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ai-guuild short

Best Way to learn AI, Most Comprehensive and get Certifed - Trim

🎓 Gain Hands-on Industry Experience
💼 Land Your Dream Job or Build Your Startup
The most beginner-friendly curriculum and Content in AI & Generative AI.
🚀 Zero to Pro in 6 months.
💰 $4,000 + Worth Value
📦 40+ Products
🎤 Live Events & Workshops
⏳ 320+ Hours of Content
--AI Agents
✅Generative AI for Busy People
✅Essential Prerequisites
✅Git and GitHub
✅Python for AI
✅Prompt Engineering for Developers
✅Master  LLM & Langchain
✅Multimodal using Gemini (LLM)
✅Hugging Face
✅RAG vs FineTuning
✅ML Ops & Deployment
✅Vector Databases and AI Agents
✅Project-based Workshops
✅ Masterclasses on New Topics
✅& More..

🌐 Join an Exclusive WhatsApp Community
🤝 Network with MENA's Most Passionate AI Enthusiasts, including Senior Professionals and Decision Makers
🚪 Access Unique Business & Job Opportunities

The Best Way to Start Your AI Journey. Join Now!

Roadmap Here ➡️ https://decoding-data-science.github.io/airoadmap/

Mohammad Arshad

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Artificial Intelligence Guild

A practical learning library that turns scattered AI workshop recordings, demos, code walkthroughs, and resources into clear paths so serious learners can stop guessing and start building with confidence.

This track is for learners who want to understand the AI landscape, LLMs, prompting, model selection, the AI builder mindset, and how to start learning AI in a structured way. It is designed for beginners and curious builders who want clarity, direction, and a simple path into AI without getting overwhelmed. By the end, learners will understand the core ideas they need to move from AI curiosity to practical building and know exactly what to explore next.

AI Learning Path 2026, Updated Track

Introduction to LLM

For Full Large Languae Model Course please Check https://nas.com/aiguild/products/btcn

Understanding Open and Closed Large Language Models

Getting started with Gemini

Building and Deploying AI Applications with Hugging Face

Managing Stakeholders as a Data and AI Professional

AI Builder Foundations

This track is for learners who want to build practical AI applications using LLM APIs, Python, RAG, vector databases, and deployment tools. It is designed for developers, technical learners, and AI builders who want to connect models with custom data, create useful interfaces, and turn prototypes into working applications. By the end, learners will understand how to build document-based assistants, knowledge-powered AI solutions, and deployable applications using real-world workflows.

Why & What is RAG? | Retrieval-Augmented Generation Explained Simply

🎙️AI Applications Using Microsoft Semantic Kernel + OpenAI

Multilingual Money Exchange Project

Why your RAG Retrieval Breaks

AI Apps, APIs , RAG and Deployment

This track is for founders, professionals, and operators who want to use AI to save time, improve output, and automate everyday work. It is designed for people who want practical wins rather than theory, with lessons focused on workflows they can apply immediately. By the end, learners will know how to use AI for writing, analysis, planning, and business productivity in a real-world setting.

Improve Insights using Advance Data Analysis chatGPT

🎙️Transform Your Workday 10X Using AI and Prompt Mastery

Claude in Powerpoint

From AI Idea to Impact: How to Successfully Manage an AI Project

AI for Productivity and Business Workflows

This track is for learners who want to go beyond traditional text-based AI and explore multimodal systems, AI agents, and modern AI tools. It is designed for builders who want to work with image, audio, tools, workflows, memory, and agentic systems that can reason, take actions, and complete practical tasks. By the end, learners will understand how to experiment with emerging AI capabilities and use them to build practical applications, intelligent workflows, and working demos.

Vendor Lock-In in the AI Era: Owning the Seams

The Four layers of Agentic AI

Model Context Protocol Explained

Regulatory Healthcare Analytics on Microsoft Fabric

The SHIP Framework: Why 80% of AI Projects Die in PoC, and How to Be the 20%

react loopengineering

harness new

context engineering 1

michealagent

Multimodal, Agentic AI and Modern AI Tools

Resources https://github.com/Decoding-Data-Science/aiguild2026/tree/main/Databricks/

7th Sep Resources
https://github.com/Decoding-Data-Science/aiguild2026/tree/main/Databricks/Session_1

01 Databricks for AI Projects: From Data to a Working Application

Debug & Deploy an AI Application on Databricks — Session 2

Databricks

AI Learning Tracks 2026

AI Learning Tracks 2026

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