Customer Insights and Personalization with Machine Learning
Four modules apply ML to customer sentiment and behavior, A/B testing, recommendations, segmentation and personalized experiences, the page lists four assignments
Four modules apply ML to customer sentiment and behavior, A/B testing, recommendations, segmentation and personalized experiences. The page lists four assignments
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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.
Shared topic: Customer analytics and personalization
Board Infinity
Four modules cover AI brand research and ethics, social listening, sentiment, audience clustering and brand-health measures, predictive engagement, personalization, marketing automation and A/B testing, and a Power BI/Google Data Studio…
Advanced, self-paced course. Coursera estimates one week at 10 hours per week. Four modules and 13 assignmentsCheck current priceEnglish
Shared topic: Customer analytics and personalization
Board Infinity
Four modules use social, search, review and cultural signals for sentiment, brand-health and competitor analysis, build dynamic personas and ML-based segmentation/trend forecasts, and produce an ethical, privacy-aware multi-source…
Intermediate, self-paced course. Coursera estimates two weeks at 10 hours per week. Four modules and 18 assignmentsCheck current priceEnglish
Shared topic: Customer analytics and personalization
Coursera
Three modules describe: identifying agent opportunities in campaign planning, social scheduling and A/B testing, prompting for brand-aligned content and sentiment tracking, and CRM integration/performance analytics. Listed course tasks…
Published estimated study commitment: 4 hours to complete. Flexible, self-paced schedule. Study estimates are distinct from total video runtimeCheck current priceEnglish