AWS AI/ML Practictioner ChallengeAWS X Udacity
2026Graduated from the Udacity program with a focus on AI and Machine Learning, completing all projects and milestones.
Passionate about building intelligent systems that solve real-world problems. Specialize in transforming ideas into beautifully crafted products.
GitHub Stats

AI/ML Engineering Scholar - Future AWS AI Programmer
July 2026 - Present

AI/ML Engineering Scholar - AWS AI Practitioner Challenge
March 2026 - August 2026

Machine Learning Engineering Intern
June 2026 - Present

Founding Growth Fellow
June 2026 - Present

AI Engineering Fellow
April 2026 - Present
Completed the AWS AI & ML Scholars project to design and ship a first AI productivity application using generative AI tools.
Completed the AWS AI & ML Scholars project on analyzing data with AI in Amazon PartyRock, turning prompts and datasets into an interactive app.
Completed the AWS AI & ML Scholars project on analyzing data with AI in Amazon PartyRock, turning prompts and datasets into an interactive app.
Actively building in the open — sharing projects, shipping features, and contributing to the data science and machine learning community.

British Airways · Code · PR #4 · Jan 2024
Open-sourced an end-to-end machine learning pipeline that predicts customer booking behaviour with 85% accuracy, plus a premium lounge demand forecasting framework.

Citi · Feature · PR #11 · Mar 2024
Contributed a multi-model quantitative pricing framework for coffee futures options, combining Cost of Carry, Black-Scholes, and Monte Carlo simulation.

Lloyds Banking Group · Bug Fix · PR #7 · Jun 2024
Improved ensemble model optimisation and added SHAP-based interpretability to surface the key drivers of customer churn.

Validated foundational knowledge of Claude, generative AI, prompt engineering, and responsible AI practices for building effective AI-powered applications.
Credential ID: 4tuvfrerrr9n

Hands-on experience using Claude Code for AI-assisted software development, including coding, debugging, refactoring, and working with AI-powered development workflows.
Credential ID: ek3onc5zrcuy

Developed foundational skills in prompt engineering, including designing effective prompts and applying generative AI techniques to improve model outputs.
Learning in public is one way to grow. The other is proving it — shipping work, earning certifications, and sharing proof so the next person in the room can follow the same path.
Graduated from the Udacity program with a focus on AI and Machine Learning, completing all projects and milestones.
Awarded the AWS AI & ML Scholarship for demonstrating potential in artificial intelligence and machine learning.
Completed the AWS Foundations course on prompt engineering, designing effective prompts and applying generative AI techniques.
Validated foundational knowledge of Claude, generative AI, prompt engineering, and responsible AI practices.
Completed Google's MLOps for Generative AI course covering model deployment, monitoring, and lifecycle management.
Designed and shipped a first AI productivity application using generative AI tools as part of the AWS AI & ML Scholars program.
Research papers, technical investigations, and experimental studies across machine learning, natural language processing, and AI systems.
Experimental Study · Charles Akinnurun · July 2026
Developed and evaluated a Transformer-based NLP model for movie review sentiment classification. The study applies tokenization, attention mechanisms, and model fine-tuning to classify reviews as positive or negative, benchmarking a full encoder-only Transformer pipeline against statistical baselines.
AWS AI & ML Scholars · AWS Future AI Programmer · Technical Report
Technical Research · Charles Akinnurun · June 2024
Engineered a credit scoring model to predict loan default risk from financial and repayment history. The research compares classical classifiers and ensemble methods, using feature engineering and threshold optimization to support risk assessment protocols.
CodeAlpha · Technical Report
Experimental Study · Charles Akinnurun · October 2024
Architected a Convolutional Neural Network for recognizing handwritten digits and characters from images. The work covers image preprocessing, data augmentation, and CNN architecture design, with an extension path to full word recognition using sequence models such as CRNNs.
CodeAlpha · Technical Report
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