Programming Languages: Python, SQL, C#, Java, etc. Framew

Nguyen Minh Vu

DATA MINING, MACHINE LEARNING INTERN

091******* ************@*****.*** https://www.facebook.com/vupro.minh 10 District, Ho Chi Minh City OBJECTIVE

I am seeking an internship position in Data Mining and ML, where I can apply my knowledge and continue learning in a professional environment. With knowledge of Machine Learning, Deep Learning, Computer Vision, NLP and Data Science, I believe my enthusiasm, willingness to grow, and ability to adapt can contribute to your company. I look forward to the opportunity to collaborate and develop with your company. WORK EXPERIENCE

British Council Viet Nam 08/2024 - 05/2025

IT HELPER

The British Council is the United Kingdom's international organization for cultural relations and educational opportunities. British Council plays a vital role in Teaching English, Educational partnerships, Cultural exchange. During my time working in this environment, I have significantly improved key skills such as:

• Problem-solving related to both hardware and software.

• Teamwork and collaboration.

• Communication and professional workplace behavior. PROJECTS

Data Science Project About Indicators Of Heart Disease 04/2025 - 06/2025 Overview: Apply Data cleaning, Data visualization, Data analysis methods, Data mining techniques, etc Analyzed a dataset describing heart disease indicators, patient physical metrics, and related medical or lifestyle factors. Applied various data science techniques to explore and uncover patterns influencing heart disease risk.

• Key Tasks & Contributions:

• Performed exploratory data analysis to evaluate correlations between heart conditions and other attributes.

• Implemented statistical assessments to estimate the likelihood of factors contributing to heart disease.

• Provided insights and recommendations based on the most impactful variables affecting cardiovascular risk.

• Manually implemented key data mining algorithms including:

• Apriori for frequent itemset mining.

• FP-Growth for pattern discovery.

• Similarity & Dissimilarity Measures for comparing patient profiles.

• Skills & Tools: Python, Pandas, Scikit-learn, Matplotlib, Data Mining, etc.

• GitHub: https://github.com/Biuuu2309/Data-Science-Project.git Berth-Crane-Truck Optimization via Quantum Seagull Algorithm and Chaotic Quantum SSA 04/2025 - 06/2025 Overview: Apply CQASOA, CQSSA algorithms to allocate ships - berths - cranes in the most optimal way Developed the TEU-BQCT model integrated with chaotic quantum mapping to design the CQASOA (Chaos Quantum Adaptive Seagull Optimization Algorithm). Also proposed the enhanced E-B&QC model using the improved CQSSA algorithm, based on quantum computing theory and chaotic mapping.

The project aims to provide an optimal scheduling solution for port operations, focusing on minimizing emissions, operational costs, and processing time.

• Key Tasks & Contributions:

• Developed a multi-objective optimization solution targeting time, cost, and carbon emissions.

• Incorporated complex constraints involving vessels, berths, quay cranes, and trucks.

• Designed and implemented custom metaheuristic algorithms by integrating multiple sub-algorithms, resulting in: CQASOA with the TEU-BQCT model and CQSSA with the E-B&QC model.

• Leveraged chaotic mapping and quantum computing theory to enhance optimization performance.

• Manually implemented optimization algorithms:

• TEU-BQCT Model: SOA, CSOA, QSOA, ASOA, CQASOA.

• E-B&QC Model: SSA, CSSA, QSSA, CQSSA.

• Skills & Tools: Python, Pandas, etc.

• GitHub: https://github.com/Biuuu2309/KLTN_DU.git Basic Text To SQL Conversion 02/2025 - 04/2025

Overview: Performed data collection and data cleaning, followed by training a T5 model using PyTorch for natural language processing tasks. Built a deep learning model to translate natural language queries into SQL statements using encoder-decoder architecture and NLP techniques.

• Key Tasks & Contributions:

• Trained using Google Colab with PyTorch.

• Applied data preprocessing and mapping between user input queries and SQL targets.

• Leveraged vector representations, word embeddings, and T5 (Text-to-Text Transfer Transformer).

• Aimed to enable intelligent query generation from plain English input.

• Perform program installation:

• Preprocessed and formatted input data for compatibility with deep learning model architecture.

• Tuned key hyperparameters (learning rate, batch size, number of epochs, etc.) to improve training efficiency and model performance.

• Skills & Tools: Python, Pandas, Transformers T5, Pytorch, etc.

• GitHub: https://github.com/Biuuu2309/T2SQLConversion.git SKILLS

• HARD SKILLS Programming Languages: Python, SQL, C#, Java, etc. Frameworks & Libraries: NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, Pytorch, etc. Database System: MSSQL Server, Google BigQuery, etc. Tools & Platforms: Jupyter Notebook, Google Colab, GitHub, Tableau, Anaconda, etc.

• SOFT SKILLS Problem-solving, Communication skills, Teamwork & collaboration, Self-learning / Continuous learning, etc. EDUCATION

Hong Bang International University 2022 - Present

Information Technology

GPA: 3.20

REFERENCE

Mr. Le Van Hanh, MSc

Lecturer – Faculty of Information Technology, University of Information Technology, VNU-HCM Email: ***********@*****.***

CERTIFICATION

Google Data Analytics Professional Certificate - Issued by: Coursera 30 AUG 2024 Google IT Automation with Python Professional Certificate - Issued by: Coursera 06 DEC 2024 LANGUAGES

• Vietnamese - Native

• English - Intermediate

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