About Me

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Hello! Thank you for visiting my blog. I hope you enjoy my contents and learn something new. If you want to learn know more about me, please check out below information.

Teaching is not a lost art, but the regard for it is a lost tradition.

Jacques Barzun

I am Toy!

  • Kasidis Satangmongkol
  • Born on 09 09 1988
  • Data Analyst | Market Researcher
  • R | Python | SQL | Excel | SPSS | PowerBI
  • Enthusiastic learner
  • To teach is to learn


  • Bachelor of Economics Kasetsart University GPA 3.41 (2006-2010)
  • MSc Food Economics and Marketing, University of Reading, Distinction (2011-2012)
  • Master of Management – Marketing, College of Management Mahidol University GPA 3.96 (2014 – 2019) ps. I finished only coursework.

Work Experience

  • Ipsos (2012 – 2015)
  • Unilever (2015 – 2016)
  • dtac (2016 – present)


Professional Certificates

  1. Udacity’s Machine Learning Engineer Nanodegree Program (2019)
  2. Udacity’s Programming for Data Science Nanodegree Program (2018)
  3. Data Scientist with R (career track on datacamp)
  4. Microsoft Office Specialist Excel 2016 Expert

MOOC Specializations

I’m an avid self-taught programmer/ learner. My favourite MOOC platforms include coursera, edx, udacity, udemy, datacamp and dataquest. Below is a list of my achievements so far as of May 2019.

Introduction to Scripting in Python

Rice University

Python for Everybody

Uni. of Michigan

From Data to Insights with GCP

Google Cloud

  1. Introduction to R Programming
  2. Introduction to Python for Data Science
  3. Foundations of Data Analysis – Part 1
  4. Foundations of Data Analysis – Part 2
  5. Data Science Orientation
  6. Statistics and R
  7. Data Science: R Basics
  8. Data Science: Wrangling
  9. Data Science: Visualization
  10. Data Science: Probability
  11. Data Science: Linear Regression
  12. Data Science: Inference and Modeling
  13. Data Science: Machine Learning
  14. FC1x: Fat Chance: Probability from the Ground Up
  15. Analyzing and Visualizing Data with Power BI
  16. SQL for Data Science
  17. Neural Networks and Deep Learning
  18. A Crash Course in Data Science
  19. How Google does Machine Learning
  20. IBM: What is Data Science?
  21. IBM: Databases and SQL for Data Science
  22. IBM: Python for Data Science
  23. Basic Statistics
  24. Inferential Statistics
  25. Customer Analytics
  26. 15.071x: The Analytics Edge (MIT)
  27. Introduction to Data Analytics for Managers
  28. Data Science Math Skills
  29. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
  30. AI For Everyone (read course summary here)
  31. Learning How to Learn (read course summary here)
  32. Data Science Specialization JHU: The Data Scientist’s Toolbox
  33. Data Science Specialization JHU: R Programming

My goal is to achieve 100 50 certificates by 2020. (changed plan!)


I’ve written more than 60 articles about data science. I’m always trying to make it accessible for most readers. So far, so good. Isn’t it :D?