Certified Data Scientist with R Language
Course
Online
Description
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Type
Course
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Methodology
Online
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Reviews
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Course material is good and the trainer is excellent in knowledge sharing.
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Course rating
Recommended
Centre rating
Ritu Gupta
This centre's achievements
All courses are up to date
The average rating is higher than 3.7
More than 50 reviews in the last 12 months
This centre has featured on Emagister for 8 years
Course programme
- Business Analytics foundation - RTools
- Lesson 00 - Business Analytics Foundation With R Tools
- 0.1 Business Analytics Foundation With R Tools
- 0.2 Objectives
- 0.3 Analytics
- 0.4 Places Where Analytics is Applied
- 0.5 Topics Covered
- 0.6 Topics Covered (contd.)
- 0.7 Career Path
- 0.8 Thank You
- Lesson 01 - Introduction to Analytics
- 1.1 Introduction to Analyics
- 1.2 analytics vs analysis
- 1.3 What is Analytics
- 1.4 Popular Tools
- 1.5 Role of a Data Scientist
- 1.6 Data Analytics Methodology
- 1.7 Problem Definition
- 1.8 Summarizing Data
- 1.9 Data collection
- 1.10 Data Dictionary
- 1.11 Outlier Treatment
- 1.12 Quiz
- Lesson 02 - Statistical Concepts And Their Application In Business
- 2.1 Statistical Concepts And Their Application In Business
- 2.2 Descriptive Statistics
- 2.3 Probability Theory
- 2.4 Tests of Significance
- 2.5 Non-parametric Testing
- 2.6 Quiz
- Lesson 03 - Basic Analytic Techniques - Using R
- 3.1 Introduction
- 3.2 Data Exploration
- 3.3 Data Visualization
- 3.4 Pie Charts
- 3.5 Correlation
- 3.6 Analysis of variance
- 3.7 Chi-squared test
- 3.8 T-test
- 3.9 Summary
- 3.10 Quiz
- Lesson 04 - Predictive Modelling Techniques
- 4.1 Predictive Modelling Techniques
- 4.2 Regression Analysis and Types of regression models
- 4.3 Linear Regression
- 4.4 Coefficient of determination R
- 4.5 How good is the model
- 4.6 How to find Liner regression equation
- 4.7 Commands to perform linear regression
- 4.8 Linear regression to predict sales
- 4.9 Case Study - Linear Regression
- 4.10 Case Study - Classification
- 4.11 Logistic regression
- 4.12 Example - Logistic regression in R
- 4.13 Logistic Regression Predicting recurrent visits to a web site
- 4.14 Cluster Analysis
- 4.15 Command to perform clustering in R
- 4.16 Hierarchical Clustering
- 4.17 Case Study - Implement K means and Hierarchical Clustering
- 4.18 Time Series
- 4.19 Cyclical versus seasonal analysis
- 4.20 Decomposition of Time Series
- 4.21 Caes Study- Time Series Analysis
- 4.22 Decomposing Non-Seasonal Time Series
- 4.23 Exponential Smoothing
- 4.25 Exponential smoothing and forecasting in R
- 4.26 Example - Holt Winters
- 4.27 White Noise
- 4.28 Correlogram Analysis
- 4.29 Box-Jenkins forecasting Models
- 4.30 Case Study - Time Series Data using ARMA
- 4.31 Business Case
- 4.32 Summary
- 4.33 Thank You
- 4.24 Advantages and Diadavantages of Exponential Smoothing
- Lesson 00 - Business Analytics Foundation With R Tools
Additional information
What is this course about?
Simplilearn’s R training is an ideal package for aspiring data analysts to gain expertise in data analytics. Participants at the end of the training will be technically competent in R programming language concepts such as data visualization, exploration; statistical concepts like linear & logistic regression, cluster analysis and forecasting.
Certified Data Scientist with R Language
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