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AI-Driven Sales Forecasting and Market Analysis

Build regression-based sales forecasts and study retention classification and K-means customer segmentation

Start-Tech Academy, Abhishek Bansal, Pukhraj Parikh · Udemy

Inside the course

What you’ll cover

Build regression-based sales forecasts and study retention classification and K-means customer segmentation

Audience and starting point

No prior experience is required according to the source

Practice and assessment

Practice: Provider-described hands-on tasks and quizzes apply regression, churn classification, clustering and Julius AI forecasting. Formal grading or depth is not confirmed

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

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

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Related tasks, tools and formats. Check the differences before choosing.

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Predictive Customer Analytics

Start-Tech Academy , Pukhraj Parikh , Abhishek Bansal

Preprocess customer data and use Excel/XLSTAT regression, clustering and automated logistic models for behavior, churn/retention and sales forecasts

6 sections • 33 lectures • 3h 29m total lengthCheck current priceEnglish
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Marketing Analytics Using R and Excel

Exam Turf

Apply logistic-regression churn models and k-means airline-customer segmentation to retention and targeted marketing within a broader R/Excel analytics course

4 sections • 22 lectures • 2h 55m total lengthCheck current priceEnglish
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Data Analytics for Marketing

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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