Name: Thanathorn Boonyakijjinda
Nickname: Chopper
Age: 25
Job Position: Data Engineer
Company: Bluebik Vulcan
bachelor's degrees: Thammasat University
GPA: 3.58
May I introduce myself? My name is Thanathorn Boonyakijjinda, but you can call me Chopper. I was born on 11 April 2000, making me 25 years old. I'm from Thailand and currently living in Bangkok. For my educational background, I graduated from Thammasat University with a bachelor's degree in Electrical Power Engineering with a GPA of 3.58. I have a passion for continuous learning and am always eager to enhance my skills. I am easygoing and cheerful, which helps me build strong relationships and collaborate effectively with others.
Professional Skills.
Key Skills
Key Skills Visualization
Key Skills Tools Of Data
My experience worked on.
My responsibilities encompass extracting data from PDF files through web scraping, designing and maintaining efficient ETL pipelines, automating daily data workflows, and delivering impactful reports and visualizations. These efforts empower the marketing team with strategic insights to drive informed decision-making.
My projects worked on.
My Upgrade Skill with Data and programming skill
Teach the entire process of Data Engineering from start to finish, overing topics such as GitHub, Data Lake, Data Warehouse, Data Lakehouse, Data Pipelines, Data Architecture, Data Orchestration, etc. The tools used include AWS, Databricks, Snowflake, Fivetran, Airbyte, dbt, Terraform, and Dagster.
This certificate for digital true academy: demonstrating their skills and knowledge in key areas for the of role junior data analyst. such as Data Analytics Foundation , Data Preparation and Cleaning , Data Engineering and Management , Exploratory Data Analysis , Data Visualization , Modeling , Math and Statistics and Data Science Comprehensive
practice-based assessments and is designed to prepare them for advanced roles in data analytics and entry-level roles in data science. They are competent in exploring large datasets, applying data analysis techinques, and building models to extract insights. They are also competent in machine learning , predictive modeling , and statistics.
This course is Google Data Analytics from Google on Coursera, which includes hands-on, practice-based assessments and is designed to prepare learners for introductory-level roles in data analytics. Participants will become proficient in tools and platforms such as spreadsheets, SQL, Tableau, and R.
This course focuses on R programming for machine learning, with a focus on using decision trees to predict user engagement with mobile apps And CRISP-DM process . which consists of business understanding, data understanding, data preparation, modeling, evaluation, and deployment.
This course covers advanced machine learning topics in Python, with a focus on logistic regression models for predicting loan approval. how to use WoE (Weight of Evidence) and IV (Information Value) to increase model performance, as well as how to apply machine learning techniques such as VIF (Variance Inflation Factor) and AUC (Area Under the Curve) to assess model accuracy and performance.
Feel free to reach out to me via the information below.
