Training on Predictive Analytics using Supervised Statistical Learning Techniques

The seminar on "Predictive Analytics Using Supervised Statistical Learning Techniques" is a survey of machine learning models applied to prediction. Models to be discussed are regression models, tree-based models, neural networks, and support vector machines. Applications include sales forecasting, credit scoring, fraud detection, churn analysis, and medical diagnosis.

Course Description

This training program is a survey of the numerous techniques in supervised machine learning. Statistical machine learning refers to a wide range of approaches in creating models and tools in evaluating the estimates may it be for prediction or for inference. However, this course only focuses on the main methodologies in supervised machine learning which includes the following:

• basic concepts in statistical learning
• linear and logistic regression
• classification problems and tree-based methods
• neural networks and support vector machines.

With a little preview of the theoretical concepts of these tools, the course offers the relevant applications in different fields and areas.

Target Audience

Attendees who want to know the methods in the rising field of statistical machine learning are highly encouraged to participate. Also, those who want to expand their statistical programming skills and implementation in R are invited.

The training is for market researchers who conduct churn analysis, business managers who forecast sales and detect fraud, practitioners in the social sciences who handle specific data analysis, to name a few.

Prerequisite Knowledge

Participants must at least have taken introductory courses in basic statistics such as computing for summary measures (mean, standard deviation, correlation, among others) and their use and interpretation.

About the resource person

Gian Louisse Roy is an instructor and information officer in the UP School of Statistics. He graduated cum laude with a bachelor’s degree in Statistics and now currently finishing his master’s degree in Statistics. He handled courses in elementary statistics, mathematical statistics, and probability theory already. More than this, he’s been an active member of the Philippine Statistical Association, Inc. in the Training Committee and Social Media, Information, and Communication Committee. He conducted trainings with private and government institutions with focus and expertise on infographic and factsheet design and principles. In addition, he held several talks already on different issues and topics such as proper data presentation, career talks, research writing, and many more. His research interests include mathematical statistics and inferential thought.

Download the following:

• 2018 PSAI Training Outline
• 2018 PSAI Training Personal Information Sheet
• 2018 PSAI Training Registration Form