Name: Predictive Analytics for Business Nanodegree Program
Rating: 4.7 (272 reviews)

Alteryx

4 Months

Month-To-Month

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.

Orientation

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

Getting Help

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

Get Help with Your Account

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.

Welcome to the program

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

The Analytical Problem

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

Selecting an Analytical Framework

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

Linear Regression

Get hands on practice building a linear regression model.

Practice 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.

Problem Solving with Analytics

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

Understanding Data

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

Data Issues

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

Data Formatting

Join and union data from different sources and formats.

Data Blending

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

Practice Project (Data Wrangling)

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.

Select predictor variables to be used in a predictive model.

Selecting Predictor Variables

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

Practice Project Select Location of a New Pet Store

Data Wrangling

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

Classification Problems

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

Binary Classification Models

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

Non-Binary Classification Models

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.

Classification Models

Understand the fundamentals of A/B testing, including selecting target and control units and variables and the duration of a test.

A/B Testing Fundamentals

Select test and control variables and understand the importance of sample size. Design a randomized design A/B test and analyze the results.

Randomized Design Tests

Match test units to control units. Design a matched pair design A/B test and analyze the results.

Matched Pair Design Tests

Use trend and seasonality as control variables for a matched pair design A/B test.

Matched Pair Practice

A/B Test a New Menu Launch

A chain of coffee shops is considering launching a new menu. You will design and analyze an A/B test and write up a recommendation on whether the chain should introduce the new menu.

A/B Testing

In this lesson you’ll learn what attributes make data a time series. You’ll also learn the key components used in time series forecasting, such as seasonality, trends, and cyclical patterns.

Fundamentals of Time Series Forecasting

In this lesson you’ll learn how to build and use ETS models. ETS stands for error, trend, and seasonality, and are the three inputs in ETS models. 

ETS Models

In this lesson you’ll learn how to build and use ARIMA models. ARIMA stands for autoregressive, integrated, moving average, which are the inputs for ARIMA models.

ARIMA Models

This lesson will demonstrate how to interpret the various results from time series model. 

Analyzing and Visualizing Results

A video game producer is planning production levels. You will use time series forecasting models to forecast monthly demand and provide a recommendation to help match supply to demand.

Practice Project Forecast Video Game Sales

Time series forecasting is a powerful analytical tool. In this course, learners will find our how ETS and ARIMA models are used
to forecast data and how they deal with trends and seasonality.

Time Series Forecasting

Understand the difference between localization, standardization, and segmentation

Segmentation Fundamentals

Scale data to prepare a dataset for cluster modeling. Select variables to include based on the business context.

Preparing Data for Clustering

Use principal components analysis (PCA) to reduce the number of variables for cluster model

Variable Reduction

Select the appropriate number of clusters. Build and apply a k-centroid cluster model.

Clustering Models

Validate the results of a cluster model. Visualize and communicate the results of a cluster model.

Validating and Applying Clusters

In this lesson, you will learn how to make visualizations in Tableau. Get excited - it is about to get awesome!

Data Visualizations in Tableau

A retail store chain wants to expand to other countries. You will build a clustering model to segment countries to determine which countries are most similar to the U.S. in order to determine the best

Segmentation Practice Project

Combining Predictive Techniques

After completing the project, you will feel comfortable combining predictive techniques and delivering results 

Segmentation and Clustering

In this section, you will gain knowledge about SQL basics for working with a single table. You will learn the key commands to filter a table in many different ways.  

Basic SQL

In this lesson, you will learn how to combine data from multiple tables together.  

SQL Joins

In this lesson, you will learn how to aggregate data using SQL functions

SQL Aggregations

In this lesson, you will learn about subqueries, a fundamental advanced SQL topic. This lesson will walk you through the appropriate applications of subqueries, the different types of subqueries, and review subquery syntax and examples.

SQL Subqueries & Temporary Tables

Cleaning data is an important part of the data analysis process. You will be learning how to perform data cleaning using SQL in this lesson.

SQL Data Cleaning

Window functions allow users to compare one row to another without doing any joins using one of the most powerful concepts in SQL data analysis.

SQL Window Functions

Learn advanced joins and how to make queries that run quickly across giant datasets. Most of the examples in the lesson involve edge cases, some of which come up in interviews.

SQL Advanced JOINS & Performance Tuning

SQL Lessons

In this lesson you learn to evaluate the quality of data visualizations and build high quality visualizations, starting with the fundamentals of data dashboards.

Data Visualization Fundamentals

In this lesson you learn to implement the best design practices, and to use the most appropriate chart for a particular situation.

Design Principles

This lesson teaches you how to build data visualizations in Tableau using data hierarchies, filters, groups, sets, and calculated fields, as well as create map-based data visualizations in Tableau.


Creating Visualizations in Tableau

In this lesson you learn how to build interactive Tableau dashboards and tell impactful stories using data.


Telling Stories with Tableau

Learn to apply sound design and data visualization principles to the data analysis process. Learn how to use analysis and visualizations in Tableau to tell a story with data.

Data Visualization with Tableau

Improve Your LinkedIn Profile

Find your next job or connect with industry peers on LinkedIn. Ensure your profile attracts relevant leads that will grow your professional network.

Take 30 Min to Improve your LinkedIn

LinkedIn is widely used by tech recruiters to find and evaluate job candidates. It's also where you can meet interesting people in your field. Get personalized feedback on how to improve your profile! (You may elect to opt out of this project.)

Career Support

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