Data Science and Machine Learning with R from A-Z Course
Learn machine learning and data analysis from scratch with R
Updated on Jun, 2025
Language - English
Development ,Data Science,Machine Learning
Lectures -81
Duration -28.5 hours
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Course Description
The course covers practical issues in statistical computing that 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 also 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.
By the end of the course, you’ll be a professional data scientist with R and confidently apply for jobs and will feel good knowing that you have the skills and knowledge to back it up.
Goals
- Learn data cleaning, processing, wrangling, and manipulation.
- Learn plotting in R (graphs, charts, plots, histograms, and more).
- How to create a resume and land your first job as a data scientist
- Learn machine learning and its various practical applications.
- Learn data and file management in R
- Use R to clean, analyze, and visualize data.
Prerequisites
- No prior knowledge of R is required.
Curriculum
Check out the detailed breakdown of what’s inside the course
Data Science and Machine Leaning Course Introduction
7 Lectures
-
Data Science and Machine Learning Introduction Section Overview
02:30
02:30
-
What is Data Science?
09:47
09:47
-
Machine Learning Overview
05:26
05:26
-
Data Science + Machine Learning Marketplace
04:38
04:38
-
Who is this Course For?
02:57
02:57
-
Data Science and Machine Learning Job Opportunities
02:37
02:37
-
Data Science Job Roles
04:04
04:04
Getting Started with R
6 Lectures
Data Types and Structures in R
14 Lectures
Intermediate R
12 Lectures
Data Manipulation in R
12 Lectures
Data Visualization in R
7 Lectures
Creating Reports with R Markdown
1 Lectures
Building Webapps with R Shiny
3 Lectures
Introduction to Machine Learning
2 Lectures
Data Preprocessing
2 Lectures
Linear Regression: A Simple Model
2 Lectures
Exploratory Data Analysis
2 Lectures
Linear Regression - a Real Model
2 Lectures
Logistic Regression
2 Lectures
Starting a Career in Data Science
7 Lectures
Instructor Details
Packt Publishing
Packt are an established, trusted, and innovative global technical learning publisher, founded in Birmingham, UK with over eighteen years experience delivering rich premium content from ground-breaking authors and lecturers on a wide range of emerging and established technologies for professional development.
Packt’s purpose is to help technology professionals advance their knowledge and support the growth of new technologies by publishing vital user focused knowledge-based content faster than any other tech publisher, with a growing library of over 9,000 titles, in book, e-book, audio and video learning formats, our multimedia content is valued as a vital learning tool and offers exceptional support for the development of technology knowledge.
We publish on topics that are at the very cutting edge of technology, helping IT professionals learn about the newest tools and frameworks in a way that suits them.
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