Learn Edge AI for Student Developers with Microsoft Course

Day 245 📅: My AI Self-Learning Journey 🏫🧠 Today, I continued Week 2 of the "AI Infrastructure and Operations Fundamentals" from NVIDIA course on Coursera. 💡 Lesson 1: AI in the Cloud Unit Overview AI in the Cloud means delivering AI technologies through cloud platforms. Instead of buying and maintaining costly hardware, users access AI tools on demand via the internet. This makes advanced capabilities more affordable, scalable, and widely available for tasks like data analysis, automation, and predictive modeling. Analogy: Like a community kitchen—chefs (users) can cook with shared tools and ingredients without owning everything themselves. 💡 Lesson 2: Introduction to AI in the Cloud Cloud-based AI lets businesses use powerful computing resources online without investing in their own infrastructure. It’s flexible and scalable—companies can increase or decrease resources as needed, much like renting time at a bakery instead of buying an oven. This setup also supports collaboration, as teams can share data and insights in real time, speeding up innovation and decision-making. 💡 Lesson 3: AI Use Cases in the Cloud Running AI in the cloud means models and applications operate on shared infrastructure rather than local machines. This provides virtually unlimited compute and storage, enabling faster training, easier scaling, and lower costs. Analogy: Like storing books (data) in a vast library instead of a cramped room—easier to organize, access, and use for teaching your “robot” (AI model). Example: A company building a chatbot can: ➖ Store and manage knowledge centrally ➖ Update information quickly ➖ Serve thousands of users at once In short, cloud AI deployment supports rapid innovation without heavy infrastructure burdens. 💡 Lesson 4: AI in the Cloud Considerations The AI maturity model is a roadmap with five stages, from Awareness (just learning about AI) to Transformational AI (AI as a core business driver). Each stage reflects greater capability and integration. Analogy: Like learning to ride a bike—starting with watching, then training wheels, then confident riding, and finally advanced tricks. This helps organizations see where they are and what’s needed to progress. 🔏 Personal Note I hope the training will dive deeper into the technical aspects in the coming weeks. So far, it’s been okay—I’ve learned a lot about what NVIDIA is offering, which is impressive and good to know, but not exactly the kind of content I want to focus on or repeat. Tomorrow, I’ll wrap up the last two lessons of the week, and then I’ll be on vacation for a week with very limited internet access. More updates to follow tomorrow :-) Challenges are opportunities to grow—keep learning! 🚀

🌍 We’re Building Something Bold, Because AI power shouldn’t belong only to big tech. Do know that to do any kind of AI work — from running models to generating content — you need computing power that can process those workloads. Today, most developers and companies access that power through big cloud providers like OpenAI, Google Cloud, or AWS, which rent out expensive GPUs. But soon, everyday people — not just tech giants — will be able to do their own AI work right from home. That’s what the Fea Edge Node makes possible: it gives you the AI power to process workloads locally, privately, and affordably. At Fea Edge AI, we’re building something bold: the Fea Edge Node — private AI in your pocket, designed to bring advanced technology into your home, workplace, and everywhere in between. What is the Fea Edge Node? An Edge Node is a compact, GPU-powered device that runs AI models locally — without depending on the cloud. Think of it as the WiFi router of the AI age: small, plug-and-play, and designed for everyday use. Instead of sending your data to distant servers like Google Cloud or Microsoft, the Fea Edge Node processes everything right where you are. This means: ✅ Local AI compute — so you don’t depend on internet access. ✅ Lower costs — a one-time purchase instead of monthly GPU rental fees. ✅ Data privacy — your personal or business data never leaves your device. ✅ Accessibility — even creators, students, and small teams can run AI workloads locally.  🌍 Click the link below to join our early adopters community https://feaedge.ai

Curious about deploying AI at the edge with #FoundryLocal and #AIToolkit? Microsoft’s Edge AI for Beginners curriculum is a hands-on, open-source guide designed to help developers build, deploy, and optimize AI models for edge scenarios no cloud dependency required. What you’ll learn: - How to run AI models locally using ONNX Runtime and Olive - How to optimize models for performance and size - How to deploy models to devices using Foundry Local and AI Toolkit - How to evaluate model accuracy and latency in real-world conditions The repo includes: - Step-by-step Jupyter notebooks - Sample models and datasets - Deployment templates for Foundry Local - Guidance on using Olive for model optimization Whether you're building smart cameras, industrial sensors, or offline AI apps, this curriculum gives you the tools to go from prototype to production locally. 💡 Start here: https://lnkd.in/dafsyhGg #EdgeAI #FoundryLocal #AItoolkit #ONNX #Olive #AIatTheEdge #MicrosoftAI #OpenSourceAI #AIForDevelopers #MSFTAdvocate

