R programming Online Training

Module 2: Introduction to R programming

Objectives:

• This module starts from the basics of R programming, like datatypes and functions.
• In this module, we present a scenario and let you think about the options to resolve it, such as which datatype should one to store the variable or which R function can help you in this scenario.
• You will also learn how to use the ‘JOIN’ function in SQL.

Topics

• Variables in R
• Scalars
• Vectors
• Matrices
• List
• Data frames
• Using c, Cbind, Rbind, attach and detach functions in R
• Factors

Module 3: Data Manipulation in R

Objectives:

• In this module, we start with a sample of a dirty data set and perform data cleaning on it, resulting in a data set that is ready for any analysis.
• Thus, using and exploring the popular functions required to clean data in R.

Topics

• Data sorting
• Find and remove duplicates record
• Cleaning data
• Recoding data
• Merging data
• Slicing of Data
• Merging Data
• Apply functions

Module 4: Data Import techniques in R

Objectives:

• This module tells you about the versatility and robustness of R, which can take up data in a variety of formats, be it from a .csv file to the data scraped from a website.
• This module teaches you various data importing techniques in R.

Topics

• Reading Data
• Writing Data
• Basic SQL queries in R
• Web Scraping

Module 5: Exploratory Data Analysis

Objectives:

• In this module, you will learn that exploratory data analysis is an important step in the analysis.
• EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis. You will also learn about the various tasks involved in a typical EDA process.

Topics

• Box plot
• Histogram
• Pareto charts
• Pie graph
• Line chart
• Scatterplot
• Developing graphs

Module 6: Overview of Machine Learning techniques

Objectives:

• This module covers statistics and machine learning techniques used in the industry and will include case studies.

Topics

• Standard deviation
• Outlier
• Linear regression
• Multiple regression
• Logistic regressions
• Correlation

Module 7: Project Work

• 1 real-time project applying the skills covered across all modules

Related Courses at NeedinTech

R programming sits within a broader data and analytics skill set. These are the courses that pair well with it:

• Big Data fundamentals: Hadoop, Spark, and Hive for the large-scale data platforms that R analysts work alongside
• ETL testing: Data pipeline validation skills that complement R programming and analytics work
• Core Java training: Build the programming foundation that supports data engineering alongside R
• Placement assistance: Explore NeedinTech placement support and outcomes