课程信息
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中级

英语(English)

字幕:英语(English)

开始攻读学位

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中级

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 9 小时

Module 0 Get Ready & Module 1 Introduction to Analytics and Evolution of Statistical Inference

This session is an overview of the business data analytics process and its components. It introduces to different modeling paradigms and invites the student to match problems to modeling paradigms. The module concludes with an overview of Rattle an interface for R and its use for univariate analysis. 

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14 个视频 (总计 86 分钟), 10 个阅读材料, 4 个测验
14 个视频
Rattle Installation Guidelines for Windows6分钟
Rattle Installation Guideline for MacOS11分钟
Rattle Interface for Windows9分钟
Lecture 1-1: Introduction to Analytics and Evolution of Statistical Inference3分钟
Lecture 1-2: From Data to Decisions9分钟
Lecture 1-3: The Evolution of Intelligent Machines3分钟
Lecture 1-4: Common Paradigms6分钟
Lecture 1-5-1: Examples of Paradigms – Part 14分钟
Lecture 1-5-2: Examples of Paradigms – Part 26分钟
Lecture 1-6: Introduction to Rattle4分钟
Lecture 1-7: Importing Datasets in Rattle8分钟
Lecture 1-8: Plotting Data and Creating Graphs in Rattle7分钟
Lecture 1-9: Rattle Practice and Summary3分钟
10 个阅读材料
Syllabus30分钟
About the Discussion Forums10分钟
Glossary30分钟
Brand Descriptions30分钟
Update Your Profile10分钟
Module 0 Agenda5分钟
Rattle Tutorials (Interface, Windows, Mac)30分钟
Module 1 Overview20分钟
Module 1 Readings, Data Sets, and Slides1小时
Module 1 Peer Review Assignment Answer Key20分钟
3 个练习
Orientation Quiz10分钟
Module 1 Practice Problems40分钟
Module 1 Graded Quiz30分钟
2
完成时间为 6 小时

Module 2 "Dating with Data"

This session focuses on identifying relationships between dependent and independent variables using a regression model. The goal is to find the best fitted model to the data to learn about the underlying relationship in the population.  

...
8 个视频 (总计 63 分钟), 3 个阅读材料, 3 个测验
8 个视频
Lecture 2-2: Developing and Estimating a Model3分钟
Lecture 2-3: Univariate and Bivariate Plots8分钟
Lecture 2-4: Bivariate Correlation5分钟
Lecture 2-5-1: Estimating With Simple Models - Part 18分钟
Lecture 2-5-2: Estimating With Simple Models - Part 210分钟
Lecture 2-6: Improving the Model12分钟
Lecture 2-7: Model Improvement Practice and Summary8分钟
3 个阅读材料
Module 2 Overview20分钟
Module 2 Readings, Data Sets, and Slides1小时
Module 2 Peer Review Assignment Answer Key20分钟
2 个练习
Module 2 Practice Problems40分钟
Module 2 Graded Quiz30分钟
3
完成时间为 6 小时

Module 3 Model Development and Testing with Holdout Data

This session introduces the student to use of a holdout data set for evaluating model performance. Methods of improving the model are discussed with emphasis on variable selection. Nuances of modeling discrete predictor variables and response variable are discussed. 

...
8 个视频 (总计 66 分钟), 3 个阅读材料, 3 个测验
8 个视频
Lecture 3-2: Introducing Root Mean Square Error14分钟
Lecture 3-3: Variable Selection8分钟
Lecture 3-4: Variable Selection with R Scripts8分钟
Lecture 3-5: Introduction to Mallow's CP6分钟
Lecture 3-6-1: Modeling Example – Part 18分钟
Lecture 3-6-2: Modeling Example – Part 29分钟
Lecture 3-7: Example Wrap-Up and Summary6分钟
3 个阅读材料
Module 3 Overview20分钟
Module 3 Readings, Data Sets, and Slides1小时
Module 3 Peer Review Assignment Answer Key20分钟
2 个练习
Module 3 Practice Problems20分钟
Module 3 Graded Quiz30分钟
4
完成时间为 5 小时

Module 4 Curse of Dimensionality

There has been a tremendous increase in the way data generation via sensors, digital platforms, user-generated content etc. are being used in the industry. For example, sensors continuously record data and store it for analysis at a later point. In the way data gets captured, there can be a lot of redundancy. With more variables, comes more trouble! There may be very little (or no) incremental information gained from these sources. This is the problem of high unwanted dimensions. And to avoid this trouble, data transformation and dimension reduction comes to the rescue by examining and extracting fewer dimensions while ensuring that it conveys the full information concisely. 

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7 个视频 (总计 67 分钟), 3 个阅读材料, 3 个测验
7 个视频
Lecture 4-2: Curse of Dimensionality9分钟
Lecture 4-3: Limitations of Scatterplots10分钟
Lecture 4-4: Principle Component Analysis10分钟
Lecture 4-5: Principle Component Analysis in Rattle9分钟
Lecture 4-6: Principle Component Analysis in Rattle With Regression10分钟
Lecture 4-7: Principle Component Analysis Exercise and Summary8分钟
3 个阅读材料
Module 4 Overview20分钟
Module 4 Readings, Data Sets, and Slides1小时
Module 4 Peer Review Assignment Answer Key20分钟
2 个练习
Module 4 Practice Problems
Module 4 Graded Quiz30分钟

讲师

Avatar

Sridhar Seshadri

Professor of Business Administration
Business Administration

领先获取学位

此 课程 隶属于 伊利诺伊大学香槟分校 提供的 100% 在线 Master of Science in Accountancy (iMSA)。立即开始学习开放课程或专项课程,观看 iMBA 教师的课程并完成自主学习作业。 完成每门课程后,您将获得一个证书,您可以添加到 LinkedIn 和简历中。 如果申请并被录取参加全部课程,您的课程将计入您的学位学习进程。

关于 伊利诺伊大学香槟分校

The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs. ...

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