2021 Data Science & Machine Learning with R from A-Z Course

Free Certification Course Title: 2021 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!

Requirements:

Basic computer skills

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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 a 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

Who this course is for:

Students who want to learn about Data Science and Machine Learning

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.