このコースについて
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次における5の5コース

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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19時間で修了

推奨:4 hours/week...

英語

字幕:英語, 韓国語

次における5の5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19時間で修了

推奨:4 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

Module 1 - Understand the data and prepare your data for analysis

This week your goal is to understand the data and prepare the data for analysis. As we discussed in this specialization, data preprocessing and cleanup is often the first step in data analytics projects. Needless to say, this step is crucial for the success of this project. We've selected a few videos from Courses 2 and 4 for you to review before completing this week's assignments. Dealing With Missing Values and Dealing with Outliers videos will remind you how to perform preliminary data cleanups. The last part of the assignments ask you to construct data visualizations. You may find the ideas discussed in What is Good Data Visualization? and Graphical Excellence useful. ...
5件のビデオ (合計25分), 2 readings, 1 quiz
5件のビデオ
Dealing with Missing Values6 分
Dealing with Outliers3 分
What is Good Data Visualization4 分
Graphical Excellence4 分
2件の学習用教材
Introduction to the Project30 分
Register for Analytic Solver Platform for Education (ASPE)10 分
2
5時間で修了

Module 2 - Perform predictive analytics tasks

This week you will perform some predictive analytics tasks, including classifying loans and predicting losses from defaulted loans. You will try a variety of tools and techniques this week, as the predictive accuracy of different tools can vary quite a bit. It is rarely the case that the default model produced by ASP is the best model possible. Therefore, it is important for you to tune the different models in order to improve the performance.This week’s assignments require you to build predictive models for both classification and regression tasks. <p> Before working on the assignments, you may review a few videos to remind yourself several important concepts, such as cross validation. These concepts are discussed in the videos Cross Validation and Confusion Matrix and Assessing Predictive Accuracy Using Cross-Validation. You may also find a refresher on XLMiner useful. The videos Building Logistic Regression Models using XLMiner and How to Build a Model using XLMiner discuss how to build logistic regression and linear regression models. Depending on your needs, you may also go back to the videos that discuss how to build trees and neural networks. </p>...
4件のビデオ (合計25分), 1 quiz
4件のビデオ
Assessing Predictive Accuracy Using Cross-Validation5 分
Building Logistic Regression Models using XLMiner6 分
How to Build a Model using XLMiner8 分
3
5時間で修了

Module 3 - Provide suggestions on how to allocate investment funds using prescriptive analytics tools

This week we turn our attention to prescriptive analytics, where you will provide some concrete suggestions on how to allocate investment funds using analytics tools, including clustering and simulation-based optimization. You will see that allocating funds wisely is crucial for the financial return of the investment portfolio. <p>The relevant videos for this week are from Course 3: Week 1: Cluster analysis with XLMiner, Week 2: Adding uncertainty to spreadsheet model, Week 2: Defining output variables and analyzing results. </p>...
1 quiz
4
5時間で修了

Module 4 - Present your analytics results to your clients

You have done a lot so far! In this last week, you will present to your analytics results to your clients. Since you have many results in your project, it is important for you to judiciously choose what to include in your presentation. Several videos in Course 4 offer some guidelines on communicating analytics results. This assignment will give you an opportunity to apply the skills you learned there. Good luck!...
1 quiz
4.4
3件のレビューChevron Right

人気のレビュー

by RAMar 4th 2019

Great List of Courses for People who are interested

講師

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Manuel Laguna

Professor
Leeds School of Business
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Dan Zhang

Professor
Leeds School of Business
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David Torgerson

Instructor

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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