Ibrahim Yasin
Applied AI & Machine Learning Systems Student
I build practical AI, data science, NLP, and machine learning systems using Python, SQL, PyTorch, spaCy, Hugging Face, FastAPI, and Docker.
About Me
I am an Applied AI & Machine Learning Systems student with a background in network engineering. I have worked on multiple specialized projects involving switch configuration, network setup, and infrastructure optimization in real-world environments.
I contributed to large-scale network projects for organizations such as the National Bank of Jordan and King Hussein Medical City, where I supported network deployment, configuration, and reliability.
Currently, I am expanding my expertise into AI, data science, and NLP systems, building end-to-end solutions that combine data engineering, machine learning, and production deployment.
Skills & Technologies
Python & Data Science
SQL & Databases
Machine Learning
NLP
Deployment & Production
Tools
AI.SPIRE Projects
Applied AI program — end-to-end project portfolio
Module 1
Hospital Admission Records Analysis
View on GitHubModule 2
Retail Sales Data Pipeline
View on GitHubHousing Price Prediction — PyTorch
View on GitHubModule 3
SQL Analytics
View on GitHubETL Pipeline
View on GitHubModule 4
Descriptive Analytics
View on GitHubKPI Dashboard
View on GitHubModule 5
Regression & Evaluation
View on GitHubML Pipeline
View on GitHubTree Models
View on GitHubHyperparameter Tuning
View on GitHubModel Comparison
View on GitHubProduction ML CLI
View on GitHubModule 6
Roadmap
What's next in the AI.SPIRE program
Module 7 — Advanced NLP Tasks
Sequence classification, sentiment analysis, and multi-label NLP tasks using transformer architectures.
Module 8 — RAG Systems & Vector Retrieval
Retrieval-augmented generation systems with vector databases and semantic search pipelines.
Module 9 — Knowledge Graphs & Semantic Web
Knowledge graph construction, entity linking, and semantic reasoning for AI applications.
Module 10 — Deployment I
Containerized ML service deployment using Docker, FastAPI, and cloud-native infrastructure.
Module 11 — Deployment II
Advanced deployment patterns, monitoring, CI/CD pipelines, and production ML reliability.
Module 12 — Capstone Project
End-to-end applied AI system integrating data engineering, ML modeling, NLP, and production deployment.