Data analytics using R Course

Embark on an illuminating journey into the realm of data analytics with our comprehensive course on Data Analytics using R. Whether you're a data enthusiast looking to dive into the world of analytics or a seasoned professional aiming to enhance your skills, our curriculum is meticulously crafted to cater to learners of all levels. Enroll in our Data analytics using R course today and unlock the full potential of your data!

|| What will I learn?

  • Learn how to manipulate, clean, and preprocess data using R.
  • Develop practical skills in data analytics through hands-on exercises and projects.
  • Understand best practices and tips for effective data analysis using R.
  • Explore data visualization principles and techniques in R.
  • Participants will gain exposure to advanced topics in R, including machine learning concepts and techniques, working with big data, and optimizing R code and workflows for efficiency.

|| What will I learn?

  • Learn how to manipulate, clean, and preprocess data using R.
  • Develop practical skills in data analytics through hands-on exercises and projects.
  • Understand best practices and tips for effective data analysis using R.
  • Explore data visualization principles and techniques in R.
  • Participants will gain exposure to advanced topics in R, including machine learning concepts and techniques, working with big data, and optimizing R code and workflows for efficiency.

|| Requirements

  • Basic understanding of statistics and data analysis concepts.
  • No prior experience with R is necessary.

|| Requirements

  • Basic understanding of statistics and data analysis concepts.
  • No prior experience with R is necessary.

    • Introduction to R
    • What is R?, 
    • Installing R, 
    • R environment
    • Understanding R data structure 
    • Variables , Scalars
    • Vectors, Matrices, List
    • Data frames, functions, Factors
    • Importing data
    • Reading Tabular Data files
    • Loading and storing data with a clipboard
    • Accessing database, Writing data to file
    • Writing text & output from analyses to file
    • Manipulating Data
    • Selecting rows/observations
    • Rounding Number
    • Merging data
    • Relabeling the column names
    • Data sorting
    • Data aggregation
    • Using functions in R
    • Commonly used Mathematical Functions
    • Commonly used Summary Functions
    • Commonly used String Functions
    • User-defined functions
    • local and global variable
    • Working with dates
    • Looping
    • While loop ,
    • If loop
    • Charts and Plots
    • Box plot, Histogram, 
    • Pie graph ,Line chart
    • Scatterplot, Developing graphs

    • Introduction to R Programming
    • Overview of R and RStudio IDE
    • Basic syntax, data types, and variables in R


    • Data Import and Manipulation
    • Importing data from various sources (e.g., CSV files, Excel spreadsheets, databases)
    • Cleaning and preprocessing data using dplyr and tidyr packages


    • Exploratory Data Analysis (EDA)
    • Summarizing and visualizing data distributions, correlations, and patterns
    • Identifying outliers, missing values, and data inconsistencies


    • Data Visualization with ggplot2
    • Creating static and interactive plots: scatter plots, histograms, bar charts, etc.
    • Customizing plot aesthetics and themes for effective storytelling


    • Statistical Analysis with R
    • Descriptive statistics: mean, median, standard deviation, etc.
    • Inferential statistics: hypothesis testing, confidence intervals, p-values


    • Advanced Data Analytics Techniques
    • Predictive modeling: linear regression, logistic regression, decision trees
    • Cluster analysis: k-means clustering, hierarchical clustering
    • Time series analysis: forecasting, seasonality, trend detection


    • Reporting and Deployment
    • Generating dynamic reports and presentations using RMarkdown
    • Building interactive web applications with Shiny for data visualization and analysis

Get in touch

placement report

|| Frequently asked question

R is an advanced language that performs various complex statistical computations and calculations. Therefore, it is widely used by data scientists and business leaders in multiple fields, from academics to business. Moreover

Free and open-source. Everyone loves a bargain, and many value open sharing of technology. ... Reproducible research. ... Extremely easy data wrangling. ... Advanced visualizations. ... Quick implementation of new theoretical approaches. ... Easily extends to serve your specific needs.

Leading language when it comes to comprehensive statistical analysis packages , Community-developed code enhancements and bug fixes.

Open-Source. ... Strong Ability to Design Graphics. ... Extensive Range of Packages. ... Efficient in Software Development. ... Computing in a Distributed Environment. ... Data Wrangling. ... No Compilation. ... Enables Quick Calculations.

Related courses

Full Stack Analytics Course
Read more
Analytics using SAS Programming
Read more
MS Power BI Course
Read more
Tableau Course
Read more
Big Data Analytics Course
Read more
Data Analytics Course
Read more
Business Analytics Course
Read more
HR Analytics Course
Read more
Finance Data Analytics Course
Read more
Banking Data Analytics Course
Read more
Health Care Analytics Course
Read more
× Popup Image

Useful links

Categories

IT Infrastructure

Development

Data Science

Work with us

Company

Copyright Baroda Institute of Technology© 2024 | Design and Developed By Bit infotech