Predictive Analytics for Business Nanodegree

Kai Sheng Teh

This repository contains projects for Udacity's Predictive Analytics for Business Nanodegree. (It was known as Business Analyst Nanodegree back in 2017)

Part 1: Problem Solving with Advanced Analytics by Alteryx

Learn a structured framework for solving problems with advanced analytics. Learn to select the most appropriate analytical methodology. Learn linear regression.

• Project: Predicting Diamond Prices
• Project: Predicting Catalog Demand

Part 2: Creating an Analytical Dataset by Alteryx

Understand the most common data types. Understand the various sources of data. Make adjustments to dirty data to prepare a dataset. Identify and adjust for outliers. Learn to write queries to extract and analyze data from a relational database.

• Project: Data Cleanup
• Project: Create Report from Database (SQL)

Part 3: Data Visualization in Tableau

Understand the importance of data visualization. Know how different data types are encoded in visualizations. Select the most effective chart or graph based on the data being displayed.

• Project: Visualizing Movie Data

Part 4: Classification Models by Alteryx

You will use classification models, such as logistic regression, decision tree, forest, and boosted, to make predictions of binary and non-binary outcomes.

• Project: Predicting Default Risk

Part 5: A/B Testing

Understand the fundamentals of A/B testing, including experimental design, variable selection, and analyzing and interpreting results.

• Project: A/B Test a New Menu Launch

Part 6: Time Series Forecasting

Understand trend, seasonal, and cyclical behavior of time series data. Use time series decomposition plots. Build ETS and ARIMA models.

• Project: Forecast Video Game Sales

Part 7: Segmentation and Clustering

Understand the difference between localization, standardization, and segmentation. Scale data to prepare a dataset for cluster modeling. Use principal components analysis (PCA) to reduce the number of variables for cluster model. Build and apply a k-centroid cluster model. Visualize and communicate the results of a cluster model. Then complete a capstone project combining techniques learned throughout the program.

• Project: Predictive Analytics Capstone