Oct 2022 - May 2025
Gia Dinh University
Bachelor of Information Technology, Big Data
GPA: 3.2 / 4.0
I am Minh Trinh, a Data Scientist with a strong foundation in artificial intelligence and machine learning,
experienced in executing numerous scientific and applied projects in both academic and real-world
environments. I have completed diverse projects ranging from facial recognition and image classification to
grade prediction. With in-depth knowledge of Python, TensorFlow, and model deployment, I am eager to
contribute to innovative AI projects, develop large-scale data systems, and support businesses in making
data-driven decisions accurately.
Holds a Bachelor's degree in Big Data and proficient in Python, R, C++, SQL, Pandas, and various data analysis
tools. Skilled in data wrangling, exploratory data analysis, feature engineering, machine learning techniques,
and model deployment.
Bachelor of Information Technology, Big Data
GPA: 3.2 / 4.0
• Guide students of varying skill levels through core Python programming concepts, including data
structures, functions, and object-oriented programming, tailoring instruction to individual learning
styles.
• Design and deliver customized lesson plans, hands-on programming exercises, and data science and
data analytics projects to help students develop problem-solving skills and reinforce fundamental
programming knowledge.
• Provide real-world examples and project-based learning, covering topics such as data analysis, web
scraping, and machine learning fundamentals, to ensure a comprehensive understanding of Python
applications.
• Collected, processed, and analyzed statistical data from public sources (GSO, yearbooks, census
reports).
• Visualized and explored datasets using Python (Pandas, Seaborn, Requests, BeautifulSoup, Selenium)
and Excel to support research insights.
• Built descriptive and regression models experimented with machine learning algorithms such as KMeans
and Decision Trees for deeper analysis.
• Supported dashboard development with Power BI and helped optimize the data standardization workflow.
• Worked closely with a senior statistician, gaining hands-on experience in data pipelines and
policy-driven data analysis.
