OpenAI prompting, GPT-4o workflows, use cases, and limitations
Building useful AI learning tools in public.
I create self-contained, offline-capable interactive courses that teach modern AI tools through lessons, quizzes, prompt sandboxes, XP systems, achievements, and practical workflows.
Live AI Course Library
Each course is a standalone app with embedded content, local progress, a prompt simulator, quizzes, achievements, and GitHub Pages deployment.
Code generation, code execution loops, and prompt patterns for software
Google DeepMind multimodal AI and ecosystem integration
xAI real-time context, X integration, and personality-led analysis
Anthropic safety, long context, constitutional AI, and document analysis
Meta open-weight models, local deployment, RAG, and fine-tuning
Efficient open-weight models, MoE concepts, APIs, and local use
GitHub/Microsoft AI for coding, M365, and enterprise workflows
AI search, citations, real-time retrieval, and research workflows
Enterprise NLP, embeddings, reranking, RAG, and Command R+
What this ecosystem shows
It is designed to make the GitHub profile look like a product studio: not isolated experiments, but a connected set of live educational apps with consistent quality and public demos.
abedinm.github.io is the personal front door. ai-tools-master-academy is the course hub. Each ai-course-* repo is a focused product.
Next expansion ideas
Prompt battles, templates, scoring, and before/after examples.
Ollama, Llama, Mistral, embeddings, RAG, and GPU workflows.
A polished app template that proves product UI and deployment skill.