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Data Analytics Course in Mumbai

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  • Data Analytics using R Programming
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10 SEATS

COURSE INSTRUCTOR

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Mr. Ankur Bhardwaj

Sr. Data Analyst

Mr. Ankur Bhardwaj has 8+ years of industrial experience and he is one of the best instructors at digiStackedu.

BASIC INFORMATION

  • Price : Call Now!
  • Lessons : 10
  • Length : 1 Month
  • Level : Advance
  • Category : Analysis
  • Started : 15 APR 2024
  • Shift : 02
  • Class : 30
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Course Description

R is a very popular programming language that is widely used for data mining and analysis. In this course, you'll learn about R programming advanced concepts with R data analytical libraries apart from this, you will work on live projects with our experts. This course focuses on how to clean, process, and analyze different varieties of data, how to create a data frame, how to handle missing values, and how to do predictive analytics.

This is one of the best courses by which you can upgrade skills in data analytics, you will get a top-level instructor and work on R Studio apart from this you will get a chance to work on a real-time project.

We will start this course with basics of R programming and then you will move to the R advance level libraries that is required to do data analysis like ggplot, dplyr and Mice a part from this,you will learn how to analyze different types of data and how to visualize and generate reports.

Course Syllabus

Module 1: An Introduction to R Programming Language.

  1. Introduction to R Programming.
  2. Variables,data type and operators in R.
  3. Type casting and user input in R.
  4. Basic problem solving skills in R.
  5. Working on R Vectors.
  6. Understanding Arithmetic Operators.
  7. Working on Logical Operators.
  8. How to Create a Matrix in R.
  9. Matrix Manipulation rbind and cbind functions.
  10. Understanding Slice a Matrix.
  11. Working on Factors and Categorical Variables.
  1. Introduction to Conditional Statements.
  2. Understanding Basics of If and Else.
  3. Controlling the flow of program using IF and Else.
  4. User Input with If-Else
  5. Nesting of If-Else Staements.
  6. Practical Demo on If-Else.
  7. Assignments on If-Else Lecture.
  8. IF and Else with Vectors.
  9. Nesting of IF and Else Statements.
  1. Introduction to Loop in R programming
  2. Basics of for Loop and While Loop.
  3. Combining Loop and If-Else Statements.
  4. Positive and Negative Loop.
  5. Practical on For Loop in R programming.
  6. Practical on Nested For Loop in R programming.
  7. Practical on While Loop in R programming.
  8. Practical on Nested While Loop in R programming.
  9. For and while Loop on R Vectors.
  10. For and while Loop on R Matrix.
  11. Switch Case Statement in R Programming.
  1. Introduction to DataFrame in R.
  2. Creating R Data Frame using Vectors.
  3. Slicing on R Data Frame.
  4. Subsetting Operation on R DataFrame.
  5. nrow() and ncol() operations.
  6. Getting unique values from R DataFrame.
  7. Discriptive Stats on R DataFrame.
  8. dplyr and tidyverse package in R.
  9. Filter a Data Frame in R.
  10. Applying user defined functions on R Data Frame..
  11. Creating a DataFrame from csv File using R Programming.
  1. An Introduction to Missing Values.
  2. Working on Data Preprocessing.
  3. Loading files and generating Missing Values.
  4. Pipeline Operator in R.
  5. Checking Null values in R DataFrame.
  6. Removing Null values from R DataFrame.
  7. Replacing Null values from Mean and Median.
  8. Renaming a column of R DataFrame.
  9. Calculating count of Null values.
  1. An Introduction to ggplot2.
  2. Loading Dataset for advance level plotting.
  3. Working on Historams in R.
  4. Drawing Correlation Matrix in R.
  5. Undersatnding bar Plot.
  6. Working on Mosaic Plot.
  7. Drawing Scatter Plot using geompoint.
  8. Linear Line on Scatter Diagram.
  9. Working on title,subtitle and caption.
  10. Handling Scale of R Graphs.
  11. Applying different theme on R Graphs.
  12. Handling Scale of R Graphs.
  13. Performing Grouping Opertion on R Graphs.
  14. Working on Pie Chart in R.
  15. Working on box plot in R.
  1. An Introduction to GroupBy Operation.
  2. Implementing GroupBy in R.
  3. Selecting and Filtering DataFrame Columns.
  4. Skip Null values and Calculating Mean.
  5. Skip Null values and Calculating Median.
  6. Statistical Operation on GroupBy.
  7. Sum and count Operation on GroupBy.
  8. Finding unique values using GroupBy.
  1. Basics of statistics.
  2. Understanding variance and standard Deviation.
  3. An Introduction to Hypothesis Testing
  4. Null vs alternate Hypothesis.
  5. Understanding P value.
  6. Level of significance in statistics.
  7. Practicals on chi square Test.
  8. Practicals on one way ANOVA Test.
  9. Practicals on two way ANOVA Test
  1. An Introduction to data analysis.
  2. Understanding machine learning models.
  3. An Introduction to regression technique.
  4. Implementing linear and multiple linear Regression in R.
  5. Implementing polynomial regression in R.
  6. Introduction to decision trees.
  7. Implementing decision tree in R Programming.
  8. Introduction to Support Vector Machine.
  9. Implementing SVM using R Programming.
  10. An Introduction K Nearest Neighbour.
  11. Implementing KNN using R Programming.
  1. An Introduction to Project Development.
  2. Project Assignments.
  3. Report Generation.
  4. Final Project Submission.

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Student Reviews

Our Student reviews after completion of this course.

Anand Mishra

Anand Mishra

Best R Course,According to me DigiStackEdu is good learning place for technical coures as i got 100% practical sessions.

Rahul Kumar

Rahul Kumar

Hi,I am non tecnical but feeling strong in Analytics now,Successfully completed my project and got 1st rank,thanks for upgarding my skills.

Mr. Mukesh

Mr. Mukesh

DigStackEdu is one of the best online learning platform,Got proper lectures and learning material.I will suggest everyone to join.

Kamal Jalal

Kamal Jalal

Different style of teaching for online study.teachers will not end class until you are not able to understand the concept.

Nadeem Malik

Nadeem Malik

Great Learning with DigiStackEdu,they will make you technical even if you are non technical,team was very supportive.

Frequently Asked Questions


Yes, you will get industry valid certificate after completeion of this course and you will be tagged as a Data Analyst.
Yes, You can pay your fee in two installments but it depands on the course you selected.
Yes, You can join R Programming online course even if you do not belong from computer science background. Our experts will help you to upgarde your technical skills, you just need some basic computer skills for this course.
This course is 100% practical oriented, you will work on R Studio and GGplot moreover, you will work on how to clean, filter, analyze and visualize data.
DigiStackEdu provide cost effective and quality training,We focus on every student and we understand the value of money.Our Trainers are certified and having more than 10+ years of experience in Digital Marketing, Data Science, Java Programming, Web Designing, Big Data and Data Analytics moreover,We have Trained 47,000+ students and professionals who are working in top level IT companies.
DigiStackEdu only provide internship in Data Science, Digital Marketing, Java Programming, PHP programming and Web Development.For more details please contact to our support team.
R is the most popular programming language for data analysis, most of the IT companies will not select you without R knowledge.This R programming course open a door for you in data analytics.
You can submit your fee after 3 classes, Even after that if you face any issue with in the next 7 days then you can contect to our support team for the return.
We'll start this course by very basic concepts of R Programming further we'll move to the advance concept of R like ggplot,tidyverse and many essential libraries that is highy required to be a data analyst.It will take approx 1 month to be master of R programming after that you will get a industry valid cerficate and will get a tag as a Data Analyst.




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