01. Program Hosts – Course Overview

Overview

The course will take you through two key analytical concepts to help you understand any business situation and help you choose the correct techniques to analyze your data.

  1. Cross Industry Standard Process for Data Mining (CRISP-DM)
  2. Predictive Methodology Map

crisp explanation

CRISP-DM

This framework was originally developed by data miners in order to generalize the common approaches to defining and analyzing a problem. In this course, we will call CRISP-DM the “Problem Solving Framework”.

The framework is made up of 6 steps:

  1. Business Issue Understanding
  2. Data Understanding
  3. Data Preparation
  4. Analysis/Modeling
  5. Validation
  6. Presentation/Visualization

crisp

 

This framework is based upon the CRISP-DM framework: Cross Industry Standard Process for Data Mining

method map explain

Methodology Map

The methodology map is a guide to determine the appropriate analytical technique(s) to solve a particular business question or problem.

The map outlines two main scenarios for a business problem:

  1. Data analysis
  2. Predictive analysis

Data analysis refers to the more standard approaches of blending together data and reporting on trends and statistics and helps answer business questions that involve understanding more about the dataset such as “On average, how many people order coffee and a donut per transaction in my store in any given week?”

Predictive analysis will help businesses predict future behavior based on existing data such as “Given the average coffee order, how much coffee can I expect to sell next week if I were to add a new brand of coffee?”

It’s highly suggested you download and print this map to help you figure out what kind of analytical techniques you should use given any business problem you may work on in your career.

method map

Analyst Methodology Map

lr

Linear Regression

You will then learn how to create linear regression models to help you predict numerical data such as sales. You’ll dive deep into these concepts:

  1. Linear relationship
  2. Multiple-R squared and p-values
  3. Significant coefficients
  4. Modeling categorical variables

project

Feel free to skip around this course if you’re already familiar with some of these topics already. You do not have to go through every video in this course.

To help you gauge what techniques you need for the project, the project will focus on linear regressions and categorical variables. If you’re already familiar with these techniques, feel free to skip ahead and start working on the project.

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