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英語

字幕:英語, 韓国語

習得するスキル

Regression AnalysisData CleansingPredictive ModellingExploratory Data Analysis

次における5の2コース

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

約21時間で修了

推奨:5 hours/week...

英語

字幕:英語, 韓国語

シラバス - 本コースの学習内容

1
4時間で修了

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

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8件のビデオ (合計38分), 1 reading, 3 quizzes
8件のビデオ
0. Introduction to the Module. Why Exploratory Data Analysis is Important3 分
1. Data Cleanup and Transformation4 分
2. Dealing With Missing Values6 分
3. Dealing with Outliers3 分
4. Adding and Removing Variables4 分
5. Common Graphs7 分
6. What is Good Data Visualization?4 分
1件の学習用教材
Register for Analytic Solver Platform for Education (ASPE)10 分
2の練習問題
Week 1 Quiz48 分
Week 1 Application Assignment 1 (optional): Data Cleanup6 分
2
2時間で修了

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.

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8件のビデオ (合計41分), 2 quizzes
8件のビデオ
1. Introduction to Linear Regression8 分
2. Assessing Predictive Accuracy Using Cross-Validation5 分
3. Multiple Regression4 分
4. Improving Model Fit3 分
5. Model Selection3 分
6. Challenges of Predictive Modeling5 分
7. How to Build a Model using XLMiner8 分
2の練習問題
Week 2 Quiz18 分
Week 2 Application Assignment40 分
3
1時間で修了

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.

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8件のビデオ (合計33分), 2 quizzes
8件のビデオ
1. Introduction to Logistic Regression4 分
2. Building Logistic Regression Model6 分
3. Multiple Logistic Regression3 分
4. Cross Validation and Confusion Matrix5 分
5. Cost Sensitive Classification2 分
6. Comparing Models Independent of Costs and Cutoffs3 分
7. Building Logistic Regression Models using XLMiner6 分
2の練習問題
Week 3 Quiz14 分
Week 3 Application Assignment26 分
4
4時間で修了

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.

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8件のビデオ (合計32分), 4 quizzes
8件のビデオ
1. Introduction to Trees2 分
2. Classification Trees5 分
3. Regression Trees2 分
4. Bagging, Boosting, Random Forest4 分
5. Building Trees with XLMiner5 分
6. Neural Networks5 分
7. Building Neural Networks using XLMiner4 分
3の練習問題
Week 4 Quiz12 分
Week 4 Application Assignment10 分
Final Course Assignment Quiz40 分
3.8
57件のレビューChevron Right

Predictive Modeling and Analytics からの人気レビュー

by HANov 20th 2017

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.

by GDDec 12th 2016

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

講師

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Dan Zhang

Professor
Leeds School of Business

コロラド大学ボルダー校(University of Colorado Boulder)について

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....

Advanced Business Analyticsの専門講座について

The Advanced Business Analytics Specialization brings together academic professionals and experienced practitioners to share real world data analytics skills you can use to grow your business, increase profits, and create maximum value for your shareholders. Learners gain practical skills in extracting and manipulating data using SQL code, executing statistical methods for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results. The problems faced by decision makers in today’s competitive business environment are complex. Achieve a clear competitive advantage by using data to explain the performance of a business, evaluate different courses of action, and employ a structured approach to business problem-solving. Check out a one-minute video about this specialization to learn more!...
Advanced Business Analytics

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