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+# Personal AI Fluency Plan
+
+## Overview
+This document outlines a structured plan to develop AI fluency over the next 12 months. The plan is based on the **AI Fluency Framework** from Anthropic and is tailored to a beginner‑to‑intermediate learner.
+
+## Goals
+1. **Understand core concepts** of AI, machine learning, and large language models.
+2. **Build practical skills** in data preprocessing, model training, and deployment.
+3. **Develop critical thinking** about AI ethics, safety, and societal impact.
+4. **Create a portfolio** of projects demonstrating end‑to‑end AI solutions.
+
+## Timeline (12 months)
+| Month | Focus | Deliverable |
+|-------|-------|-------------|
+| 1‑2 | Foundations | Complete *AI Fluency Foundations* course; write a summary. |
+| 3‑4 | Data & ML Basics | Build a simple regression model on a public dataset. |
+| 5‑6 | NLP & LLMs | Fine‑tune a small transformer on a custom text corpus. |
+| 7‑8 | Prompt Engineering | Design a prompt library for common tasks; document best practices. |
+| 9‑10 | Deployment | Deploy a chatbot using LangChain and Streamlit. |
+| 11 | Ethics & Safety | Write a short essay on AI safety principles. |
+| 12 | Portfolio & Reflection | Publish a GitHub repo with all projects; reflect on learning. |
+
+## Resources
+- **Courses**: AI Fluency Foundations, Coursera ML, Fast.ai NLP.
+- **Tools**: Python, PyTorch, Hugging Face, LangChain, Streamlit.
+- **Reading**: *The Alignment Problem*, *AI Ethics* by Bostrom.
+
+## Milestones
+- **M1**: Course completion + summary.
+- **M2**: Regression model + GitHub repo.
+- **M3**: Fine‑tuned transformer + demo.
+- **M4**: Prompt library + documentation.
+- **M5**: Deployed chatbot.
+- **M6**: Ethics essay + final portfolio.
+
+## Reflection
+After each milestone, review progress, identify gaps, and adjust the next steps accordingly.
+
+---
+
+*Prepared by: [Your Name]*