Overview

My name is Richard. I’m a consultant that uses many forms of technology to analyze data such as SQL, Power BI, Tableau, Salesforce, Looker and R. I wanted to share my experience in in data analytics around R language environment. This is a journey of sleepless nights during Covid-19 lockdown and how I was able to learn R programming through Coursera - JHU Data Science Specialization (Johns Hopkins University 2020). I enrolled for the course in March of 2020 and I will summarize a tidy format of my notes during these specialization.

The program consists of 10 courses that covers the following:

  1. The Data Scientist’s Toolbox
  2. R Programming
  3. Getting and Cleaning Data
  4. Exploratory Data Analysis
  5. Reproducible Research
  6. Statistical Inference
  7. Regression Models
  8. Practical Machine Learning
  9. Developing Data Products
  10. Data Science Capstone

As of today, July 29, 2020 I’m currently at course 10 Data Science Capstone - Week 1. The entire data science specialization can be completed in less than 11 months based on your desire to learn. I’ve put in an average of 5 hours per day in each courses. The reason I wanted to learn these materials so fast are as follows:

  • Personal growth
  • Love dissecting data for insights
  • The course syllabus is well thought-out
  • Professors’ expertise in their respective field and abilities to communicate and teach the courses in a simple and concise manner.

Professor Roger D. Peng, PhD, Professor Brian Caffo, PhD and Professor Jeff Leek, PhD - from the bottom of my heart - thank you so much.

Also, thank you for the code folding solution from Sébastien Rochette. The code is use through-out this book (Rochette 2017).

References

Johns Hopkins University. 2020. “Data Science Specialization.” Baltimore, MD: Coursera. https://www.coursera.org/specializations/jhu-data-science.

Rochette, Sébastien. 2017. “Code Folding in Bookdown.” https://stackoverflow.com/questions/45360998/code-folding-in-bookdown/45501553.