Learn Data Science & Machine Learning with R from A-Z

Become a professional Data Scientist with R and learn Machine Learning, Data Analysis + Visualization, Web Apps + more!

4.00 (1353 reviews)
Udemy
platform
English
language
Data Science
category
instructor
Learn Data Science & Machine Learning with R from A-Z
95,111
students
28.5 hours
content
Jan 2021
last update
$59.99
regular price

What you will learn

Become a professional Data Scientist, Data Engineer, Data Analyst or Consultant

How to write complex R programs for practical industry scenarios

Learn data cleaning, processing, wrangling and manipulation

Learn Plotting in R (graphs, charts, plots, histograms etc)

How to create resume and land your first job as a Data Scientist

Step by step practical knowledge of R programming language

Learn Machine Learning and it's various practical applications

Building web apps and online, interactive dashboards with R Shiny

Learn Data and File Management in R

Use R to clean, analyze, and visualize data

Learn the Tidyverse

Learn Operators, Vectors, Lists and their application

Data visualization (ggplot2)

Data extraction and web scraping

Full-stack data science development

Building custom data solutions

Automating dynamic report generation

Data science for business

Why take this course?

Welcome to the Learn Data Science and Machine Learning with R from A-Z Course!

In this practical, hands-on course you’ll learn how to program in R and how to use R for effective data analysis, visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.

Our main objective is to give you the education not just to understand the ins and outs of the R programming language, but also to learn exactly how to become a professional Data Scientist with R and land your first job.

The course covers practical issues in statistical computing which include programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting on R code. Blending practical work with solid theoretical training, we take you from the basics of R Programming to mastery.

We understand that theory is important to build a solid foundation, we understand that theory alone isn’t going to get the job done so that’s why this course is packed with practical hands-on examples that you can follow step by step. Even if you already have some coding experience, or want to learn about the advanced features of the R programming language, this course is for you!

R coding experience is either required or recommended in job postings for data scientists, machine learning engineers, big data engineers, IT specialists, database developers and much more. Adding R coding language skills to your resume will help you in any one of these data specializations requiring mastery of statistical techniques.

Together we’re going to give you the foundational education that you need to know not just on how to write code in R, analyze and visualize data but also how to get paid for your newly developed programming skills.

The course covers 6 main areas:

1: DS + ML COURSE + R INTRO

This intro section gives you a full introduction to the R programming language, data science industry and marketplace, job opportunities and salaries, and the various data science job roles.

  • Intro to Data Science + Machine Learning

  • Data Science Industry and Marketplace

  • Data Science Job Opportunities

  • R Introduction

  • Getting Started with R


2: DATA TYPES/STRUCTURES IN R

This section gives you a full introduction to the data types and structures in R with hands-on step by step training.

  • Vectors

  • Matrices

  • Lists

  • Data Frames

  • Operators

  • Loops

  • Functions

  • Databases + more!

3: DATA MANIPULATION IN R

This section gives you a full introduction to the Data Manipulation in R with hands-on step by step training.

  • Tidy Data

  • Pipe Operator

  • dplyr verbs: Filter, Select, Mutate, Arrange + more!

  • String Manipulation

  • Web Scraping

4: DATA VISUALIZATION IN R

This section gives you a full introduction to the Data Visualization in R with hands-on step by step training.

  • Aesthetics Mappings

  • Single Variable Plots

  • Two-Variable Plots

  • Facets, Layering, and Coordinate System

5: MACHINE LEARNING

This section gives you a full introduction to Machine Learning with hands-on step by step training.

  • Intro to Machine Learning

  • Data Preprocessing

  • Linear Regression

  • Logistic Regression

  • Support Vector Machines

  • K-Means Clustering

  • Ensemble Learning

  • Natural Language Processing

  • Neural Nets


6: STARTING A DATA SCIENCE CAREER

This section gives you a full introduction to starting a career as a Data Scientist with hands-on step by step training.

  • Creating a Resume

  • Personal Branding

  • Freelancing + Freelance websites

  • Importance of Having a Website

  • Networking

By the end of the course you’ll be a professional Data Scientist with R and confidently apply for jobs and feel good knowing that you have the skills and knowledge to back it up.

Screenshots

Learn Data Science & Machine Learning with R from A-Z - Screenshot_01Learn Data Science & Machine Learning with R from A-Z - Screenshot_02Learn Data Science & Machine Learning with R from A-Z - Screenshot_03Learn Data Science & Machine Learning with R from A-Z - Screenshot_04

Reviews

Frackson
August 25, 2023
This course is exactly what i need. As an M&E specialist i need these tools to capture, maintain, Process, Communicate and analyze the large sums of data that we collect everyday.
Daniel
July 13, 2023
A lot of talking without saying very much. A lot of glossing over of things. Some good (albeit brief) examples of how to use R Shiny and the process of using recipe() to create data preprocessing, modelling and visualisation pipelines, but again, very brief, very surface level and hardly what I would call Data Science and Machine Learning with R from A to Z. More like From A to B and there's a lot of letters left before you get to Z.
Ergin
April 15, 2023
so much 'right', 'you know', so much bla bla, not enough to the point. maybe you could have written what you want to tell and then just tell it, not more.
Mansoureh
February 8, 2023
section 13 should have demonstrated some examples of each data type alongside the verbal explanation.
Shella
December 2, 2022
The course pretty straight forward, and too much details and talk, everything you need to know, even how you can get a job online afterwards, and most common used freelancers websites, Totally recommend.
Jon
November 18, 2022
I've always been interested in data science but had no idea where to begin. If you find yourself in the same situation, this course is for you. It's simple to follow, packed with useful ideas and information, and the instructors are really helpful if you get stuck.
Roy
November 17, 2022
Excellent exercises for reinforcing what I'm learning. I had been seeking for a new course to help me advance my data science skills, and this was the right fit.
Delly
November 15, 2022
The course takes you through the basics of data analysis and provides a solid foundation in Phyton. The course is for beginners but also assumes you have some programming knowledge. That said, the course is perfect for anyone who has basic level programming experience and wants to start doing more advanced work with data.
Douglas
October 16, 2022
It is a beginner-intermediate level course that can teach everyone primary concepts about how to use R and RStudio as a statitical and machine learning tool. I do recommend this course!
Alejandro
August 24, 2022
Really good explained, the first 5 Sections are bit basic and slow, but you always can speed up the audio. This is perfect for beginners. The instructor is clear and gives you really useful tips. (Thanks for the "pivot_longer")
Grzegorz
August 10, 2022
Very thoroughly explained R, tidyverse libraries for DataScience. And then some real life examples of Machine Learing. Very good english spoken. Overall very, very good course.
Darryl
July 19, 2022
Simply One Of The Best Courses I've Had The Pleasure To Have Taken.The Instructor Was Both Engaging And Knowledgeable Providing Clear Easy To Understand Explanations On Every Aspect He Is Teaching.
Tyler
July 7, 2022
It was a good course, but there was very little actually dedicated to machine learning. This course title is a bit misleading because it suggests that it is also machine learning with R from A-Z, but in reality there was only an hour dedicated on the topic (split between linear regression and logistic regression), but even that was lacking. No KNN, no random forest, no xgboost, no neural networks, no NLP...
Gaurav
May 9, 2022
Its good as of now and but we need more content on r basic like syntax looping statements and all so that any fresher can learn everything at a single place instead of jumping places to places
Pavan
February 24, 2022
Everything is nice teaching and tutor are very good but only concern is caption some captions are misleading instead of "R" the capion uses 'our" its confusing .

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3535922
udemy ID
9/30/2020
course created date
11/21/2020
course indexed date
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