Available for Internship · Apr – Aug 2026

Syahmi Amin bin Shamsul

// Data Science & AI Student

Computer Science student at Taylor's University specialising in Data Science and AI. I build ML models, analytics dashboards, and turn raw data into actionable insights.

syahmi.py
1class SyahmiAmin:
2  def __init__(self):
3    self.name = "Syahmi Amin"
4    self.role = "Data Science & AI"
5    self.university = "Taylor's University"
6    self.skills = ["Python", "ML", "DL"]
7    self.open_to_work = True
8 
9  def get_accuracy(self):
10    # best model score so far
11    return 93.58%

Who I Am

7+
ML Projects
93%
Best Accuracy
53K+
Records Trained
2026
Graduating

I'm a final-year Computer Science student at Taylor's University, specialising in Data Science with an extension in Artificial Intelligence. I'm passionate about building models that solve real problems — from detecting bone fractures in X-rays to predicting loan defaults.

Beyond the models, I care about the full pipeline: clean data, meaningful insights, and dashboards that tell a story. My capstone project is a Visual Analytics Dashboard for Patient Pathway and Hospital Flow Management.

I'm actively seeking a full-time internship from April to August 2026 where I can contribute, learn fast, and make data-driven impact.

LocationPuchong, Selangor, Malaysia
UniversityTaylor's University
LanguagesEnglish (Advanced), Malay (Native)

Tech Stack

Programming
Python R SQL Java pandas NumPy scikit-learn
Machine Learning
Supervised Learning Unsupervised Learning Classification Regression Clustering Random Forest kNN Decision Tree
Deep Learning
TensorFlow PyTorch LSTM CNN Neural Networks
Tools & Platforms
Jupyter Google Colab VS Code PyCharm Tableau GitHub Gradio Streamlit

What I've Built

🧠
Deep Learning

Mental Health Sentiment Analysis

Built two text classification models on 53K+ mental health statements using Python, pandas, and scikit-learn. Compared Decision Tree vs Neural Network performance.

93.58% Neural Network · 90.78% Decision Tree
🎬
Deep Learning

Sentiment Analysis on IMDB Reviews

Performed sentiment analysis using a Bidirectional LSTM model on IMDB movie reviews in Google Colab. Binary classification of positive vs negative reviews.

86.8% Accuracy — BiLSTM
💊
Machine Learning

Analyse Lethal Drug Combinations

Built data mining models on drug-death records. Applied Random Forest for classification, K-Means for seasonal clustering, and Isolation Forest to detect geographic outliers.

81% Accuracy — Random Forest
🏦
Machine Learning

Predicting Loan Defaults

Developed ML models to analyse loan default risk on a financial dataset. Compared k-Nearest Neighbours against Decision Tree classifiers on key financial features.

88.54% kNN · 88.07% Decision Tree
🦴
Computer Vision

Bone Fracture Detection

Developed a Convolutional Neural Network (CNN) to automatically detect bone fractures in X-ray images. Trained on labelled radiography data with data augmentation techniques.

73.84% Accuracy — CNN
🌿
IoT

Smart Monitoring for Houseplants

Built an IoT prototype using ESP32 and Raspberry Pi with sensors to automate plant watering and monitor moisture, temperature, humidity, and soil pH in real time.

❤️
Machine Learning

Heart Disease Prediction

Conducted EDA and preprocessing on the UCI Heart Disease dataset using Python and Scikit-learn. Developed a Logistic Regression model to predict heart disease risk.

66.67% Accuracy — Logistic Regression
🏥
Capstone

Visual Analytics — Hospital Flow

Ongoing capstone project building a visual analytics dashboard for patient pathway and hospital flow management. Full EDA, predictive modelling, and interactive Tableau/Streamlit dashboards.

⏳ In Progress

Work & Activities

Student Assistant — FitFuel Station Research Project
Jan 2026 – Apr 2026
Taylor's University, Malaysia · INNOVATE Grant
  • Coordinating the 'FitFuel Station — An AI-Driven Vending Device for Foodstuff Customisation' research project
  • Assisting in software logic translation, data handling, and validating nutrition algorithms
  • Ensuring accurate integration between body composition inputs, decision engines, and AI-controlled dispensing output
UG Research Idea Pitch Competition Participant
Dec 2025
Research & Innovation Festival (RNIF 2025) · Taylor's University, Malaysia
  • Participated in the undergraduate research idea pitch competition at the university-wide innovation festival

Academic Background

Bachelor of Computer Science (Honours)
Taylor's University, Malaysia · Feb 2024 – Aug 2026 (Expected)
Specialisation: Data Science Extension: Artificial Intelligence
Capstone Project: Visual Analytics Dashboard for Patient Pathway and Hospital Flow Management (Ongoing)

Let's Connect

I'm actively looking for a data science internship from April to August 2026. If you're building something interesting with data or AI, I'd love to hear from you.

Availability Status
Open to Internship Offers
April 2026 – August 2026 · Full-time

Based in Puchong, Selangor, Malaysia. Open to on-site roles in the Klang Valley or remote opportunities. Seeking roles in data science, ML engineering, analytics, or AI research.