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A streamlined range of courses with hands-on-experience to help you learn and implement data analytics for career or business growth.
Data Science with R - Course content
1.Introduction to Data Analytics
2.Data Analytics using Excel
3.Statistics for Data Analysts
4.Data Analytics using R
5.Data Visualisation using R
6.Machine Learning using R
7.Advanced Data Analytics techniques using R
8.Project
Benefits
Personalized training programs
Project work covered
Assignments to practice
Detailed Course Structure
1.Introduction to Data Analytics
a.What is Data Science?
b.Tools and Techniques in Data Science
2.Data Analytics using Excel
a.Introduction to Excel
b.Advanced Excel
3.Statistics for Data Analysts
a.Basic Statistics
b.Understanding Distributions
c.Hypothesis testing
4.Data Analytics using R
a.Introduction to R
b.Exploratory Data Analysis
c.Data Manipulation
5. Data Visualisation using R
a. Concepts in Data Visualization: Historical Graphs, Tufte, Few, Maeda, Grammar of Graphics
b. Basic and Advanced Plots. GGPLOT Interactive Plots: Multiple Graphs, Title, Axes, Labels, Color Palletes, vcd, Tableplot, Googlecharts, Shiny, Rcharts, D3.js
6. Machine Learning using R
a. Covariance and Correlation
b. Regression Analysis
c. Multicollinearity and Hetroscedasticity in Model
d. Outliers and VIF
e. Logistic Regression Modelling
f. Understanding the ROC Curve
g. Understanding the Confusion Matrix
h. KMeans Clustering
i. Decision Trees
j. Association Analysis
k. Types of Problems and Tasks
l. What is Machine Learning?
7. Advanced Data Analytics techniques using R
a. Time Series Analysis
b. Text Mining
c. Sentiment Analysis
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