Study segmentation, propensity, lookalike and customer-value models and apply NLP sentiment analysis to brand monitoring and social campaigns within a broader analytics course
Study segmentation, propensity, lookalike and customer-value models and apply NLP sentiment analysis to brand monitoring and social campaigns within a broader analytics course
Practice and assessment
Practice: The outline includes downloadable exercise material, section quizzes and an exercise-and-conclusion section
Access and subscriptions
Recorded Udemy course advertised with a public course preview. Exact lesson count may be unknown. Purchase or organization-subscription terms and current availability require checking
An original example for comparing learning plans. Ask whether the course teaches this task, includes practice and offers feedback; the diagram does not describe a provider’s course.
The 24-module book-based course includes AI/ML behavioral segmentation and persona development, predictive lead scoring, customer lifetime value and dynamic pricing, churn models and retention measurement, NLP/sentiment, predictive…
Coursera displays 24 modules, 23 assignments, beginner level, two weeks at ten hours per week, flexible schedule, English and eight languages availableCheck current priceEnglish
Implement customer segmentation, social sentiment, ecommerce recommendations, customer lifetime value and association rules within a broader 21-project Python ML portfolio. These outputs differ from the same creator’s retained…
1 section • 21 lectures • 6h 41m total lengthCheck current priceEnglish
Shared topic: Customer analytics and personalization
Christ Raharja
Analyze campaign and retention metrics, use unsupervised customer segmentation, build CatBoost churn and MLP lifetime-value models, and run A/B tests within a broader Excel/Python/Power BI course
19 sections • 21 lectures • 3h 27m total lengthCheck current priceEnglish