Name: Data Science and Machine Learning with R
Price: 85 USD
Rating: 5 (57 reviews)

Unlock the power of data with our Data Science and Machine Learning with R course! This comprehensive program is perfect for those looking to dive into advanced data analysis and predictive modeling. Learn to leverage R for data manipulation, visualization, and machine learning. Key topics include data cleaning, exploratory data analysis, regression models, and classification techniques. Hands-on projects and real-world case studies will deepen your understanding and provide practical experience. By the end of the course, you’ll be equipped with the skills to analyze complex datasets and build sophisticated models, empowering you to make data-driven decisions and advance in the field of data science. Join us and become proficient in R for cutting-edge data science and machine learning!

Who is this course for?

By taking this Data Science and Machine Learning with R Course, you’re able to open yourself to new opportunities within the data science and machine learning career path. Such careers may include:

Data Scientist (£35,000 to £65,000)
Machine Learning Engineer (£45,000 to £80,000)
Data Analyst (£30,000 to £55,000)

Data Science and Machine Learning Course Intro
	Data Science and Machine Learning Introduction	00:03:00
	What is Data Science	00:10:00
	Machine Learning Overview	00:05:00
	Who is This Course for	00:03:00
	Data Science and Machine Learning Marketplace	00:05:00
	Data Science and Machine Learning Job Opportunities	00:03:00
Data Types and Structures in R
	Unit Introduction	00:30:00
	Basic Type	00:09:00
	Vector Part One	00:20:00
	Vectors Part Two	00:25:00
	Vectors – Missing Values	00:16:00
	Vectors – Coercion	00:14:00
	Vectors – Naming	00:10:00
	Vectors – Misc	00:06:00
	Creating Matrics	00:31:00
	List	00:32:00
	Introduction to Data Frames	00:19:00
	Creating Data Frames	00:20:00
	Data Frames: Helper Functions	00:31:00
	Data Frames Tibbles	00:39:00
Intermediate R
	Intermediate Introduction	00:47:00
	Relational Operations	00:11:00
	Conditional Statements	00:11:00
	Loops	00:08:00
	Functions	00:14:00
	Packages	00:11:00
	Factors	00:28:00
	Dates and Times	00:30:00
	Functional Programming	00:37:00
	Data Import or Export	00:22:00
	Database	00:27:00
Data Manipulation in R
	Data Manipulation in R Introduction	00:36:00
	Tidy Data	00:11:00
	The Pipe Operator	00:15:00
	The Filter Verb	00:22:00
	The Select Verb	00:46:00
	The Mutate Verb	00:32:00
	The Arrange Verb	00:10:00
	The Summarize Verb	00:23:00
	Data Pivoting	00:43:00
	JSON Parsing	00:11:00
	String Manipulation	00:33:00
	Web Scraping	00:59:00
Data Visualization in R
	Data Visualization in R Section Intro	00:17:00
	Getting Started	00:11:00
	Aesthetics Mappings	00:25:00
	Single Variable Plots	00:37:00
	Two Variable Plots	00:21:00
	Facets, Layering, and Coordinate Systems	00:18:00
	Styling and Saving	00:12:00
Creating Reports with R Markdown
	Creating with R Markdown	00:29:00
Building Webapps with R Shiny
	Introduction to R Shiny	00:26:00
	A Basic R Shiny App	00:31:00
	Other Examples with R Shiny	00:34:00
Introduction to Machine Learning
	Machine Learning Part 1	00:22:00
	Machine Learning Part 2	00:47:00
Starting A Career in Data Science
	Starting a Data Science Career Section Overview	00:03:00
	Data Science Resume	00:04:00
	Getting Started with Freelancing	00:05:00
	Top Freelance Websites	00:05:00
	Personal Branding	00:05:00
	Importance of Website and Blo	00:04:00
	Networking Do’s and Don’ts	00:04:00

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Data Science and Machine Learning with R

Course Curriculum