Update README.md

Author: arshad831

README.md

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-# aiguild
-aiguild
+# AI Guild — Learning Assets (2026)
+
+A curated, builder-first repository of AI Guild resources: roadmaps, workshop decks, reference PDFs, and hands-on notebooks (Colab/Jupyter). The intent is simple: **learn → build → publish proof**.
+
+## What you’ll find here
+- **Roadmaps** to move from AI-curious to AI builder (2026 focus)
+- **Workshop decks** (AI Explorer sessions, CPE-ready material)
+- **RAG foundations + demos** (production-minded patterns, not just toy examples)
+- **Hands-on notebooks** (Python refreshers, sentiment analysis, LangChain + Chroma demos)
+
+---
+
+## Quick Start (Recommended Learning Order)
+1. **Roadmap (high-level direction)**
+   - `DDS_2026_Roadmap_4jan.pdf`
+   - `AI_Curious_to_AI_Builder_2026_Roadmap.pdf`
+
+2. **AI Explorer decks (conceptual clarity + business translation)**
+   - `AI_Explorer_Professional_CPE_Deck.pdf`
+
+3. **RAG Foundations (core mental model + pipeline)**
+   - `RAG foundation 6th Jan 2026.pdf`
+
+4. **RAG Demo (hands-on implementation)**
+   - `RAG_Demo_LangChain_Chroma_Colab.ipynb`
+
+5. **Skill boosters (Python + applied notebook)**
+   - `DDS_Python_mini_course2026.ipynb`
+   - `Copy_of_DDS_Academy_LLM_Sentiment_Analysis.ipynb`
+
+---
+
+## Repository Contents
+
+| Type | File | Purpose |
+|------|------|---------|
+| PDF | `AI_Curious_to_AI_Builder_2026_Roadmap.pdf` | A practical pathway for turning “AI interest” into shipped demos and portfolio proof. |
+| PDF | `DDS_2026_Roadmap_4jan.pdf` | DDS-wide roadmap and priorities for 2026. |
+| PDF | `AI_Explorer_Professional_CPE_Deck.pdf` | Professional deck for AI Explorer sessions (CPE-friendly). |
+| PDF | `RAG foundation 6th Jan 2026.pdf` | RAG fundamentals: ingest → chunk → embed → retrieve → generate, with quality + trust considerations. |
+| Notebook | `RAG_Demo_LangChain_Chroma_Colab.ipynb` | End-to-end RAG demo using LangChain + Chroma (builder workflow). |
+| Notebook | `DDS_Python_mini_course2026.ipynb` | Python essentials refresher for AI builders (fast-track). |
+| Notebook | `Copy_of_DDS_Academy_LLM_Sentiment_Analysis.ipynb` | Applied LLM sentiment analysis notebook (practical baseline). |
+
+---
+
+## How to Use
+
+### Option A — Read PDFs in GitHub
+- Click any `*.pdf` file to open it in GitHub’s PDF viewer.
+- For best viewing, download the PDF locally if you need full-screen reading or annotation.
+
+### Option B — Run Notebooks in Google Colab (recommended)
+1. Open the notebook file in GitHub.
+2. Click **“Open in Colab”** (if available) or copy the notebook URL into Colab:
+   - In Colab: `File → Open notebook → GitHub` and paste your repo URL.
+
+> Tip: If you want a consistent “Open in Colab” button inside each notebook, add a small header cell with a GitHub/Colab badge.
+
+### Option C — Run Notebooks Locally (Jupyter)
+**Prerequisites**
+- Python 3.10+ recommended
+- Jupyter installed (`pip install jupyter`)
+
+**Run**
+```bash
+jupyter notebook