🚀 Dive into the World of AI Agents with Databricks 🚀 Curious about AI agents and their transformative potential in enterprise applications? Databricks offers a comprehensive free, on-demand course to help you build a solid foundation in this cutting-edge field. 📚 What You'll Learn: Introduction to AI Agents: Understand their role and significance in modern AI applications. Core Components: Explore the key elements that make up AI agents. Real-World Use Cases: Discover how AI agents are applied across various industries. Advanced Topics: Get a glimpse into agentic workflows and multi-agent systems. Hands-On Demos: Learn how to build and deploy AI agents using Databricks' Mosaic AI platform and Agent Bricks. 🎓 Course Details: Skill Level: Introductory Duration: Approximately 1 hour 30 minutes Prerequisites: Recommended to have completed Databricks Fundamentals Databricks This training is perfect for professionals aiming to stay ahead in the AI-driven landscape. Whether you're in data science, engineering, or business strategy, understanding AI agents is becoming essential. 🔗 Start your free training now! #AIAgents #Databricks #GenerativeAI #MachineLearning #AITraining #CareerGrowth #FreeLearning

💡 Build declarative agents faster with TypeSpec Sébastien Levert (Microsoft) demos how to create your first Microsoft 365 Copilot agent using TypeSpec—no manual JSON or OpenAPI needed. He shows how to scaffold, connect APIs, validate, and publish a GitHub issue agent using the Microsoft 365 Agents Toolkit in minutes. 📺 Watch the demo → https://msft.it/6040sPCip #Microsoft365 #Copilot #TypeSpec #AI #DeveloperTools

Training a model is the easy part. Keeping it alive in production? That’s where MLOps begins. Most courses stop at “model trained successfully ✅” — This one starts right after that moment, where production challenges get real. The Free MLOps with Databricks series skips theory and jumps straight into hands-on implementation. Across 10 concise, practical lectures, you’ll explore: 🔹 Core MLOps principles 🔹 Building workflows on Databricks 🔹 Tracking & registering models with MLflow 🔹 Serving and deployment strategies 🔹 CI/CD pipelines and monitoring All built using Databricks + MLflow, the same tools used by production-grade ML teams. If you’ve ever said, “It works on my laptop,” this course shows you how to make it work in production too. 🎥 MLOps with Databricks – Free Edition by Maria Vechtomova View Maria Vechtomova’s profile   & Başak Tuğçe Eskili 💻 100% free. Practical from day one. 🎥 Watch here : https://lnkd.in/d22m87Cq ♻️ Share this with someone learning to scale ML the right way. #MLOps #Databricks #AI #MachineLearning #DataEngineering #MLflow

Your workflow deserves AI-powered momentum. In this episode of the Good Decisions Podcast, host James Combs invites Ravi Shankar G. Lead Principal Software Engineer at Microsoft, to explore how developers are leveraging GitHub Copilot and generative AI tools to transform their workflows. The future of coding isn’t just about faster execution, it’s about smarter augmentation. Workdays now begin with Copilot, not just for writing code but for brainstorming and draughting technical docs. It’s not about replacing engineers. It’s about enhancing their impact. AI boosts productivity, but fundamentals still rule. Automated code means nothing without testing frameworks and human review. The best outcomes come when humans guide the tools, not when tools run unchecked. Innovation works best when paired with responsibility. 🎧 Watch the full episode https://lnkd.in/gQmuhMEm ____________________________________________________ Curious why enterprises struggle to scale AI innovation and how your AI governance compares to industry peers? Get your FREE copy of the AI Governance Benchmark Report today and gain valuable insights for accelerating AI time-to-value. 👉 https://lnkd.in/gDXMJDx8 #softwareengineering #generativeAI #GitHubCopilot #productivitytools #futureofwork #Microsoft #developers #AIinEngineering #GoodDecisionsPodcast

The course "AI Agent Fundamentals" from Databricks provided a solid foundation on LLMs, Prompt Engineering, and an exciting new product from Databricks — Agent Bricks (currently in Beta). 💡 Agent Bricks is a low-code/no-code tool designed to help users easily build and deploy AI Agents within the Databricks ecosystem. It’s fascinating to see how Databricks is bridging the gap between data and AI with such intuitive tools. Excited to explore more in this space! 🚀 #Databricks #AIAgents #LLMs #PromptEngineering #AgentBricks #LearningJourney

V1 Docs Just Dropped! 🚀 Our open-source continual-learning framework for LLM agents is now available. 👉 https://lnkd.in/eFZ6hD4V Fresh off our demo at AI Show & Tell NYC at Microsoft Research Lab, where we showcased our SRE Agent autonomously resolving complex Kubernetes incidents. ATLAS enables developers to integrate real-time continual learning into any AI agent delivering better performance and reduced token costs without updating model weights. Our docs provide: Insights: Understand continual learning and online prompt optimization. Guides: Step-by-step instructions to integrate ATLAS into your workflows. Use Cases: Examples like our SRE Agent’s Kubernetes incident resolution. For MLEs and AI devs these docs provide a starting point for experimenting with adaptive, learning agents. Explore Docs: https://lnkd.in/eFZ6hD4V Try Atlas: https://lnkd.in/eNPkt-MH

🤖 Struggling to Scale Your AI Agents? AI Genius Has the Fix. Agents that can’t connect to real-time data or external tools are holding you back. In Episode 1 of the Season 2 of AI Genius - Elevate Your Agents with Model Context Protocol (MCP), learn how to build intelligent, scalable agents and make it secure, connected and smart using: 🔧 Azure AI Foundry Agent Service 🔗 Model Context Protocol (MCP) 🔐 PostgreSQL Get hands-on with the same tools used in the workshops—and access scripts, slides, and resources to build smarter agents. 👉 Join Episode 1: https://msft.it/6048s06Qj

America On Tech is excited to be participating in this year’s Salesforce Dreamforce conference, where we’ll be speaking in THREE sessions! We’re diving deep into important conversations on tech and education, including: 🤖 AI Education 📊 Tableau Next 🧠 Agentic AI Agents + Analytics 🎯 Grant Reporting & Fundraising …and more. The AI era is here, and we believe students and schools should not be left behind. That’s why we’re focused on building AI literacy and in-demand skills for the next generation of technology leaders. We’re also proud to have partnered with Salesforce and Accenture on one of the first implementations of Tableau Next. Catch our sessions to explore real-world insights, measurable impact, and how we're advancing innovative AI education. Sessions:  https://lnkd.in/g9wWzdig https://lnkd.in/gZmHw8JZ

How Databricks + AI solve real worl industry problems ? Take this scenario, Your company deals with huge Procurement Data (PDF, Invoices, contracts, etc ) You want to build applications which takes PDF’s as input and check if this PO, contract is matching or not. Isn’t it good ? No code , just a drag and drop application That’s what i taught in these two courses 1. Build Databricks End to End project using DLT and Gen AI - https://lnkd.in/g2U2JqfF 2. Build Rag Based Chatbot - https://lnkd.in/gYTvsj4B

Our newest AI Agents for Beginners course is here. Learn how to build prod-ready AI agents using the Microsoft Agent Framework (MAF) — plus how it stacks up against Semantic Kernel and AutoGen. You’ll walk away ready to build with MAF (with code samples!), apply it to your own use cases, and migrate existing frameworks.