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

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

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What you'll 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

Description

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.


Your Instructor


Juan E. Galvan
Juan E. Galvan

Hi I'm Juan. I've been an Entrepreneur since grade school. My background is in the tech space started from Digital Marketing, E-commerce, Web Development to Programming. I believe in continuous education with the best of a University Degree without all the downsides of burdensome costs and inefficient methods. I look forward to helping you expand your skillsets.


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Course Curriculum


  Training Overview
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  Section 1: Introduction to Data Science +ML with R from A-Z
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  Section 2: Getting Started with R
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  Section 3: Data Types and Structures in R
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  Section 4: Intermediate R
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  Section 5: Data Manipulation in R
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  Section 6: Data Visualization in R
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  Section 7: Creating Reports with R Markdown
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  Section 8: Building Webapps with R Shiny
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  Section 9: Introduction to Machine Learning
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  Section 10: Data Preprocessing
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  Section 11: Linear Regression: A Simple Model
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  Section 12: Exploratory Data Analysis
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  Section 13: Linear Regression: A Real Model
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  Section 14: Logistic Regression
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  Section 15: Starting a Career in Data Science
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  Audio Version of the Training
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Frequently Asked Questions


When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

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