Data Analytics Certification Courses in Bangalore

Data Science With R Training in Bangalore

Data science with r Training – Data science is one of the most promising areas in today’s world. It is an interdisciplinary approach that banks a lot on the application of statistical methods to computation with added stress been given to fields such as machine learning in order to improve outcomes. As such the subject matter concerns almost anything and everything related to data – its collection and organisation. Thus data analytics, data mining, machine learning and many other fields can be thought of as being within this broad discipline. Learn data science with R training in btm layout, Bangalore from experts and working professionals.

The move towards the field of data science is gradually becoming more and more visible. This process is predicted to undergo a rapid thrust. The field is poised to be one of the biggest employment generators in the coming decade. With the potential of data science to predict patterns of consumer behavior, market variations etc, it is proving to be a much sought after domain.

R is one of the top programing languages that finds application in the field of system analysis and data science. It is an open source language with millions of registered users globally. It finds widespread application today and is probably the best coding language for huge data intensive simulations. It is a powerful language for scripting and offers an unparalleled degree of visualization. R proves to be extremely effective with its graphics and chart preparations that offer a better grasp of the data. Thus R is an effective tool that helps in better decision making through data analysis. The existence of a huge and vibrant community support supplements the learning process.

The data science course that our institution provides seeks to harness the vast potential that the knowledge of data science with an effective grasp of R can offer. By choosing our institution for guidance you will be availing the following:

  • Sound expertise in data science with a working knowledge of R that gives a great enhancement to your employment prospects.
  • Training from experienced hands who are well versed in the fields of data science and R programing.
  • A course that is fine tuned to the requirements of the industry.
  • Constant updation in concurrence with the changes in the industry.
  • Flexibility in class timings to cater to the needs of students.
The unmatched discipline and efficient methodology that we follow is guaranteed to grant you confidence and competence in data science.


SECTION 1: Introduction
  • What is R?
  • Why R?
  • Installing R
  • R environment
  • How to get help in R
  • R console and Editor
SECTION 2: Understanding R data structure
  • Variables in R
  • Scalars
  • Vectors
  • Matrices
  • List
  • Data frames
  • Using c, C bind, R bind, attach and detach functions in R
  • Factors
SECTION 3: Importing data
  • Reading Tabular Data files
  • Reading CSV files
  • Importing data from excel
  • Importing data from SAS
  • Accessing database
  • Saving in R data
  • Loading R data objects
  • Writing to files
SECTION 4: Manipulating Data
  • Selecting rows/observations
  • Selecting columns/fields
  • Merging data
  • Relabelling the column names
  • Converting variable types
  • Data sorting
  • Data aggregation
SECTION 5: Using functions in R
  • Commonly used Mathematical Functions
  • Commonly used Summary Functions
  • Commonly used String Functions
  • User defined functions
  • local and global variable
SECTION 6: R Programming
  • While loop
  • If loop
  • For loop
  • Arithmetic operations
SECTION 7: Charts and Plots
  • Box plot
  • Histogram
  • Pareto charts
  • Pie graph
  • Line chart
  • Scatterplot
  • Developing graphs
SECTION 8: Advanced Concept
  • Social media analysis(Twitter)through API
  • Web apps in R
SECTION 9: Statistics and Machine Learning
  • Standard deviation
  • Outlier
  • Linear regression
  • Multiple regression
  • Logistic regressions
  • Chi square
  • Anova
  • Clustering
  • Correlation
  • Decision tree
  • K-NN Algorithm

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