About Me

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

Picture: @What The Duck event 16 December 2022

I am Toy!

  • Kasidis Satangmongkol
  • 1980s Kid 😝
  • Data Analyst | Content Developer
  • R, Python, SQL, Statistics and Classical ML
  • Enthusiastic learner. To teach is to learn.

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

Jacques Barzun


  • 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) – only coursework.

Work Experience

  • Samsung (2021 – present)
  • dtac (2016 – 2020)
  • Unilever (2015 – 2016)
  • Ipsos (2012 – 2015)


Professional Certificates

  1. AWS Certified Cloud Practitioner (2020 – 2022)
  2. Facebook Certified Digital Marketing Associate (2020 – 2022)
  3. Facebook Certified Marketing Science Professional (2020 – 2021)
  4. 🗽 HBSO – Business Analytics Certificate (March 2020)
  5. 🗽 eCornell – Business Statistics Certificate (March 2020)
  6. Udacity’s Machine Learning Engineer Nanodegree Program (2019)
  7. Udacity’s Programming for Data Science Nanodegree Program (2018)
  8. Data Scientist with R (career track on datacamp)
  9. 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.


  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 (Microsoft)
  6. Statistics and R (HarvardX)
  7. Data Science: R Basics (HarvardX)
  8. Data Science: Wrangling (HarvardX)
  9. Data Science: Visualization (HarvardX)
  10. Data Science: Probability (HarvardX)
  11. Data Science: Linear Regression (HarvardX)
  12. Data Science: Inference and Modeling (HarvardX)
  13. Data Science: Machine Learning (HarvardX)
  14. FC1x: Fat Chance: Probability from the Ground Up (HarvardX)
  15. Analyzing and Visualizing Data with Power BI (Microsoft)
  16. SQL for Data Science (UC Davis)
  17. Neural Networks and Deep Learning (deeplearning.ai)
  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 (Wharton)
  26. 15.071x: The Analytics Edge (MITx)
  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
  34. Data Science Specialization JHU: Getting and Cleaning Data
  35. The R Programming Environment
  36. DS102X: Machine Learning for Data Science and Analytics
  37. Amazon SageMaker: Simplifying Machine Learning Application Development
  38. Crash Course on Python
  39. Getting Started with Google Sheets
  40. Structuring Machine Learning Projects

My goal is to achieve 100 80 certificates by 2020. (changed plan!)


I’ve written more than 100 articles about data science. I’m always trying to make it accessible for most readers.