Available for opportunities

Hi, I'm Saidul Islam
I build intelligent systems

Final-year CSE student specialising in AI Engineering and Full-Stack Development. I build production-ready AI systems, NLP pipelines, and LLM-powered applications. Targeting MSc in AI abroad and AI Engineer roles in Europe.

View Projects → Get in Touch

Projects Built

3.6

CGPA / 4.0

Certifications

97%

Best Model Accuracy

saidul@portfolio ~ zsh

❯ whoami

Saidul Islam — AI Engineer & Full-Stack Developer

❯ cat skills.json

{

"ai_ml": ["PyTorch", "TensorFlow", "Scikit-learn"],

"llm": ["RAG", "Groq API", "OpenAI API"],

"backend": ["ASP.NET Core", "Django", "C#"],

"languages": ["Python", "C#", "SQL", "C++"]

}

❯ echo $goal

MSc in AI abroad + EU AI Engineer roles

❯ status --current

🟢 Open to opportunities

❯

About Me

Passionate about AI that works

I'm a final-year Computer Science & Engineering student at IUBAT, Bangladesh, with a CGPA of 3.6/4.0. My focus is on building AI systems that solve real problems — from medical classifiers that detect breast cancer with 97% accuracy to RAG-powered LLM chatbots.

I have hands-on experience with the full AI pipeline: data collection and EDA, model training and evaluation, deployment, and integration into production applications. I'm equally comfortable writing Python ML code and building full-stack .NET applications around it.

My goal is to pursue an MSc in Artificial Intelligence in Europe and join a forward-thinking team as an AI Engineer where I can build systems that matter.

🧠 AI / ML 🔗 LLM Integration 🌐 Full-Stack .NET 🐍 Python 🎓 MSc Aspirant 🇪🇺 EU Opportunities

🤖

AI Engineering

Building NLP pipelines, medical AI classifiers, and RAG-based LLM systems from scratch.

⚡

Full-Stack Dev

Production-ready apps with ASP.NET Core, Django, clean architecture and proper auth.

📊

Data Science

End-to-end data pipelines — EDA, feature engineering, model evaluation and deployment.

🎯

Problem Solver

From sentiment analysis to survival prediction — I love turning messy data into insight.

Technical Skills

What I work with

Tools and technologies I use to build intelligent, production-ready systems.

🧠

AI / Machine Learning

PyTorch TensorFlow Scikit-learn Pandas NumPy Matplotlib SVM Gradient Boosting TF-IDF

🔗

LLM / AI APIs

RAG Pipeline Groq API OpenAI API LLM Integration Prompt Engineering Semantic Search

🌐

Web / Backend

ASP.NET Core MVC C# Entity Framework Django REST APIs OAuth 2.0

💻

Languages

Python C# C C++ SQL HTML / CSS / JS

🗄️

Databases

MySQL SQLite MS SQL Server Entity Framework ORM

🛠️

Tools & Deployment

Git / GitHub Docker VS Code Streamlit Cloudflare Pages Linux

Projects

Things I've built

From medical AI classifiers to RAG-powered platforms — real systems solving real problems.

⭐ Featured Project

ReLuNet — AI-Powered Tech Blogging Platform

A full-stack tech blogging platform built with Clean Architecture (.NET 10). Features a RAG pipeline — articles are embedded, keyword-matched against user queries, and passed as context to a Groq LLM to generate personalised learning paths. Includes Google OAuth, rich-text editor, likes, bookmarks, and comments.

.NET 10 MVC ASP.NET Core Entity Framework Groq API RAG Google OAuth SQLite

⌥ GitHub

// RAG Pipeline

User Query

↓ keyword matching

ArticleEmbeddings (SQLite)

↓ top 5 articles

Prompt Builder

↓ context + query

Groq LLM API (llama)

↓ generated response

Personalised Answer + Links

🔬 Medical AI

Breast Cancer Detector

SVM classifier on the Wisconsin Breast Cancer dataset achieving 97% accuracy. Predicts benign or malignant tumours from clinical features. Deployed live on Streamlit Cloud.

Python Scikit-learn SVM Streamlit Joblib

⌥ GitHub ↗ Live

🤰 Medical AI

Pregnancy Risk Level Predictor

Classification model that predicts maternal risk levels (low / mid / high) from clinical features. Deployed as a publicly accessible health-risk assessment tool on Streamlit Cloud.

Python Scikit-learn Streamlit

⌥ GitHub ↗ Live

💬 NLP

Social Media Sentiment Analysis

Analysed sentiment of ~500 social media posts using TF-IDF vectorisation and SVM. Identified emotional patterns — accept, reject, and anger — with visualised insights.

Python TF-IDF SVM Pandas Matplotlib

⌥ GitHub

🚢 Prediction

Titanic Survival Prediction

Gradient Boosting classifier predicting Titanic passenger survival with 82.71% accuracy. Feature engineering on passenger class, gender, and cabin location.

Python Gradient Boosting Scikit-learn Pandas

⌥ GitHub

⚽ SQL Analysis

EPL Match Analysis

Complex SQL queries to analyse English Premier League results and team performance. Win rates, goal differentials, and head-to-head comparisons across seasons.

MySQL MS SQL Server

⌥ GitHub

🍋 Django

Little Lemon Restaurant

Full-featured restaurant demo site with Django — menu management, table booking, and static pages. Capstone project for the Meta Django Web Framework certification.

Python Django HTML/CSS/JS SQLite

⌥ GitHub

Experience