Redprism came a long way intending to ‘Transform the Career and Lives’ of the individuals in the competitive world and up skilling their career, and creating a balance between the learning and implementing the real-time cases in education and achieve the dreams.
What is R programming?
R is an extremely powerful language extensively used for data analysis and statistical computing. Developed in the '90s and still, huge efforts have been made for the purpose of improving R's user interface. This programming language has a different statistical and graphical method which includes a machine learning algorithm, linear regression, time series, etc. Data analytics with R is performed through a series of steps which are programming, transforming, discovering, modeling and communicating the results.
Why Should You Adopt R Programming?
R Programming is the best mechanism for statistics, data analysis, and machine learning. It is more than a statistical package; it’s a programming language so that you can create your objects, functions, and packages.
Like all applications, R programs explicitly record the actions of analysis and make it easy to reproduce and update report, which means it can quickly try many ideas and factual issues.
It can easily be used anywhere. It’s platform-independent, so it can apply it to each operating system. And it’s free, so it can implement it in any organization without purchasing a license.
Not solely is R Programming free, but it’s also open-source. That means anyone can examine the source code to see exactly what it’s doing. This also means that anyone, can fix bugs and add features, rather than waiting for the vendor to find/fix the bug and add the feature –at their discretion– in a future release.
R Programming allows integrating with other languages (C/C++, Java, and Python) and enables to communicate with many data sources: ODBC-compliant databases (Excel, Access) and other statistical packages (SAS, Stata, SPSS, Minitab).
What students will achieve at the end of course?
ü Basic understanding of the business analytics
ü Installing R, R studio and workspace setup and get to learn about the different r packages
ü Learn the R programming and get to know how different statements are carried out in R
ü Achieve an in-depth knowledge and understanding of any data structure which is used in R programming and knows about the process of import and export of data in R
ü Get an idea of the usage of different graphics in R for the purpose of data visualization
ü Understand the use of linear, nonlinear reversion models and different classification methods for data analysis.
Exclusive Key factors at Redprism
All our R trainers at Redprism are certified and well qualified data analytics experts. So, we will teach you with the best R training and support.
According to the students’ convenience, we schedule classroom and online training with affordable R training cost in Noida. So, comparing other centers, Redprism is a top class offering R training, with complete hands-on sessions and practical classes.
Prime Features why to Join Red Prism?:-
· Industry Expert Trainers with 10-15 years of experience.
· Course content is curated by best Subject Matter Experts.
· Practical Assignments.
· Real Time Projects.
· Video recording of each and every session.
· We conduct regular Mock tests and certifications at the end of course.
· Certification Guidance.
· Recognized training complete certificate.
· 100% Placement Assistance.
· Less fees as compared to other institutes.
· Flexi payment options
· Scholarship Available
- What is R?
- Why R?
- Installing R
- R environment
- How to get help in R
- R Studio Overview
- Variables in R
- Data frames
- Cbind,Rbind, attach and detach functions in R
- 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
- Cross Tabulation
- 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
- Creating a graph
- Density Pot
- Dot Pot
- Bar Pot
- ine charts
- Pie charts
- Box po
- Scatter Pot
- Graphical Parameters
- Customizing Graph
- Exporting Graphs
- Lattice graphs
- Combining Plot
- Ggplots graph
- Probability graphs
- Creating Random Numbers
- Generating Random Numbers
- Random Sampling
- Sentiment analysis with Machine learning
- C 5.0
- Support vector Machines
- K Means
- Random Forest
- Naïve Bayes algorithm
- Linear Regression
- Non Linear Regression
- Advanced analyses – ANOVA and 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
- API in R (Twitter and Facebook)
- Word Cloud in R