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.

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.
Teaching is not a lost art, but the regard for it is a lost tradition.
Jacques Barzun
Education
- 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)
Communities
- DataRockie facebook page (74,000+ followers as of Jan 2020)
- DataRockie School (15000+ students as of Jan 2020)
- MIT – The Analytics Edge by DataRockie (1500+ members)
Professional Certificates



- AWS Certified Cloud Practitioner (2020 – 2022)
- Facebook Certified Digital Marketing Associate (2020 – 2022)
- Facebook Certified Marketing Science Professional (2020 – 2021)
- 🗽 HBSO – Business Analytics Certificate (March 2020)
- 🗽 eCornell – Business Statistics Certificate (March 2020)
- Udacity’s Machine Learning Engineer Nanodegree Program (2019)
- Udacity’s Programming for Data Science Nanodegree Program (2018)
- Data Scientist with R (career track on datacamp)
- 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.
Certificates
- Introduction to R Programming
- Introduction to Python for Data Science
- Foundations of Data Analysis – Part 1
- Foundations of Data Analysis – Part 2
- Data Science Orientation (Microsoft)
- Statistics and R (HarvardX)
- Data Science: R Basics (HarvardX)
- Data Science: Wrangling (HarvardX)
- Data Science: Visualization (HarvardX)
- Data Science: Probability (HarvardX)
- Data Science: Linear Regression (HarvardX)
- Data Science: Inference and Modeling (HarvardX)
- Data Science: Machine Learning (HarvardX)
- FC1x: Fat Chance: Probability from the Ground Up (HarvardX)
- Analyzing and Visualizing Data with Power BI (Microsoft)
- SQL for Data Science (UC Davis)
- Neural Networks and Deep Learning (deeplearning.ai)
- A Crash Course in Data Science
- How Google does Machine Learning
- IBM: What is Data Science?
- IBM: Databases and SQL for Data Science
- IBM: Python for Data Science
- Basic Statistics
- Inferential Statistics
- Customer Analytics (Wharton)
- 15.071x: The Analytics Edge (MITx)
- Introduction to Data Analytics for Managers
- Data Science Math Skills
- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
- AI For Everyone (read course summary here)
- Learning How to Learn (read course summary here)
- Data Science Specialization JHU: The Data Scientist’s Toolbox
- Data Science Specialization JHU: R Programming
- Data Science Specialization JHU: Getting and Cleaning Data
- The R Programming Environment
- DS102X: Machine Learning for Data Science and Analytics
- Amazon SageMaker: Simplifying Machine Learning Application Development
- Crash Course on Python
- Getting Started with Google Sheets
- Structuring Machine Learning Projects
My goal is to achieve 100 80 certificates by 2020. (changed plan!)
Articles
I’ve written more than 60 articles about data science. I’m always trying to make it accessible for most readers.
Contact
- toy@datarockie.com
- FB messaging: m.me/datarockie
- LinkedIn: https://th.linkedin.com/in/kasidistoy/