Beginners R Programming Data Science And Machine Learning!

What you'll learn
Code in R by building variables, loops, statements, and more.
Input data sets from text files, CSV files, or database systems.
Output data by creating tables, text files, or CSV files.
Build functions efficiently and apply functions to data.
Manipulate and store data properly using dplyr.
Use R packages to supersize your toolkit.
Solve practical business problems using R.
Fill out dataframes.
Visualize data and build plots using ggplot2.
Use machine learning techniques for R, including K-means clustering.
Make predictions with decision trees.
And more!
Requirements
No experience necessary!
Mac/PC compatible. Recorded on a PC.
Please download R from the CRAN repository.
Download RStudio, the top development environment for R.
Description
Have you ever wanted to code and use data to your advantage? Well, you've come to the right place!After purchasing this course, you'll be taken step-by-step through every process needed to do just that. Funded by a #1 Kickstarter Project by Mammoth Interactive.Our very talented instructor John Kemp, explains everything from a basic, beginner level. That means, you don't have to have any prior coding experience to succeed here.R Programming for Absolute Beginners: from Data Analytics to Visualization to Machine Learning!5 hours on-demand video!Learn offline via the Udemy app14 Articles12 Downloadable ResourcesFull lifetime accessManipulate Data and Learn about Matrices with R.Data scientist and online mentor John Kemp will take you through the process of learning to code from scratch in a massively popular programming language: R in RStudio.You will learn everything it takes to be a data analyst, including:inputting and outputting datamanipulating and storingsolving business problemsvisualizing datamaking predictions using machine learningand so much more with the abundant R packages of the exploding R community. Learn Online at ANY Pace!The beauty of taking an online course like this is the ability to replay any of the lectures at any time. There is no time limit or final tests. You get to learn at your own pace with a practical model method of learning.One of the best features is that you can watch the courses at any speed you want. This means you can speed up the or slow down the video if you want to.This course is project-based so you will not be learning a bunch of useless coding practices. At the end of this course you will have real world apps to use in your portfolio. We feel that project based training content is the best way to get from A to B. Taking this course means that you learn practical, employable skills immediately.You can use the projects you build in this course to add to your LinkedIn profile. Give your portfolio fuel to take your career to the next level.Learning how to code is a great way to jump in a new career or enhance your current career. Coding is the new math and learning how to code will propel you forward for any situation. Learn it today and get a head start for tomorrow. People who can master technology will rule the future.An Amazing Instructor Deep in the Field.John Kemp has been programming in R as a data scientist since 2011. He has spent 100+ hours tutoring students online to help them learn R from scratch or to enhance their R abilities.John has been set up as an online mentor to partner with students looking to enter into the data science profession. In addition, John uses R as a hobby and will also help various businesses with data manipulation, network optimization and other data science tasks.Enroll Now while on Sale!
Overview
Section 1: Course Introduction
Lecture 1 Course Introduction
Lecture 2 Source Files
Section 2: Introduction to R Programming
Lecture 3 Introduction to R Variables
Lecture 4 Source Files
Section 3: Data Input and Output with R
Lecture 5 Data Input
Lecture 6 Data Output
Lecture 7 Source Files For Each Lecture
Section 4: Setting up Control Flow in R
Lecture 8 Loops
Lecture 9 How to Use If Statements in R
Lecture 10 Source Files For Each Lecture
Section 5: Core Concepts of R Programming
Lecture 11 Vectors
Lecture 12 Functions
Lecture 13 Packages
Lecture 14 (Project) Solve a Business Problem with R
Lecture 15 Source Files For Each Lecture
Section 6: Matrix Construction in R
Lecture 16 Matrices
Lecture 17 Source Files
Section 7: R Data Frame
Lecture 18 Data Frames
Lecture 19 Source Files
Section 8: Apply a Function over a List or Vector
Lecture 20 Lists and Lapply
Lecture 21 Source Files
Section 9: Data Manipulation in R Dplyr
Lecture 22 Data Manipulation and Dplyr
Lecture 23 Source Files
Section 10: Data Visualization in R using ggplot2
Lecture 24 Basic Plots | ggplot Visualizations
Lecture 25 Additional Plotting
Lecture 26 Advanced Plotting
Lecture 27 Source Files For Each Lecture
Section 11: Introduction to Machine Learning
Lecture 28 Machine Learning Introduction
Lecture 29 K-means Clustering
Lecture 30 Decision Trees
Lecture 31 Source Files For Each Lecture
Section 12: R Conclusion
Lecture 32 Conclusion
Lecture 33 Source Files
Lecture 34 Please rate this course!
Lecture 35 Bonus Lecture: Mammoth Interactive Deals
Anyone who wants to learn to code in a growing programming language.


Homepage

https://www.udemy.com/course/beginners-r-programming-data-science-and-machine-learning/