Methodology

This course includes interactive discussion and the use of exercises and case studies. Each Machine Learning algorithm is supported by its own case study with step-by-step outputs that go in parallel with its multi-stage analysis. All algorithms are detailed with sequential screen shot applications on comparative technologies such as SPSS, SAS, Statistica and Excel.

Course Objectives

By the end of the course, participants will be able to:

Gain a clear understanding of Machine Learning concepts

Differentiate between Data Analysis and Machine Learning methodologies

Apply testing and validation techniques to Machine Learning models

Present an overview of optimal analytic solutions

Build and fine-tune predictive models for accurate estimations

Target Audience

Any level of professional interested in how Machine Learning can assist their organization, would benefit from this course. These include professionals from industries including, but not limited to, banking, insurance, retail, government, manufacturing, healthcare, telecom, and airlines.

Target Competencies

Predictive Analysis

Predictive Models

Data Analysis

Data Analytic Models