Course Highlights
Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step training course. This Data Science & Machine Learning with R Complete Training has been specially designed to help learners gain a good command of Data Science & Machine Learning with R Complete Training, providing them with a solid foundation of knowledge to become a qualified professional.
Through this Data Science & Machine Learning with R Complete Training, you will gain both practical and theoretical understanding of Data Science & Machine Learning with R Complete Training that will increase your employability in this field, help you stand out from the competition and boost your earning potential in no time.
Not only that, but this training includes up-to-date knowledge and techniques that will ensure you have the most in-demand skills to rise to the top of the industry. This qualification is fully accredited, broken down into several manageable modules, ideal for aspiring professionals.
Learning outcome
- Familiar yourself with the recent development and updates of the relevant industry
- Know how to use your theoretical knowledge to adapt in any working environment
- Get help from our expert tutors anytime you need
- Access to course contents that are designed and prepared by industry professionals
- Study at your convenient time and from wherever you want
Course media
Why should I take this course?
- Affordable premium-quality E-learning content, you can learn at your own pace.
- You will receive a completion certificate upon completing the course.
- Internationally recognized Accredited Qualification will boost up your resume.
- You will learn the researched and proven approach adopted by successful people to transform their careers.
- You will be able to incorporate various techniques successfully and understand your customers better.
Requirements
- No formal qualifications required, anyone from any academic background can take this course.
- Access to a computer or digital device with internet connectivity.
Course Curriculum
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Data Science and Machine Learning Introduction
00:03:00 -
What is Data Science
00:10:00
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Machine Learning Overview
00:05:00
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Who is This Course for
00:03:00
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Data Science and Machine Learning Marketplace
00:05:00
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Data Science and Machine Learning Job Opportunities
00:03:00
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Getting Started
00:11:00
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Basics
00:06:00
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Files
00:11:00
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RStudio
00:07:00
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Tidyverse
00:05:00
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Resources
00:04:00
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Unit Introduction
00:30:00
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Basic Type
00:09:00
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Vector Part One
00:20:00
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Vectors Part Two
00:25:00
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Vectors – Missing Values
00:16:00
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Vectors – Coercion
00:14:00
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Vectors – Naming
00:10:00
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Vectors – Misc
00:06:00
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Creating Matrics
00:31:00
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List
00:32:00
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Introduction to Data Frames
00:19:00
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Creating Data Frames
00:20:00
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Data Frames: Helper Functions
00:31:00
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Data Frames Tibbles
00:39:00
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Intermediate Introduction
00:47:00
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Relational Operations
00:11:00
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Conditional Statements
00:11:00
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Loops
00:08:00
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Functions
00:14:00
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Packages
00:11:00
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Factors
00:28:00
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Dates and Times
00:30:00
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Functional Programming
00:37:00
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Data Import or Export
00:22:00
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Database
00:27:00
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Data Manipulation in R Introduction
00:36:00
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Tidy Data
00:11:00
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The Pipe Operator
00:15:00
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The Filter Verb
00:22:00
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The Select Verb
00:46:00
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The Mutate Verb
00:32:00
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The Arrange Verb
00:10:00
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The Summarize Verb
00:23:00
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Data Pivoting
00:43:00
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JSON Parsing
00:11:00
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String Manipulation
00:33:00
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Web Scraping
00:59:00
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Data Visualization in R Section Intro
00:17:00
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Getting Started
00:16:00
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Aesthetics Mappings
00:25:00
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Single Variable Plots
00:37:00
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Two Variable Plots
00:21:00
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Facets, Layering, and Coordinate Systems
00:18:00
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Styling and Saving
00:12:00
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Creating with R Markdown
00:29:00
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Introduction to R Shiny
00:26:00
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A Basic R Shiny App
00:31:00
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Other Examples with R Shiny
00:34:00
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Machine Learning Part 1
00:22:00
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Machine Learning Part 2
00:47:00
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Starting a Data Science Career Section Overview
00:03:00
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Data Science Resume
00:04:00
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Getting Started with Freelancing
00:05:00
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Top Freelance Websites
00:05:00
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Personal Branding
00:05:00
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Importance of Website and Blo
00:04:00
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Networking Do’s and Don’ts
00:04:00
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Duration:22 hours, 7 minutes
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Access:1 Year
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Units:69
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