Profit-Driven Business Analytics (E-learning)

📅 Self-Paced E-learning course
🌍 English

Overview

Business Knowledge Series course

Presented by Bart Baesens, Ph.D. Professor at the School of Management of the University of Southampton (UK); or Wouter Verbeke, Ph.D., Assistant Professor, Business Informatics, University of Brussels (Belgium)

The E-learning course course actionable guidance on optimizing the use of data to add value and drive better business decisions. Combining theoretical and technical insights into daily operations and long-term strategy, this course acts as a development manual for practitioners who seek to conceive, develop, and manage advanced analytical models. Detailed discussion delves into the wide range of analytical approaches and modeling techniques that can help maximize business payoff, and the instructor team draws upon their recent research to share deep insights about optimal strategy. Real-life case studies and examples illustrate these techniques at work, and provide clear guidance for implementation in your own organization. From step-by-step instruction on data handling, to analytical fine-tuning, to evaluating results, this course provides invaluable guidance for practitioners seeking to reap the advantages of true profit-driven business analytics. The E-learning course consists of more than 7 hours of movies, each 5 minutes on average. Quizzes are included to facilitate the understanding of the material. Upon registration, you will get an access code which gives you unlimited access to all course material (movies, quizzes, scripts, ...) during 6 months. The E-learning course focusses on the concepts and modeling methodologies and not on the SAS software. To access the course material, you only need a laptop, iPad, iPhone with a web browser. No SAS software is needed.

Learn how to

develop profit-driven descriptive analytics models
develop profit-driven predictive analytics models
evaluate profit-driven analytics models
develop and evaluate uplift models
understand the economic impact of analytics.

Course Outline

Introduction

profit-driven business analytics
introduction to profit-driven descriptive analytics
introduction to profit-driven predictive analytics
introduction to uplift modeling
introduction to profit-driven evaluation
the business analytics process model

Profit-Driven Descriptive Analytics

profit-driven segmentation
profit-driven association rules

Profit-Driven Predictive Analytics

cost matrix
-profit-driven decision making with cost-insensitive models: threshold setting
profit-driven predictive analytics framework: pre-training, during-training, post-training methods
pre-training methods: sampling and weighting
during-training methods: cost-sensitive logistic regression and cost-sensitive decision trees
post-training methods: threshold tuning and MetaCost
hybrid methods
cost-sensitive regression: BSZ tuning
self-study: profit driven ensemble methods

Uplift Modeling