使用Excel Real Statistics外接程序
你将学到什么：
了解端到端数据分析工作流
了解基础知识或Excel Real Statistics加载项
使用Excel Real Statistics插件应用不同的机器学习算法
展示应用回归、KMeans等算法的知识，使用医疗保健数据
要求：
不需要特定的经验。
说明：
您是否有兴趣学习如何使用医疗保健数据和Excel应用一些机器学习算法？是的，那就别再看了。本课程的设计考虑了各种参数。我结合了我22年的医疗IT经验和12年的向不同背景（技术和非技术）的学生教授医疗IT的经验。在本课程中，您将了解以下内容：通过收入周期管理工作流程了解患者之旅——前台、中台和后台数据可视化之旅——从源系统到创建报告了解描述性、诊断性、预测和说明性分析目前，我已经解释了以下算法简单线性回归多元线性回归加权线性回归逻辑回归多项式回归序数回归KNN分类KMeans聚类经典时间序列ARIMA下面列出了一些关键解释的概念同方差与异方差Breusch-Pagan&White测试混淆矩阵名义与序数数据AUC&ROC曲线ACF&PACF时间序列中的差异时间序列中的差异医疗保健数据集创建算法。我在下面列出了使用的医疗保健数据集健康保险数据视频病例哮喘数据肥胖会员注册医药销售前列腺癌乳腺癌产妇健康风险**课程图片封面是使用Freepik网站上的资产设计的。
本课程的对象：
对使用医疗保健数据创建基本分析感兴趣的初学者
医疗IT专业人员
医疗保健/医院管理专业人员
希望了解分析基础知识的非技术背景专业人士
Healthcare IT Decoded - Data Analytics
Published 5/2024
Created by Harish Rijhwani
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 176 Lectures ( 10h 4m ) | Size: 5.1 GB
Using Excel Real Statistics Add-In
What you'll learn:
Understand the End to End Data Analysis Workflow
Understand basics or Excel Real Statistics Addin
Apply different Machine Learning Algorithms using Excel Real Statistics AddIn
Demonstrate knowledge of applying Algorithms like Regression, KMeans using Healthcare Data
Requirements:
No specific experience required.
Description:
Are you Interested in learning how to apply some machine learning algorithms using Healthcare data and that too using Excel? Yes, then look no further. This course has been designed considering various parameters. I combine my experience of twenty two years in Health IT and twelve years in teaching the same to students of various backgrounds (Technical as well as Non-Technical).In this course you will learn the following:Understand the Patient Journey via the Revenue Cycle Management Workflow - Front, Middle and Back OfficeThe Data Visualization Journey - Moving from Source System to creating ReportsUnderstand Descriptive, Diagnostic, Predictive and Prescriptive Analytics At present I have explained below AlgorithmsSimple Linear Regression | Multiple Linear Regression | Weighted Linear Regression | Logistic Regression | Multinomial Regression | Ordinal Regression | KNN Classification | KMeans Clustering Classic Time Series | ARIMA | Some of the concepts key explained are listed below Homoscedasticity vs HeteroskedasticityBreusch-Pagan & White TestConfusion MatrixNominal vs Ordinal DataAUC & ROC CurveACF & PACF in Time SeriesDifferencing in Time Series Healthcare Datasets to create the algorithms.I have listed a the healthcare datasets used belowHealth Insurance DataCovid CasesAsthma DataObesity Member Enrollment Pharma SalesProstate CancerBreast CancerMaternal Health Risk**Course Image cover has been designed using assets from Freepik website.
Who this course is for:
Beginners curious about create basic Analytics using Healthcare Data
Health IT Professionals
Healthcare/Hospital Management Professionals
Professionals from a Non-Technical background who want to understand basics of Analytics
