Passion on AI & Data Science

Here, I showcase my work/progress/learning in data science and related fields. You’ll find a list of projects demonstrating my skills and knowledge in machine learning, deep learning, AI, and different programming languages and software. More details can be found below.
- Skilled-oriented projects
- End-to-end project: IBM-Data-Science-Professional-Certification project. It provides a thorough overview of my abilities and a well-presented end-to-end project. The summary and slide presentation are also shown below.
I’m always eager to learn and expand my skills, so I’ll be updating my GitHub repository with more exciting projects in the future. Stay tuned!

IBM Professional Certificate in Data Science

Capstone project: Space X Falcon 9 Landing Analysis and Prediction

Completed a comprehensive online data science program, earning a professional certificate from IBM and Coursera|Demonstrated transferable skills in data collection, data wrangling, data visualization, SQL, statistical analysis, and machine learning through a hands-on portfolio of projects|Showcased expertise in real-world data science by completing a capstone project, “Space X Falcon 9 Landing Analysis and Prediction”

Analyzed key factors affecting successful launches and landings and predicted the total cost of launches for a new commercial rocket launch provider, Space Y, to compete with SpaceX.
Utilized data collection methods such as the SpaceX API and web scraping, data wrangling, exploratory data analysis (EDA) with visualization and SQL, interactive visual analytics with Folium maps and Plotly dashboards, and predictive analysis with supervised machine learning including logistic regression, support vector machine (SVM), decision tree classifier, and K-Nearest Neighbors (KNN) Algorithm
Predicted the success of first-stage rocket booster landings with an accuracy rate of 83.33% and identified important features for launch success through exploratory data analysis and machine learning models.
Gained hands-on experience in data science and the confidence to apply these skills to real-world scenarios.

“You don’t have to be the best in the world to get ahead. You don’t need to be number on to see the limelight, strike it rich, or find meaning in life. You only need to be good or great—or at least fairly competent—at a few things and then combine those things to foster that uttermost creative quality within yourself.”

— Pat Flynn

Skill sets

I’ve been actively honing my skills in these areas: spreadsheets, SQL databases, coding in R, Julia, and Python, object-oriented programming, optimization, exploratory data analysis (EDA), data extraction through web scraping and APIs, data cleaning, data transformation, data visualization and storytelling, statistics and probability, modeling and simulation, machine learning, deep learning, natural language processing, computer vision, and dashboard creation.

Experiences

Programming and relevant libraries
- PYTHON (e.g., SciPy, NumPy, Pandas, Matplotlib, Scikit-learn, Tensorflow, Keras, Pytorch), R (e.g., tidyverse, caret, ggplot2), SQL, MATLAB, GAMS, and Julia