AI has spent a decade in the cloud. Now, it’s coming home... to your PC. Lee Stott’s latest post breaks down why Windows AI PCs and Edge AI are transforming how engineers build, deploy, and scale models. This isn’t just a performance boost. It’s a shift in mindset. 👉 Decisions in milliseconds, not round-trips to a data center. 👉 Privacy built-in, not bolted on. 👉 Resilience that keeps apps running even when the network drops. 👉 Costs that drop without sacrificing capability. With NPUs from Intel and Qualcomm, plus tools like ONNX Runtime, DirectML, and Olive, developers can finally deploy models locally with the same sophistication once reserved for the cloud. The EdgeAI open-source course, Edge AI for Beginners, walks engineers from concept to production. It covers Small Language Models (SLMs), local inference, cross-platform optimization, and real-world deployments... all in 48+ languages. Read the full post here 👉 https://lnkd.in/g-8Gb85a #EdgeAI #WindowsAIPC #AIEngineering #MachineLearning #Developers

The Department of Artificial Intelligence & Machine Learning (AIML) organized an enriching industrial visit to Microsoft, Noida, providing students with valuable exposure to real-world innovations and industry practices. During the visit, students gained insights into cutting-edge AI technologies, cloud computing and digital transformation initiatives at Microsoft. The interaction with industry professionals helped them understand how classroom learning connects with practical applications in the tech ecosystem. Such visits play a vital role in bridging the gap between academia and industry, inspiring students to explore future-ready skills and innovation-driven careers. #GalgotiasCollege #AIML #Microsoft #IndustrialVisit #AI #MachineLearning #Innovation #IndustryConnect #TechEducation #ExperientialLearning

🚀 Build Your Own AI Agent with Azure — Hands-on Learning for Everyone! I’m excited to share an incredible resource for all learners who want to build and understand AI Agents using Microsoft Azure. 💡 Microsoft has created a step-by-step, self-paced learning path where you can explore how AI agents work, design them using Azure tools, and even deploy your own agent — all with guided exercises and practical demos. Here’s what you’ll explore through this journey: ✅ Fundamentals of AI Agents and their real-world use cases ✅ How to use Azure OpenAI Service and Azure AI Studio ✅ Connecting APIs, prompts, and tools to create intelligent behavior ✅ Hands-on labs to build, test, and refine your own AI agent This is not just theory — it’s a complete “learn-by-doing” experience that helps you build confidence while working with cutting-edge Azure AI tools. 💬 I highly recommend all students, developers, and AI enthusiasts give this a try — it’s a perfect way to gain practical, industry-ready skills in agent development. 👉 Start your learning journey here: 🔗 Build AI Agents using Azure (https://lnkd.in/gVJ3dmt9) Let’s keep learning, experimenting, and building the next generation of AI innovations together! 🤖✨ #AzureAI #AIAgents #GenerativeAI #MicrosoftLearn #AIForEveryone #LearningByDoing #AIInnovation

Modules 1, 6, and 7 of the Microsoft Learning Path "Develop AI agents on Azure" has been updated to reflect the new Microsoft Agent Framework #AlwaysBeLearning https://lnkd.in/eJutp3dE

Growth in Progress - built with Lovable Cloud & Lovable AI Traditional campus recruiting is broken. Paper resumes, lost contacts, and manual screening make it slow and inefficient. TapIN.io transforms this process into a seamless digital experience that helps students and companies grow together. Students build a complete digital identity with interactive 3D business cards — directly integrated into Apple and Google Wallet. Recruiters scan QR codes and receive instant AI-generated summaries, powered by Lovable AI, turning data into insight within seconds. Every profile update, every scan, and every summary reflects growth in progress - for students refining their professional identity and for companies improving how they identify talent. Built entirely on Lovable Cloud, TapIN.io showcases how AI and serverless technology can drive real-world self-improvement at scale. Link to the project: https://lnkd.in/dmDQsq7u #LovableChallenge #GrowthInProgress #TapIn #LovableAI #LovableCloud #CareerTech #AI

Tough Tongue AI scenario creator now uses #Perplexity deep search to  collect critical information before creating a scenario. - Create a scenario to practice US B1 Visa Interview - Create a scenario to practice Google Cloud PM: Domain Interview - Or literally anything else you want to prepare for This will search the internet including latest asked questions, new trends etc and then feed as input to agent responsible for high-quality scenario creation. This can dramatically increase the quality of scenario for topics that needs research. Want to learn quantum mechanics? The AI will research it first, then coach you through it using Notepad, whiteboard, and conversation—just like a real tutor would. #Perplexity #VoiceAI #ToughTongueAI

🚀 If you skip learning AI today, AI might skip you tomorrow. The software industry is evolving faster than ever and AI isn’t just a trend anymore, it’s a foundation. Developers who embrace AI tools, frameworks, and thinking will lead the next wave of innovation. Those who ignore it may find themselves left behind. It’s not about replacing humans it’s about enhancing our capabilities. Start small. Learn how AI integrates with your domain whether it’s Android, web, backend, or cloud. Because in the next few years, knowing AI won’t be an advantage it’ll be a requirement. #AI #ArtificialIntelligence #SoftwareDevelopment #FutureOfWork #Learning