Data Science with R
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About Data Science with R
R is an open source programming language. It combines Big data analysis, Simulation, graphics, etc. It is the leading and most flexible programming language. Also it is the most powerful. By using R the data science is more flexible. The Data Science with R combines a Statistical Modeling. By using R the Data Science is gaining on big-data analysis packages due to flexibility. Also, provides documentation and open-source.
Data Science with R Course Objectives
What are the Course Objectives?
After completion of the data science with R Course, you will be expertise and eligible for:
- Complete knowledge of Data Science
- Able to analyze big data
- Able to work in Data Mining
- Able to work on Statistic
- Learn how to use different tool like Tableau, Map Reduce
- Creation of Decision tree
- Explore Big data concept
Who should go for this course
- Any IT experienced Professional who are interested to build their career in Development/ Data Scientist.
- Any B.E/ B.Tech/ BSC/ MCA/ M.Sc Computers/ M.Tech/ BCA/ BCom College Students in any stream.
- Fresh Graduates.
Pre-requisites
The course can learn by any IT professional having basic knowledge of :
- Mathematics
- Statistic
- Any Programming Language
COURSE SYLLABUS
Introduction to R Language
- What is R? - Why R? - Installing R - R environment - How to get help in R - R Studio Overview
Understanding R data structure
- 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
Importing data
- 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
Manipulating Data
- 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
Using functions in R
- 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
R Programming
- While loop - If loop - For loop - Arithmetic operations
Charts and Plots
- Box plot - Histogram - Pie graph - Line chart - Scatterplot - Developing graphs - Cover all the current trending packages for Graphs
Machine Learning Algorithm
- Sentiment analysis with Machine learning - C 5.0 - Support vector Machines - K Means - Random Forest - Naïve Bayes algorithm
Statistics
- Correlation - Linear Regression - Non Linear Regression - Predictive time series forecasting - K means clustering - P value - Find outlier - Neural Network - Error Measure
Leading Topics
- Overture of R Shiny - What is Hadoop - Integration of Hadoop in R - Data Mining using R - Clinical research preface in R - API in R (Twitter and Facebook) - Word Cloud in R
Training Features
Instructor-Led Training Sessions
We believe to provide our students the Best interactive experience as part of their learning
Flexible Schedule
Do not hesitate to ask… because we will work according to your calendar
Industry Specific Scenarios
Students are provided with all the Real-Time and Relevant Scenarios
Expert Trainers
We Constantly evaluate our trainers and only the “Best” Provides the Training
e-Learning Sessions
Online training sessions are held Live and we provide students with the Training Videos
Support
No Problem@ all…!!! Your Question will be answered by Us as soon as possible