How to Predict and Prevent Customer Loss Using AI

skills

BEGINNER

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Updated 1 year ago

What you will learn

Introduction to Artificial Intelligence
Write basic instructions with Python Programming Language.
Understand the concept of customer churn and its impact on business.
Gain hands-on experience with a real-world customer churn dataset.
Build and train an ANN model for churn prediction.
Evaluate the performance of the ANN model using metrics such as precision | recall and accuracy.
Interpret the results using a confusion matrix and a classification report.

About

Modules

M:1

10:00 AM - 10:30 AM: Registration and Welcome

Participant registration and introductory remarks. Overview of the workshop objectives and agenda.

M:2

10:30 AM - 11:30 AM: Introduction to Customer Churn

Understanding customer churn and its business implications. Overview of predictive analytics for churn prediction.

M:3

11:30 AM - 12:30 PM: Data Exploration and Preprocessing

Introduction to the customer churn dataset. Data cleaning and preprocessing techniques.

M:4

12:30 PM - 1:30 PM: Lunch Break

M:5

1:30 PM - 3:00 PM: Building the ANN Model

Introduction to Artificial Neural Networks. Building and training the ANN model using TensorFlow/Keras.

M:6

3:00 PM - 3:15 PM: Coffee Break

M:7

3:15 PM - 4:30 PM: Model Evaluation and Interpretation

Evaluating the model using precision, recall, and accuracy. Understanding and interpreting the confusion matrix and classification report.

M:8

4:30 PM - 5:00 PM: Q&A and Wrap-Up

Addressing participant questions and discussing further resources. Closing remarks and feedback collection.

Instructors:

Toheeb Adisa

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This course includes:

7 Minutes on-demand video
Lifetime access
Milestone budges