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Predictive Analytics for Business

Nanodegree Program

Learn to clearly define business issues, prepare and clean data, and implement a variety of predictive modeling techniques.

Learn to clearly define business issues, prepare and clean data, and implement a variety of predictive modeling techniques.

Built in collaboration with

Alteryx

Intermediate

2 months

Real-world Projects

Completion Certificate

Last Updated June 27, 2024

Skills you'll learn:
Data storytelling • Tableau data pane • Tableau map-based visualizations • Tableau interactive dashboards
Prerequisites:

No experience required

Courses In This Program

Course 1 1 day

Welcome to the program

Lesson 1

Orientation

Welcome to the Predictive Analytics for Business Nanodegree program! In this lesson, you will learn more about the structure of the program and meet the team.

Lesson 2

Getting Help

You are starting a challenging but rewarding journey! Take 5 minutes to read how to get help with projects and content.

Lesson 3

Get Help with Your Account

What to do if you have questions about your account or general questions about the program.

Lesson 4 • Project

Predicting Diamond Prices

You will apply a framework to work through the problem and build a linear regression model to provide results and a recommendation.

Course 2 2 weeks

Problem Solving with Analytics

Lesson 1

The Analytical Problem

In this course you'll learn strategies for solving problems, non-predictive data analysis, and more.

Lesson 2

Selecting an Analytical Framework

Select the most appropriate analytical methodology based on the context of the business problem.

Lesson 3

Linear Regression

Build, validate, and apply linear regression models to solve a business problem

Lesson 4

Practice Project

Get hands on practice building a linear regression model.

Lesson 5 • Project

Predicting Catalog Demand

You will apply a framework to work through the problem and build a linear regression model to provide results and a recommendation.

Course 3 2 weeks

Data Wrangling

Lesson 1

Understanding Data

Understand the most common data types. Understand the various sources of data.

Lesson 2

Data Issues

Identify common types of dirty data. Make adjustments to dirty data to prepare a dataset. Identify and adjust for outliers.

Lesson 3

Data Formatting

Summarize, cross-tabulate, transpose, and reformat data to prepare a dataset for analysis.

Lesson 4

Data Blending

Join and union data from different sources and formats.

Lesson 5

Practice Project (Data Wrangling)

Get hands on practice cleaning, blending, and preparing a dataset.

Lesson 6 • Project

Create an Analytical Dataset

A pet store chain is selecting the location for its next store. You will use data preparation techniques to build a robust analytic dataset, then build a predictive model to select the best location.

Lesson 7

Selecting Predictor Variables

Select predictor variables to be used in a predictive model.

Lesson 8

Practice Project Select Location of a New Pet Store

A pet store chain is selecting the location for its next store. Build a predictive model to select the best location.

Course 4 2 weeks

Classification Models

Lesson 1

Classification Problems

Understand the fundamentals of classification modeling and how it differs from modeling numeric data

Lesson 2

Binary Classification Models

Build logistic regression and decision tree models. Use stepwise to automate predictor variables selection. Score and compare models and interpret the results.

Lesson 3

Non-Binary Classification Models

Build and compare forest and boosted models and interpret their results. Score and compare models and interpret the results.

Lesson 4 • Project

Predicting Default Risk

A bank recently received an influx of loan applications. You will build and apply a classification model to provide a recommendation on which loan applicants the bank should lend to.

Taught By The Best

Photo of Tony Moses

Tony Moses

Instructor

Tony Moses is a Solutions Engineer at Alteryx, Inc. He works with customers to help develop plans to solve complex business problems around data preparation, geospatial analysis and predictive analytics.

Photo of Rod Light

Rod Light

Instructor

Rod Light is a Solutions Engineer Practice Lead at Alteryx, where he helps customers and prospects design data analytics solutions for their businesses using Alteryx.

Photo of Maureen Wolfson

Maureen Wolfson

Instructor

Maureen Wolfson is a Solution Engineer at Alteryx, Inc. She has more than 20 years of data analysis expertise specializing in data, customer and geospatial analysis.

Photo of Ben Burkholder

Ben Burkholder

Instructor

Ben Burkholder is a senior solution engineer at Alteryx, Inc. In this role he works extensively with clients to help develop plans to solve complex business problems around data preparation, geospatial analysis, and predictive analytics.

Photo of Patrick Nussbaumer

Patrick Nussbaumer

Instructor

Patrick Nussbaumer is Technical Activation Director at Alteryx, Inc. Prior to Alteryx, Patrick has spent the past 20 years in a variety of roles focused on data analysis, telecommunications, and financial services industries.

Ratings & Reviews

Average Rating: 4.7 Stars

272 Reviews

Fawziah a.

December 22, 2022

excellent experience

Areej A.

December 12, 2022

So far so good

Phanindra P.

September 6, 2022

Ab testing and Segmentation need more focus

Abdulaziz A.

July 30, 2022

I'm Enjoyed

Gazwan N.

July 30, 2022

great

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