Compare AI training for customer analytics, marketing data and interpreting campaign results.
333 courses in this collection
Eduonix Learning Solutions, Eduonix-Tech .
Define a customer-churn problem, prepare the data and build Python machine-learning models through a complete problem-to-model sequence
Shreesha Jagadeesh
Build an iterative customer-churn classification project using baseline Random Forest, feature engineering and tuned ensembles within a broader fraud/churn/financial-risk compilation
Vinay Karode
Implement logistic-regression and decision-tree churn models, interpret predictions and compare ensembles alongside broader insurance and retail-sales projects
Richard Aragon
Demonstrate customer-churn and sales-forecast models and NLP email-response automation within a broader seven-project corporate AI course
Taman Belajar, Bina Nusantara University
Prepare customer data, implement k-means in Python, evaluate and interpret clusters and complete a customer-segmentation case study
Meta Brains , Skool of AI
Prepare and evaluate k-means, hierarchical and DBSCAN clusters, then complete an ecommerce customer-segmentation project, broader unsupervised ML supports the marketing application
Mammoth Interactive, John Bura
Use ChatGPT guidance with Excel sales forecasting and customer-value analysis, then develop engagement and loyalty strategies from the resulting insights
Eduonix Learning Solutions
Apply ML to customer value, segmentation and market-basket analysis and build an LLM engagement chat solution within broader pricing, demand and business-data science
Eduonix Learning Solutions
Analyze and segment customers, forecast customer value, map journeys, model real-time personalization and targeted advertising and develop product-query conversations
Vinay Karode
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…
Francesco Alaimo
Use KNIME churn-training workflows and a clothing-customer dataset for k-means segmentation, cluster optimization and marketing personas within a broader platform course
Eric Hulbert
Build a KNIME Random Forest model for a sales-and-marketing client, prepare data and interpret predictions within a broader no-code data-science course
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