R for Data Analysis: Students and Professionals
Most Honest Crash Course to Become a Data Analyst using R by Solving Real-World Data Problems
R Programming,Data Analysis,Data Visualization
Lectures -109
Resources -1
Duration -11 hours
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Course Description
Interested in becoming a Data Analyst?
Want to gain practical skills and solve real-world business problems? Then this is the perfect course for you!
This course is created by a Senior Data Analyst who has 10 years of experience in the Insurance and Health Care sectors. This course will equip you with foundational knowledge and help you learn key concepts of loading data, data manipulation, data aggregation, and how to use libraries/packages in a simple method.
I will guide you step-by-step into the World of Data Analysis. With every lecture and lab exercise, you will gain and develop understanding of these concepts to tackle real data problems! This course is mainly designed using R to solve the labs and capstone projects.
This course will be super useful and exciting. I tried my best to design the course curriculum in the most natural logical flow:
- Module 0 - Intro to R: set up R environment and understand the basics of R packages/libraries
- Module 1 - Load and Write Data: learn how to load and write data from flat files (i.e., .csv or Excel format)
- Module 2 - Data Types and Formatting: master the data types and learn how to convert data types for the right operations
- Module 3 - Data Manipulation: clean and preprocess data, perform sorting, ordering, and subsetting records
- Module 4 - Join Operations: learn how to perform joins using R packages (i.e., dplyr and sqldf)
- Module 5 - Data Aggregation: learn how to aggregate data using summary statistics and perform feature engineering
- Module 6 - Time Intelligence: learn how to calculate business days and time dimension analysis
- Module 7 - Data Visualization: learn the basics of exploratory data analysis (EDA) and uni-variate/bi-variate visualizations
Each module has independent content. Technically speaking, you can take the course from start to end or jump into any specific topics of your interest. However, I highly recommend students to take the course from Module 1 to 7 in order to complete the capstone project challenge!
This course is packed with real-world data/business problems that I solved during my career as a senior data analyst. You will learn not just concepts but also a lot of practical and hands-on experience from the course. Enroll today and take the first step towards mastering the art of data analysis using R.
Goals
Installing R and R Studio for seamless coding environment setup.
Mastering data type conversion and formatting techniques for consistent data representation.
Utilizing dplyr functions for efficient data manipulation tasks.
Implementing various types of join operations to merge datasets effectively.
Aggregating data and engineering new features for insightful analysis.
Handling date and time data effectively using lubridate package.
Creating customizable visualizations with ggplot2 for effective data communication
Complete a capstone project: OpenAirBnB data using concepts and skills learned from this course to create effective visualizations and communicate your findings
Prerequisites
Operating Systems: 64-bit versions of Microsoft Windows 7, 8.1 and 10 or Mac
Installation of R and R Studio
No prior experience in R but highly desirable to know some basic analytics with Excel
![R for Data Analysis: Students and Professionals R for Data Analysis: Students and Professionals](https://d3mxt5v3yxgcsr.cloudfront.net/courses/18882/course_18882_image.png)
Curriculum
Check out the detailed breakdown of what’s inside the course
Welcome to the Course
10 Lectures
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0_1. Lecture: Part A - Course Intro 06:56 06:56
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0_2. Lecture: Part B - Overview of R and R Studio 03:24 03:24
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0_3. Lecture: Part C - Install R and Launching R Studio 01:58 01:58
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0_4. Lecture: Part D - Intro to R Packages and Installation 04:51 04:51
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DOWNLOAD COURSE PACK: Datasets, Coding Exercises, Course Outline and Cheatsheet
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0_5. Demo: Overview of Course Folder Structure 03:37 03:37
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0_6. Demo: Part A - How to Download R and R Studio 03:02 03:02
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0_7. Demo: Part B - How to Install R 02:10 02:10
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0_8. Demo: Part C - How to Install R Studio 01:50 01:50
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0_9. Demo: Part D - Navigate R and R Studio 04:08 04:08
Load and Write Data in R
10 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Data Types and Formatting
10 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Data Manipulation
12 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Join Data Operations
13 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Data Aggregation and Feature Engineering
12 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Time Intelligence
12 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Data Visualization with ggplot2
20 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Capstone Projects
7 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
CONGRATULATIONS!!!
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Instructor Details
![Taesun Yoo](https://www.tutorialspoint.com/assets/profiles/1166350/profile/200_3543859-1715630906.png)
Taesun Yoo
Taesun is a seasoned data analytics specialist with a wealth of experience in managing large-scale projects. His expertise spans from overseeing data quality and integration testing to crafting informed ad-hoc reports and developing insightful analytics products. Additionally, he serves as a freelance mentor and is the proud owner of the YouTube Channel 'DataScienceOne,' dedicated to showcasing data science projects for aspiring enthusiasts and career-switchers. Taesun's vision is to influence and educate as many individuals as possible, guiding them to launch their first data analytics career.
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