Generative AI Engineer Portfolio

About Me

My passion lies at the intersection of artificial intelligence and game development. I am dedicated to learning how to leverage generative models to create dynamic worlds, non-player characters (NPCs) with unique personalities, and procedurally generated quests and stories. My goal is to work within a team of passionate game developers that want to push the boundaries for a better gaming experience.

I am currently developing skills in game design, machine learning, deep learning, and specific generative AI techniques such as GANs, VAEs, RAG and transformers, with a focus on their application in the gaming industry.

My Skills

Python TensorFlow PyTorch Generative AI Game Development Procedural Generation Unreal Engine 5 Full-Stack Web Development Database Architecture Software Documentation Data Wrangling Restful API React Node Flask UI Design Prototyping NoSQL Application Frameworks Natural Language Processing Quality Assurance NumPy Pandas Generative Adversarial Networks (GANs) Variational Autoencoders (VAEs)

Certifications

MSc in Computer Science
IBM Generative AI Engineering Professional Certificate
IBM RAG for Generative AI Applications
Epic Games Game Design Professional Certificate
CompTIA A+
CompTIA Cloud Essentials+
Certified Cybersecurity Technician (CCT)

My Learning Roadmap

MSc in Computer Science: Completed a Master's degree with distinction, providing a deep understanding of core AI, machine learning, and software engineering principles.
100 Days of Code: The Complete Python Pro Bootcamp: Building Python projects, games and apps using data science and automation.
The Complete Full-Stack Web Development Bootcamp: Build 16+ web development projects using React, Node, Javascript, Web3, PostgreSQL.
Python for Data Science: Building on a strong foundation in Python and its core data science libraries like NumPy, Pandas, and Scikit-learn.
Game Dev Basics: Learning the fundamentals of a game engine like Unreal Engine or Unity.

IBM Generative AI Engineering Professional Certificate: Actively studying and on track to complete this comprehensive program covering generative AI models, tools, and applications.
IBM RAG for Generative AI Applications: Studying the use of Retrieval-Augmented Generation (RAG) to ground LLMs with specific knowledge for more accurate and contextually relevant outputs in applications
GANs & VAEs: Studying the theory and implementation of Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) for image and texture generation.
Transformers & LLMs: Understanding the architecture and fine-tuning of transformers and Large Language Models (LLMs) for generating dialogue and storylines.
Epic Games Game Design Professional Certificate: 8+ hands-on gaming projects leveraging; advanced game design, blueprint scripting, visual and audio development, UX and UI design, collaboration
Ethical AI: Discussing the ethical considerations of using generative AI in creative works.

AI Quality Assurance: Researching and applying best practices for testing, validating, and ensuring the quality and safety of AI-generated content in a game development pipeline.
Implementation: Begin coding a game prototype, integrating the learned generative models to create game assets, narratives, or characters.
Iteration & Refinement: Testing the prototype with users and iterating on the AI models based on feedback.
Documentation: Documenting the process, challenges, and solutions for the project.