis, Prophet/ARIMA KPI forecasting, STL/S-H-ESD/Bayesian change-point anomaly detection, k-means/RFM, decision trees/random forests, LDA/QDA and PyMC Marketing BTYD…

13 modules and 15 assignments. Intermediate. Coursera estimates two weeks at ten hours per week. Some assignments are shortCheck current priceAsk about teaching language
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Marketing focus

RA: Retail Customer Analytics and Trade Area Modeling.

Shared topic: Email and lifecycle marketing

Haytham Omar-Ph.D

Apply k-means to RFM customer data, predict CLV tiers with a decision tree, build a churn pipeline and interpret commercial segments, alongside trade-area/store-location modeling

12 sections • 164 lectures • 15h 42m total lengthCheck current priceEnglish
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