| 1 -Business Data Preprocessing.mp4 | 76.5 MB | ||
| 1 -Clustering.mp4 | 55.3 MB | ||
| 1 -GGPlot.mp4 | 61.4 MB | ||
| 1 -Linear Regression.mp4 | 35.3 MB | ||
| 1 -The Evolution of Business Intelligence (BI).mp4 | 44.9 MB | ||
| 2 -Business Intelligence Value Chain.mp4 | 131.3 MB | ||
| 2 -Classification.mp4 | 159.4 MB | ||
| 2 -Clustering - Hands-on.mp4 | 121.5 MB | ||
| 2 -Exploratory Data Analytics.mp4 | 19.8 MB | ||
| 2 -GGPlot - Hands-on.mp4 | 188.6 MB | ||
| 3 -Applications of Business Intelligence.mp4 | 67.6 MB | ||
| 3 -Exploratory Data Analytics - Hands-on.mp4 | 83.3 MB | ||
| 3 -Geo Plots.mp4 | 64.9 MB | ||
| 3 -Linear Regression - Hands-on.mp4 | 43.4 MB | ||
| 3 -Time Series Analysis.mp4 | 55 MB | ||
| 4 -Classification - Hands-on.mp4 | 166.7 MB | ||
| 4 -Data Cleaning - Hands-on.mp4 | 143.8 MB | ||
| 4 -Geo Plots - Hands-on.mp4 | 325.9 MB | ||
| 4 -Time Series Analysis - Hands-on.mp4 | 154.3 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 21 total files | |||
Business Intelligence and Data Analytics using R
https://WebToolTip.com
Published 7/2025
Created by A. Robert Singh,Suganya A
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 19 Lectures ( 4h 17m ) | Size: 2 GB
Transforming Raw Data into Actionable Insights with R – A Practical Approach to Business Intelligence and Analytics
What you'll learn
Explain the concept of Business Intelligence (BI) and describe its historical evolution, key milestones, and the technological advancements
nstrate understanding of data preprocessing techniques using R by identifying, cleaning, transforming, and preparing raw business data for analysis
Apply supervised learning techniques to build predictive models with R using labeled business data, and evaluate model performance
Utilize unsupervised learning techniques such as clustering using R to uncover hidden patterns, groupings, and insights from unlabeled business data
Create and interpret a variety of data visualizations using R to effectively communicate business insights and support data-driven decision-making.
Requirements
basic programming knowledge
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