R for Data Analysis: Students and Professionals

Most Honest Crash Course to Become a Data Analyst using R by Solving Real-World Data Problems


What you'll learn
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

Requirements
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

Description
Interested in becoming a Data Analysts? Want to gain practical skills and solve real world business problems? Then this is pefrect course for you!! This course is created by a
Senior Data Analyst
who has 10 years of experience in
Insurance and Health Care sectors
. This course will equip you with foundation 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 understandings of these concepts to tackle the real data problems! This course is mainly designed by using R to solve the labs and capstone project(s).
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: setup R environment and understand the basics of R packages/libraries
Module 1 - Load and Write Data: 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 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 basics of exploratory data analysis (EDA) and uni-variate/bi-variate visualizations
Each module is independent content. Techinically 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 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 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.
Who this course is for:
This course is designed for individuals with no prior experience in tools (e.g., R or Python).
For new graduates who are considering a data analytics career. This course covers real-world practical data analytics use cases and frequently asked interview questions to prepare yourself
For career switchers who wants to be a data analyst or upgrade yourself to perform complex analyses beyond Excel spreadsheets.

More Info