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Introduction to Data Science and Analytics using R

Learn to create & test Machine Learning & Data Science Models in R from Data Science experts. Code templates included.
4.3
☆☆☆☆☆ 4.3/5
(2 reviews)
52 students
Created by
Diganta Nil Chatterjee

9.0

Classbaze Grade®

9.8

Freshness

7.8

Popularity

8.9

Material

Detailed Analysis »

Learn to create & test Machine Learning & Data Science Models in R from Data Science experts. Code templates included.
Go to course »
Platform: Udemy
Price: check current price
Video: 5h 0m
Language: English
Next start: On Demand

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Classbaze Rating

Classbaze Grade®

9.0 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

9.8 / 10
This course was last updated on 2/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

7.8 / 10
We analyzed factors such as the rating (4.3/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

8.9 / 10
Video Score: 8.3 / 10
The course includes 5h 0m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 3 hours 52 minutes of 7 RStudio courses on Udemy.
Detail Score: 9.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
14 resources.
0 exercise.
0 test.

In this page

About this course

  The course will teach you this
  What you need to START the course
  Who can start this course?
General questions
  Coupons & Discounts
  Guarantees & money back
  Financial aid
Teacher
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About the course

Are you interested in the field of Data Science and Machine Learning but haven’t had experience in it? Then this course is for you!
This course has been designed by a professional Data Scientist so that I can share my knowledge and industry experience and help you learn the basics of data science algorithms and coding libraries.
This course includes a step-by-step approach to Data Science and Machine Learning. With each lecture, you will develop the mathematical understanding as well as the understanding of necessary libraries to help you ace Data Science interviews and enter into this field.
The course is structured in a very crisp and comprehensive manner to help you understand industry-relevant algorithms. It is structured the following way:
Part 1.) Getting started with R
•Setting up R
•Getting Started with R Studios IDE
• Swirl
Part 2.) Introduction to Statistical Measures
•Measures of Central Tendencies
•Introduction to Data Science using R
Part 3.) Data Processing and Data Visualisation in R
•Measures of Dispersions and Outlier Treatment
•Missing Value Treatment using R
•Data Visualization using R ( boxplots, bubble plots, heat plots, automated-EDA in R)
Part 4.) Building Regression Models in R
•Linear Regression Theory
•Linear Regression using R
•Multivariate Linear Regression Theory
•Multivariate Linear Regression using R (Multiple Linear Regression, R-square, Adjusted R-square, p-value, backward selection)
Part 5.) Building Classification Models in R
•Classification using Logistic Regression
•Logistic Regression and Generalized Linear Models in R & Measures of Accuracy for a Classification Models (AIC, AUC, Confusion Matrix, Precision, and Recall)
Part 6.) Random Forest Models in R
•Introduction to decision tree classifier (trees package, Gini index, and tree pruning )
•Creating decision tree and Random Forest in R (Random forest package in R, hyper-parameters tuning, visualizing a tree in R)
•Building Random Forest Regressors

The course takes you through practical exercises that are based on real-life datasets to help you build models hands-on.
And as additional material, this course includes R code templates which you can download and re-use on your own projects.

What can you learn from this course?

✓ Basics of statistical modelling
✓ Basics of data science using R and Python
✓ Forecasting and prediction using Data
✓ Data Visualisation

What you need to start the course?

• No programming experience needed

Who is this course is made for?

• Engineering students
• Beginner python and R data analysts
• Data science enthusiasts
• Business graduates

Are there coupons or discounts for Introduction to Data Science and Analytics using R ? What is the current price?

The course costs $14.99. And currently there is a 40% discount on the original price of the course, which was $37. So you save $22 if you enroll the course now.
The average price is $15.0 of 7 RStudio courses. So this course is 0% cheaper than the average RStudio course on Udemy.

Will I be refunded if I'm not satisfied with the Introduction to Data Science and Analytics using R course?

YES, Introduction to Data Science and Analytics using R has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any financial aid for this course?

Currently we could not find a scholarship for the Introduction to Data Science and Analytics using R course, but there is a $22 discount from the original price ($37). So the current price is just $14.99.

Who will teach this course? Can I trust Diganta Nil Chatterjee?

Diganta Nil Chatterjee has created 1 courses that got 2 reviews which are generally positive. Diganta Nil Chatterjee has taught 52 students and received a 4.3 average review out of 2 reviews. Depending on the information available, we think that Diganta Nil Chatterjee is an instructor that you can trust.

Learn everything about

Diganta Nil Chatterjee

Data Scientist
Hello students,
My name is Diganto and I am a post-grad data scientist! ( Data Scientist at Accenture Strategy, Ex-Mu Sigma, IIT Kharagpur, CAT 2018 – 98.36 percentile, GATE AIR-184).
I am a Kaggle expert Tier data scientist with a rank of 1134 and I am within the top 0.7 percentile of data scientists in Kaggle. I have close to 3 years of experience in Data Science and Analytics and I have developed various commodity price prediction models and have extensively worked with time series algorithms, Linear, Logistic Regression Modelling, Classification, and Regression Trees (CART) as well as with unsupervised learning algorithms such as Clustering Algorithms and purchase propensity models using Python, R, and R Shiny.
I have trained more than 300 students in data science using R and Python.
I look forward to interacting with you all during the course.
Happy learning!
Diganta Nil Chatterjee's full profile and courses »
Go to class »

9.0

Classbaze Grade®

9.8

Freshness

7.8

Popularity

8.9

Material

Detailed Analysis »

Learn to create & test Machine Learning & Data Science Models in R from Data Science experts. Code templates included.
Go to course »
Platform: Udemy
Price: check current price
Video: 5h 0m
Language: English
Next start: On Demand

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