Machine Learning Data Science

TRẦN VĂN ANH THƯ

Intern AI Engineer

Ho Chi Minh Github 094******* *******************@*****.*** SUMMARY

I am a highly motivated AI Engineer intern with a strong foundation in artificial intelligence, machine learning algorithms, and data analysis. My technical expertise is complemented by hands-on experience in building and optimizing machine learning models, developing data pipelines, and conducting in-depth data analyses. I am eager to leverage my skills in AI and data science to drive innovation and deliver impactful solutions. My goal is to advance into a senior AI Engineer role within the next 2-3 years, contributing to cutting-edge AI projects and furthering my expertise in the field. EDUCATION

Ho Chi Minh City University of Science 2022-2026

Artificial Intelligence

Bachelor Degree - GPA: 8.75

Mindx Technology School 6/2024

Data Analyst

• Trained in knowledge and skills related to data cleaning and visualization tools such as SQL, PowerBI and Python. Especially knowledge about databases, database storage as well as the working process of a Data Analyst from raw data to complete Insights.

• Be trained in the mindset of converting data into useful insights for business operations. CERTIFICATIONS

Google Data Analytics 4/2024-6/2024

Google Advanced Data Analytics 4/2024-6/2024

MindX Data Analyst 6/2024

WORK EXPERIENCE

Công ty Cổ phần Dịch vụ Di động Trực tuyến (Momo) Ho Chi Minh, Vietnam Machine Learning Engineer Intern 7/2024 – 9/2024

• Understanding the Process of Building a Codebase Using Bazel and Dagger

• Learning the Fundamentals of Large Language Models (LLMs)

• Unit Testing for Online Lending System

• Learning to Build Data Pipelines with Apache Airflow PERSONAL PROJECTS

Football Analyst Using Machine Learning and Computer Vision 4/2024 Description: This project aimed to analyze football matches to detect and track players, referees, and footballs in a video using the YOLO (You Only Look Once) algorithm. The analysis involved processing videos to identify key elements on the field and generating detailed statistics for further insights. Goal: The goal was to provide actionable insights and predictive models to help football teams optimize their strategies, improve player performance, and enhance overall game analysis. Role details:

• Preprocessed and analyzed video datasets: Utilized Python and libraries such as OpenCV and YOLO to preprocess and analyze football match videos.

• Implemented YOLO for object detection: Applied the YOLO algorithm to detect players, referees, and footballs in the input videos, ensuring high accuracy in object identification.

• Tracked player movements and ball trajectories: Developed and integrated tracking algorithms to monitor player movements and ball trajectories throughout the match.

• Visualized key findings: Created visual representations of the analysis, including heat maps, player paths, and ball movement patterns, to facilitate understanding and decision-making.

• Generated detailed statistics: Compiled comprehensive statistics on player speed, distance covered, ball possession, and other relevant metrics.

• Compiled a comprehensive report: Summarized the analysis findings and suggested strategies for improving team performance and game tactics based on the data insights.

• Provided recommendations: Offered insights such as optimizing player positions, identifying strengths and weaknesses, and enhancing training programs based on the analyzed data.

• Conducted additional research: Supported insights and recommendations by analyzing trends in different matches, player performances, and game outcomes.

• Developed predictive models: Built models to predict player fatigue, potential injuries, and game outcomes, evaluated the model's effectiveness, and identified important factors affecting the predictions. Hotel Booking Analysis Project 6/2024

Description: his project aimed to analyze hotel booking data to identify factors influencing cancellation rates and revenue generation. The analysis included examining variables such as pricing, special requests, meal types, and booking trends.

Goal: The goal was to provide actionable insights to help hotels optimize their pricing strategies, reduce cancellation rates, and enhance revenue generation. Role details:

• Preprocessed and analyzed a dataset containing hotel booking records using Python and libraries such as Pandas and Matplotlib.

• Visualized key findings through charts and graphs to facilitate understanding and decision-making.

• Identified correlations between variables and cancellation rates to provide recommendations for improvement.

• Compiled a comprehensive report summarizing the analysis findings and suggesting strategies for mitigating cancellations and maximizing revenue.

• Provided recommendations such as offering competitive room pricing, implementing targeted marketing campaigns, and enhancing service quality.

• Conducted additional research to support insights and recommendations, including analyzing trends in different hotel segments and geographical locations. SKILLS

Programming: Python (Pandas, Numpy, Scikit-learn), SQL, C/C++ Visualization: Power BI, Python (Matplotlib, Seaborn). Machine Learning: Linear/ Logistic Regression, Naive Bayes, Decision Tree, Random Forest. Microsoft Office: Excel, Word, PowerPoint.

Language: Proficient in English.

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