Machine Learning and its Applications in Market Research

Part 2: Predictive analytics using ML frameworks in Python
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Type On demand
Digital Yes

Welcome to Virtual Academy On-Demand

This exclusive on-demand training offers you access to six-hours of content, split into three engaging sessions. Designed to enhance your skills at your own pace and convenience, you'll be able to download resources, see the trainer's contact information and earn a certificate upon course completion.

This is the recommended prerequisite for the course:
Machine Learning and its Applications in Market Research

Use code VA_Python25_FDP when buying both for a 25% discount!

Overview

This course builds on the previous course Python for Market Research. It introduces you to the topic of Machine Learning (ML), how to build predictive models using ML algorithms and to use them for inferencing, decision making and forecasting. Data pre-processing will be an integral part of this course.

The course will focus on learning by doing and so be prepared for hands-on work and exercises. Introductory videos will be made available to help the participant ease into the course.

This course will cover the following:

  • Data pre-processing

  • Machine Learning using Scikit-Learn

  • Building predictive models

  • Applications in Market Research and hands-on exercises

After this course, you’ll be able to:

  • Use different data pre-processing techniques for different kinds of data

  • Use the ML frameworks in Python like Scikit-Learn for model building

  • Work with different ML algorithms to build predictive models based on data

  • Measure and analyze mode accuracy and tweak models for better performance

  • Discuss applications of ML methods in Market Research

Who should attend?

Anyone who has attended the Python for Market Research course or anyone with intermediate-level programming knowledge in Python and interested in learning Machine Learning methods.

Prerequisites for the course are:

  • Complete the intro course Python for Market Research OR

  • Has an intermediate level of Python programming knowledge

  • High school-level mathematics (Algebra, etc.)

A lot of content - questions were very well addressed. Friendly instructor and an opportunity to meet live in Teams and ask questions. ESOMAR platform is really good. I liked that the material was provided in advance so that you can prepare everything and don't have to do it during the course and have the possibility to watch video recording afterwards.

Feedback from an attendee

Trainer

Jag Rao
Professor of Practice at University of Georgia I MRII