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Data Science with R

Course Description

Data Science using R gives the best statistical computing and design. Data science with R offers data exploration, visualization, predictive, and descriptive analytics techniques with R language. R is the most flexible and powerful analytic tool to develop statistical software and data analysis. R is trending now and has immense demand in the future. R is open-source, good data handling capability, graphical capabilities, advancements, and cost-efficient as compared to SAS statistical tool. R is also very simple and easy to learn.

Hachion Data Science with R online training provided by industry experts from end to end. Data Science using R course tutorial includes data science tools and techniques including cleaning, exploring, visualizing data using the R language. Through our Data science R language online course, you will learn about packages, structures, statistical concepts, cluster analysis, import/export data, and forecasting. By enhancing theoretical and practical knowledge one can easily appear for the Data Science certification exam.

Course Fee : 341.3 USD

Data Science with R Learners from Hachion: 65
Course Schedule

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Choose the best training mode which suits to your requirement
Live online training

USD 341.3

Training Fee: USD 426.7 20% Discount

  • Live interactive online training
  • Daily Assignments and Lab exercises
  • Resume and certification guidance
  • Mock interview and live project assistance
  • Resume marketing and job assistance
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Mentoring mode training
  • Live interactive online training
  • Daily Assignments and Lab exercises
  • Resume and certification guidance
  • Mock interview and live project assistance
  • Resume marketing and job assistance
Live online training and internship
  • Live interactive online training
  • Daily Assignments and Lab exercises
  • Resume and certification guidance
  • Mock interview and live project assistance
  • Resume marketing and job assistance

Course Content

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  •   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

  •  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

  •   API in R (Twitter and Facebook)

  •   Word Cloud in R

Data Science with R Training FAQs

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We provide 100% job assistance to the Hachion students, once they complete the course. We also provide resume writing, mock interviews, and resume marketing services as part of our job assistance program. 

We offer three modes of training in the Data Science online training program.

  • Self Placed
  • Mentorship
  • Instructor-Led

Basic Knowledge of Variables, Control Statements & Loops, etc., are enough to learn R With Data Science course. R is easy to learn & use for beginners compared to other programming languages.

This Data Science field intensively deals with mathematics, for analysis of data and algorithms. A decent mathematical background is necessary and we engineers definitely excel at that! If you have had a mathematical background at school and covered engineering mathematics (such as probability, statistics, linear algebra, etc/), you're good to go! Maybe you could just brush up the topics.

The course assumes a working knowledge of key data science topics (statistics, machine learning, and general data analytic methods). Programming experience in some language (such as R, MATLAB, SAS, Mathematica, Java, C, C++, VB, or FORTRAN) is expected. In particular, participants need to be comfortable with general programming concepts like variables, loops, and functions. Experience with Python is helpful (but not required).

This course is perfectly aligned with the current industry requirements and gives exposure to all the latest techniques and tools. The course curriculum is designed by specialists in this field and monitored improved by industry practitioners on a continual basis.

The average salary for Data scientists in the US is $124,244 per year - indeed

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