Technoglobe Jaipur’s No.1 institute for training and internship is providing training in R Programming. Technoglobe has been shining in the field of technology since more than one and a half decade. Our remarkable achievement includes affiliation with Rajasthan Technical University and we also became the authorized partners of Microsoft & HP.

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R is a powerful language for data analysis, data visualization, machine learning, statistics. Originally developed for statistical programming, it is now one of the most popular languages in data science.**R Programming Course Training in Jaipur- Technoglobe is one of the best R Programming training institute in Jaipur with 100% Placement Support. We provides real-time and placement focused R Programming training in Jaipur. We have a track record of more than 1000 placements.**

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- Types of variables
- Using Variables
- Logical Variables and Operators
- The "While" Loop
- Using the console
- The "For" Loop
- The "If" statement
- What is a Vector?
- Let's create some vectors
- Using the [] brackets
- Vectorized operations
- The power of vectorized operations
- Functions in R
- Packages in R
- Matrices
- Building Your First Matrix
- Naming Dimensions
- Colnames() and Rownames()
- Matrix Operations
- Visualizing With Matplot()
- Subsetting
- Visualizing Subsets
- Creating Your First Function
- Importing data into R
- Exploring your dataset
- Using the $ sign
- Basic operations with a Data Frame
- Filtering a Data Frame
- Introduction to qplot
- Building Dataframes
- Merging Data Frames
- Loop Functions
- lapply()
- sapply()
- apply()
- tapply()
- mapply()
- Regular Expressions
- Saving r objects
- dplyr package
- Shiny Apps

**R with Real Time Examples**

** Statistics with R**

- Data collection
- Data collection - Questionaire Designing
- Data collection - Observation
- Data collection - Case Study Method
- Qualitative Data Vs Quantitative Data
- Data Patterns
- Deciles Statistics
- Venn Diagram
- Central limit theorem
- Chebyshev's Theorem
- Kurtosis
- Normal Distribution
- Laplace Distribution
- Log Gamma Distribution
- Rayleigh Distribution
- Exponential distribution
- Multinomial Distribution
- Binomial Distribution
- Beta Distribution
- F distribution
- Negative Binomial Distribution
- Gamma Distribution
- Chi-squared Distribution
- Geometric Mean
- Harmonic Mean
- Outlier Function
- Stem and Leaf Plot
- Poisson Distribution
- Cumulative Poisson Distribution
- Inverse Gamma Distribution
- Continuous Uniform Distribution
- Hypergeometric Distribution
- Harmonic Number
- Gumbel Distribution
- Comparing plots
- Power Calculator
- Process Sigma
- Harmonic Resonance Frequency
- Standard normal table
- Pooled Variance (r)
- Mean Deviation
- Means Difference
- code(+theory) for Descriptive:
- entral tendency:
- Arithmetic Mean
- Arithmetic Median
- Arithmetic Mode
- Arithmetic Range
- Range Rule of Thumb
- Adjusted R-Squared
- Standard Deviation
- Relative Standard Deviation
- Analysis of Variance
- Grand Mean
- Boxplots
- Quartile Deviation
- Frequency Distribution
- Bar Graph
- Dot Plot
- Scatterplots
- Correlation Co-efficient
- Pie Chart
- Histograms
- Cumulative Frequency
- Cumulative plots
- Skewness
- Goodness of Fit
- Transformations
- Trimmed Mean
- Reliability Coefficient
- Linear regression
- Logistic Regression
- Quadratic Regression
- Regression Intercept Confidence Interval
- Residual sum of squares
- Equation Sum of Square
- Standard Error ( SE )
- Root Mean Square
- Cohen's kappa coefficient
- Ti 83 Exponential Regression
- Shannon Wiener Diversity Index
- Building Linear Regressors
- Interpreting Regression Results and Interactions Terms
- Performing Residual Analysis & Extracting Extreme Observations Cook's Distance
- Extracting Better Models with Best Subsets, Stepwise Regression, and ANOVA
- Validating Model Performance on New Data with k-Fold Cross Validation
- Building Non-Linear Regressors with Splines and GAMs
- Building Logistic Regressors, Evaluation Metrics, and ROC Curve
- Understanding the Concept and Building Naive Bayes Classifier
- Building k-Nearest Neighbors Classifier
- Building Tree Based Models Using RPart, cTree, and C5.0
- Building Predictive Models with the caret Package

**Machine Learning with Real Time Examples**

**Big Data & Hadoop with Real Time Examples**

- Introduction to Big Data
- Getting started with Hadoop
- Hive Concepts
- Pig Concepts
- Use case on log collections & analysis
- Use Case on Ecommerece

**Take Away – R Programming Training in Jaipur, R Programming Certification Courses in Jaipur**