3.8
193 个评分
57 个审阅

### 您将获得的技能

Regression AnalysisData CleansingPredictive ModellingExploratory Data Analysis

1

## Exploratory Data Analysis and Visualizations

At the end of this module students will be able to: 1. Carry out exploratory data analysis to gain insights and prepare data for predictive modeling 2. Summarize and visualize datasets using appropriate tools 3. Identify modeling techniques for prediction of continuous and discrete outcomes. 4. Explore datasets using Excel 5. Explain and perform several common data preprocessing steps 6. Choose appropriate graphs to explore and display datasets ...
8 个视频 （总计 38 分钟）, 1 个阅读材料, 3 个测验
8 个视频
0. Introduction to the Module. Why Exploratory Data Analysis is Important3分钟
1. Data Cleanup and Transformation4分钟
2. Dealing With Missing Values6分钟
3. Dealing with Outliers3分钟
5. Common Graphs7分钟
6. What is Good Data Visualization?4分钟
1 个阅读材料
Register for Analytic Solver Platform for Education (ASPE)10分钟
2 个练习
Week 1 Quiz48分钟
Week 1 Application Assignment 1 (optional): Data Cleanup6分钟
2

## Predicting a Continuous Variable

This module introduces regression techniques to predict the value of continuous variables. Some fundamental concepts of predictive modeling are covered, including cross-validation, model selection, and overfitting. You will also learn how to build predictive models using the software tool XLMiner....
8 个视频 （总计 41 分钟）, 2 个测验
8 个视频
1. Introduction to Linear Regression8分钟
2. Assessing Predictive Accuracy Using Cross-Validation5分钟
3. Multiple Regression4分钟
4. Improving Model Fit3分钟
5. Model Selection3分钟
6. Challenges of Predictive Modeling5分钟
7. How to Build a Model using XLMiner8分钟
2 个练习
Week 2 Quiz18分钟
Week 2 Application Assignment40分钟
3

## Predicting a Binary Outcome

This module introduces logistic regression models to predict the value of binary variables. Unlike continuous variables, a binary variable can only take two different values and predicting its value is commonly called classification. Several important concepts regarding classification are discussed, including cross validation and confusion matrix, cost sensitive classification, and ROC curves. You will also learn how to build classification models using the software tool XLMiner....
8 个视频 （总计 33 分钟）, 2 个测验
8 个视频
1. Introduction to Logistic Regression4分钟
2. Building Logistic Regression Model6分钟
3. Multiple Logistic Regression3分钟
4. Cross Validation and Confusion Matrix5分钟
5. Cost Sensitive Classification2分钟
6. Comparing Models Independent of Costs and Cutoffs3分钟
7. Building Logistic Regression Models using XLMiner6分钟
2 个练习
Week 3 Quiz14分钟
Week 3 Application Assignment26分钟
4

## Trees and Other Predictive Models

This module introduces more advanced predictive models, including trees and neural networks. Both trees and neural networks can be used to predict continuous or binary variables. You will also learn how to build trees and neural networks using the software tool XLMiner....
8 个视频 （总计 32 分钟）, 4 个测验
8 个视频
1. Introduction to Trees2分钟
2. Classification Trees5分钟
3. Regression Trees2分钟
4. Bagging, Boosting, Random Forest4分钟
5. Building Trees with XLMiner5分钟
6. Neural Networks5分钟
7. Building Neural Networks using XLMiner4分钟
3 个练习
Week 4 Quiz12分钟
Week 4 Application Assignment10分钟
Final Course Assignment Quiz40分钟
3.8
57 个审阅

### 热门审阅

this course teach you about the technical of using tools for predictive modeling. very useful for you who want to learn the fundamental of analytics.

There were some instructions in the quizzes hard to understand with no additional explanation in case of error.

Professor

## 关于 科罗拉多大学波德分校

CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies....