Data Science also called as data-driven science. Data science is order to solve analytically complex problems. It is a multidisciplinary field of data inference, algorithm development, and technology improvement from various forms. Data Science is similar to Data mining. It is used by mathematics, statistics, computer science, information science, machine learning, data mining, data visualization, databases, classification, cluster analysis and data quantification. Greens Technologys helps to get up to date knowledge in Data science.

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Our Data Science Course syllabus covering some important topics like Introduction to R Programming, R Data Structure, importing data, manipulating data, Using functions in R, R Programming, charts and plots, Machine Learning Algorithm, Statistics, Data science real-time project and Data science placement training in Chennai.

- What is R?
- Why R?
- Installing R
- R environment
- How to get help in R
- R Studio Overview

- Variables in R
- Scalars
- Vectors
- Matrices
- List
- Data frames
- Cbind, Rbind, attach and detach functions in R
- Factors
- Getting a subset of Data
- Missing values
- Converting between vector types

- Reading Tabular Data files
- Reading CSV files
- Importing data from excel
- Loading and storing data with clipboard
- Accessing database
- Saving in R data
- Loading R data objects
- Writing data to file
- Writing text and output from analyses to file

- Selecting rows/observations
- Rounding Number
- Creating string from variable
- Search and Replace a string or Number
- Selecting columns/fields
- Merging data
- Relabeling the column names
- Data sorting
- Data aggregation
- Finding and removing duplicate records

- Apply Function Family
- Commonly used Mathematical Functions
- Commonly used Summary Functions
- Commonly used String Functions
- User defined functions
- local and global variable
- Working with dates

- While loop
- If loop
- For loop
- Arithmetic operations

- Box plot
- Histogram
- Pie graph
- Line chart
- Scatterplot
- Developing graphs
- Cover all the current trending packages for Graphs

- Sentiment analysis with Machine learning
- C 5.0
- Support Vector Machines
- K Means
- Random Forest
- Naïve Bayes algorithm

- Correlation
- Linear Regression
- Non-Linear Regression
- Predictive time series forecasting
- K means clustering
- P value
- Find outlier
- Neural Network
- Error Measure

- Overture of R Shiny
- What is Hadoop
- Integration of Hadoop in R
- Data Mining using R
- Clinical research preface in R

- Data Science with SAS
- Data Science with R
- Certified Data Scientist with Python course
- Data Science with Advanced SAS: Macros & SQL
- Machine Learning for Data Science and Analytics

- API in R (Twitter and Facebook)
- Word Cloud in R