This course empowers learners to apply predictive analytics techniques using the CART (Classification and Regression Tree) algorithm in the context of term deposit investment decisions. Structured around real-world marketing scenarios, learners will explore the end-to-end process of building decision tree models—from understanding business objectives and interpreting variables to developing, optimizing, and validating CART models.
Predictive Analytics Model for Term Deposit Investment
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Recently updated!
August 2025
Assessments
4 assignments
Taught in English
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There is 1 module in this course
This module introduces learners to the foundational concepts and practical implementation of the Classification and Regression Tree (CART) algorithm for predicting term deposit investment outcomes. Through step-by-step walkthroughs, learners explore the structure and logic behind CART, examine the variables involved in modeling, and gain hands-on experience in building, optimizing, and validating decision tree models. The module emphasizes model interpretability, parameter tuning, and best practices for applying predictive analytics in financial marketing contexts.
What's included
10 videos4 assignments
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