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
Data cleaning, processing, wrangling and manipulation
Data extraction and web scraping
Data visualization (ggDescription2)
Step by step practical knowledge of R programming language
How to land your first job as a Data Scientist
The fundamentals and setup of R Language
Learn Descriptionting in R (graphs, charts, Descriptions, histograms etc)
Learn Data and File Management in R
Perform operations in R including sorting, data wrangling using dplyr, and making Descriptions
Learn Operators, Vectors, Lists and their application
Learn the Tidyverse
Use R to clean, analyze, and visualize data
Building custom data solutions
Machine learning applications
Full-stack data science development
Automating dynamic report generation
Data science for business
Requirements
Basic computer skills
Description
Early Bird Release for the full upcoming 2021 Learn Data Science and Machine Learning with R from A-Z course!
Please note! This is currently in an Early Bird Beta access, meaning we are still going to be continually adding content to the course (even though we are already at over 22 hours of content!) Since we're still adding content and taking student feedback as we complete the course through the start of 2021, students who enroll now will get access to a wide variety of benefits!
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 Descriptions
Two-Variable Descriptions
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.
Who this course is for:
Students who want to learn about Data Science and Machine Learning

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