Hands-On System
R is most popular and the leading open source language in data science and statistics. Today, R language is the choice for most data science professionals in every industry and academics.
This course is thoroughly described R programming, Statistics and Data Science for beginners using real life examples.
Let s parse that.
This course does not require a prior quantitative or mathematics background. It starts fundamental concepts of R programming, introducing basic concepts such as the mean, median etc and eventually covers all aspects of an analytics (or) data science career from analyzing and preparing raw data to visualizing your findings.
This course is an introduction to Data Science and Statistics using the R programming language. It covers both the theoretical aspects of Statistical concepts and the practical implementation using R.
Real life examples: Every concept is explained with the help of examples, case studies and source code in R wherever necessary.
Course material in the form for articles include in this program
Data Analysis with R: Datatype and Data structures in R, Vectors, Arrays, Matrices, Lists, Data Frames, Reading data from files, Aggregating, Sorting & Merging Data Frames.
Linear Regression: Regression, Simple Linear Regression in Excel, Simple Linear Regression in R, Multiple Linear Regression in R, Categorical variables in regression, Robust regression, Parsing regression diagnostic plots
Instructor Details
Courses : 1
Specification: R programming with Statistics for Data science
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14 reviews for R programming with Statistics for Data science
Add a review
| Price | $12.99 |
|---|---|
| Provider | |
| Duration | 8 hours |
| Year | 2020 |
| Level | All |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
$12.99
Henrick –
Instructor is knowledgeable and delivering way is engaging. This course can be helpful for both beginner as well as intermediate… It covers a vast topic which is really interesting and making this course unique.
Ayan –
The instructor descriptions are clear and way of describing something is also very good.. Looking forward to learn a lot from this course.. Will update more once i complete the course.
KUMARAN KUMAR –
Its not going into details of the topic
Rishita –
I am still on the base R part. Till now it is explained quiet well. The data types,functions, loops are explained well. The course structure is very good. And covers a huge topics.
kanna Dheepankar S –
Very well explained
Hansa Sadeesha Lokuwaduge –
Felt like i m listing to reading book, felt disappointed
Madhuparna Saha –
This is the first time I have attended a class in this format and wondered how effective it would be. It is very effective and therefore I am really looking forward to the course. The instructor is very knowledgeable and provides a wealth of information about the course. The topics covered are really interesting and helpful.
Janhab –
Good
Smith –
It is well explained…
Amy –
Can you include repeated measure ANOVA and mixed model lm?
Amir sharafi –
The accent of the mentor is very hard to understand IT seems that she is in a hurry and going too fast, she could explain the steps in a slower and understandable way
Akash Supare –
good course for beginners
Yogesh Kodgire –
First 2 3 models are explained in very well manner but after that instructor reads slides only. Very few explanation.
Mamadou BARRY –
I’m graduate in IT and I’d like to specialized as R programmer