Online Data Analytics With R Programming Course


A Certified Course to give you an understanding of R Programming and its extensive application in the field of Data Analytics. This will be followed by internship opportunities in the field of Data Analytics to make you INDUSTRY-READY.

₹ 6,499
₹ 4,999/-

Offer expires in Calculating .....

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Instructor

Soumendra Dhanee

8-10 Weeks

8 Levels

61 Lectures

8-10 Weeks

8 Levels

61 Lectures



₹ 6,499
₹ 4,999/-

Offer expires in Calculating .....

Take This Course

Key Features


  • Certified Course
  • Delivery - Video Lectures
  • Assessment - Quizzes And Assignments
  • More Practical Less Theory
  • Internship Opportunity To Top Performers

Course Description

Learn and Master Data Analytics with R Programming.

This Online Data Analytics Course is designed for students like you who wish to build a career in data science. At the end of this course, you will be able to use R Programming for world's most wanted skill - Data Analysis.

Quizzes and Assignments shall ensure that you understand everything well. Doubt solving, guidance and mentorship shall be provided through and through. Best Part? You decide the timings for the class. You can study the course in your own free time, anytime within 1 year.

Along with this being a certified course, we also offer internship opportunities to all students who perform well in the course.

Flexible Learning

Learn from any place, at any time. No strings attached.

Unlimited Retakes

Gain access to the course unlimited times, for 365 days. Leave no stones unturned.

Interactive & Animated

Fun, animated, and informative videos with an interactive and challenging quiz at the end of each video. Review your knowledge and mug up no more.

Experienced Mentor

With years of experience in the industry, the Mentor has been implementing Data Analytics for a lot of clients. With an indepth undertsanding of Data Analytics and working experience with R Programming, he has seamlessly integrated Data Analytics with R Programming in this course.

Pocket Friendly

Learn Data Analytics using R Programming at a reasonable fee. Recover the money you invest as your first month's stipend.

Introduction to The Course

6 Lectures

Lecture 1:What is data science?
Lecture 2:Data
Lecture 3:Insights
Lecture 4:Methods, Processes & Systems
Lecture 5:Why R for data science?
Lecture 6:What will you learn from the course?

Introduction to R

17 Lectures

Lecture 1:Setting up R and R studio on Mac
Lecture 2:Setting up R and R studio on Windows
Lecture 3:Setting up R and R studio on Ubuntu
Lecture 4:Introduction to R studio
Lecture 5:Introduction to R Ecosystem
Lecture 6:Basics of R
Lecture 7:Lists
Lecture 8:Matrix
Lecture 9:Conditionals
Lecture 10:Loops
Lecture 11:Reading and writing CSV
Lecture 12:Data Frames
Lecture 13:Functions
Lecture 14:Apply Family
Lecture 15:More about reading and writing CSV
Lecture 16:Loops and Vectorisation
Lecture 17:R Best Practices

Data Wrangling

8 Lectures

Lecture 1:Vectors vs Lists vs DataFrames
Lecture 2:Reading and writing Data
Lecture 3:Introduction to Tidyerse
Lecture 4:dplyr filter
Lecture 5:dplyr arrange
Lecture 6:dplyr select
Lecture 7:dplyr mutate
Lecture 8:dplyr summarise

Visualisations

17 Lectures

Lecture 1:Thinking about data
Lecture 2:Categorical Data with Factor Variables
Lecture 3:Thinking about visualisation
Lecture 4:Grammar of Graphics and ggplot2
Lecture 5:EDA part 1 & 2
Lecture 6:Missing Values part 1&2
Lecture 7:Back to summarising datasets part 1,2&3
Lecture 8:Scatterplots
Lecture 9:Histograms
Lecture 10:Barplots
Lecture 11:Boxplots
Lecture 12:QQ-plots
Lecture 13:Multivariable graphs
Lecture 14:Corrgrams
Lecture 15:Facet Plots
Lecture 16:Telling Stories with Data
Lecture 17:Visualisation pitfalls

Statistics

2 Lectures

Lecture 1:Descriptive Statistics
Lecture 2:Inferential Statistics

Machine Learning

5 Lectures

Lecture 1:What is Machine Learning?
Lecture 2:Linear Regression
Lecture 3:Logistic Regression
Lecture 4:Steps in Data Science Workflow
Lecture 5:Introduction to Caret

Git and GitHub

5 Lectures

Lecture 1:Introduction to Git and GitHub
Lecture 2:Getting Started with Git and GitHub
Lecture 3:How Git works?
Lecture 4:A Git workflow template
Lecture 5:Common Git/GitHub usage patterns

Case Study

1 Lecture

Lecture 1:Case Study

Soumendra Dhanee

Founder, Two Beards

Soumendra has been working as a data scientist for close to 7 years now. In that time, he has gone on to lead data science teams in companies in various domains, including Educational Technology, Human Resources, Medical Diagnostics, and Transportation. He has conducted R workshops in academia and financial institutions in India and abroad. He is the founder of difference-engine.ai, where he works on bringing large deep learning and machine learning models to small devices.

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