Get certified as an Azure AI Engineer (AI-102) this summer?
For developers, the accreditation as an Azure AI Engineer—certified through the rigorous AI-102 exam—has become a golden ticket to career acceleration. It isn’t just about coding chatbots or fine-tuning machine learning models; it’s about gaining the confidence (for you and for your business) that you can wield Azure’s toolkits to configure AI solutions that augment human capability. Before we dive in, if you’re planning to become certified as an Azure AI Engineer, you may find this Starter Learning Plan (AI 102) valuable—recently curated by a group of Microsoft experts, purposed for your success. We recommend adding it to your existing learning portfolio. It’s a light introduction that should take less than four hours, but it offers a solid glimpse into what to expect on your journey and the breadth of solutions you might craft in the future. From revolutionizing customer service with intelligent agents to optimizing supply chains through predictive analytics, Azure AI engineers sit at the confluence of technological ingenuity and business transformation. For those with an appetite for problem-solving and a vision for AI-driven futures, this certification isn’t just another badge—it’s an assertion of expertise in a field where demand is outpacing supply. Securing that expertise, however, requires more than just a weekend of cramming. Today’s aspiring AI engineers navigate an ecosystem of learning that is as modern as the field itself. Gone are the days when one could rely solely on a stack of manuals; now, candidates immerse themselves in a medley of Microsoft Learn modules, hands-on labs, AI-powered coding assistants, and community-led study groups. Many take a pragmatic approach—building real-world projects using Azure Cognitive Services and Machine Learning Studio to cement their understanding. Others lean on practice exams and structured courses from platforms like Pluralsight and Udemy, ensuring they aren’t just memorizing but internalizing the core principles. The AI-102 exam doesn’t reward rote knowledge—it demands fluency in designing, deploying, and securing AI solutions, making thorough preparation an indispensable part of the journey. In addition to the above learning plan, we want to provide a few other tips. Understand the Exam Objectives: Begin by thoroughly reviewing the AI-102 study guide. This document outlines the key topics and skills assessed, including planning and managing Azure AI solutions, implementing computer vision and natural language processing solutions, and deploying generative AI solutions. Familiarizing yourself with these areas will provide a structured framework for your study plan. Continuous memorization is part of your study. But if you get a bit bored from your flashcards and look for more ‘storyline’ style learning content, we recommend adding MSFT employee created learning plan to your mix. They are scenario-based and focus more on providing you with a structured understanding of how to do XYZ on Azure. Here are 3 examples: Modernize for AI Readiness Build AI apps with Azure Re-platform AI applications Hands-On Practice: Practical experience is invaluable. Engage with Azure AI services directly by building projects that incorporate computer vision, natural language processing, and other AI functionalities. This hands-on approach not only reinforces theoretical knowledge but also enhances problem-solving skills in real-world scenarios. Utilize Practice Assessments: Assess your readiness by taking advantage of free practice assessments provided by Microsoft. These assessments mirror the style and difficulty of actual exam questions, offering detailed feedback and links to additional resources for areas that may require further study. Stay Updated on Exam Changes: Certification exams are periodically updated to reflect the latest technologies and practices. Regularly consult the official exam page to stay informed about any changes in exam content or structure. Participate in Community Discussions: Engaging with peers through forums and study groups can provide diverse perspectives and insights. The Microsoft Q&A platform is a valuable resource for asking questions, sharing knowledge, and learning from the experiences of others preparing for the same certification. By systematically incorporating these strategies into your preparation, you'll be well-positioned to excel in the AI-102 exam and advance your career as an Azure AI Engineer. If you have additional tips or thoughts, let us know in the comments area. Good luck!Use AI for Free with GitHub Models and TypeScript! 💸💸💸
Learn how to use AI for free with GitHub Models! Test models like GPT-4o without paying for APIs or setting up infrastructure. This step-by-step guide shows how to integrate GitHub Models with TypeScript in the Microblog AI Remix project. Start exploring AI for free today!Unlocking the Power of Azure Container Apps in 1 Minute Video
Azure Container Apps provides a seamless way to build, deploy, and scale cloud-native applications without the complexity of managing infrastructure. Whether you’re developing microservices, APIs, or AI-powered applications, this fully managed service enables you to focus on writing code while Azure handles scalability, networking, and deployments. In this blog post, we explore five essential aspects of Azure Container Apps—each highlighted in a one-minute video. From intelligent applications and secure networking to effortless deployments and rollbacks, these insights will help you maximize the capabilities of serverless containers on Azure. Azure Container Apps - in 1 Minute Azure Container Apps is a fully managed platform designed for cloud-native applications, providing effortless deployment and scaling. It eliminates infrastructure complexity, letting developers focus on writing code while Azure automatically handles scaling based on demand. Whether running APIs, event-driven applications, or microservices, Azure Container Apps ensures high performance and flexibility with minimal operational overhead. Watch the video on YouTube Intelligent Apps with Azure Container Apps – in 1 Minute Azure Container Apps, Azure OpenAI, and Azure AI Search make it possible to build intelligent applications with Retrieval-Augmented Generation (RAG). Your app can call Azure OpenAI in real-time to generate and interpret data, while Azure AI Search retrieves relevant information, enhancing responses with up-to-date context. For advanced scenarios, AI models can execute live code via Azure Container Apps, and GPU-powered instances support fine-tuning and inferencing at scale. This seamless integration enables AI-driven applications to deliver dynamic, context-aware functionality with ease. Watch the video on YouTube Networking for Azure Container Apps: VNETs, Security Simplified – in 1 Minute Azure Container Apps provides built-in networking features, including support for Virtual Networks (VNETs) to control service-to-service communication. Secure internal traffic while exposing public endpoints with custom domain names and free certificates. Fine-tuned ingress and egress controls ensure that only the right traffic gets through, maintaining a balance between security and accessibility. Service discovery is automatic, making inter-app communication seamless within your Azure Container Apps environment. Watch the video on YouTube Azure Continuous Deployment and Observability with Azure Container Apps - in 1 Minute Azure Container Apps simplifies continuous deployment with built-in integrations for GitHub Actions and Azure DevOps pipelines. Every code change triggers a revision, ensuring smooth rollouts with zero downtime. Observability is fully integrated via Azure Monitor, Log Streaming, and the Container Console, allowing you to track performance, debug live issues, and maintain real-time visibility into your app’s health—all without interrupting operations. Watch the video on YouTube Effortless Rollbacks and Deployments with Azure Container Apps – in 1 Minute With Azure Container Apps, every deployment creates a new revision, allowing multiple versions to run simultaneously. This enables safe, real-time testing of updates without disrupting production. Rolling back is instant—just select a previous revision and restore your app effortlessly. This powerful revision control system ensures that deployments remain flexible, reliable, and low-risk. Watch the video on YouTube Watch the Full Playlist For a complete overview of Azure Container Apps capabilities, watch the full JavaScript on Azure Container Apps YouTube Playlist Create Your Own AI-Powered Video Content Inspired by these short-form technical videos? You can create your own AI-generated videos using Azure AI to automate scriptwriting and voiceovers. Whether you’re a content creator, or business looking to showcase technical concepts, Azure AI makes it easy to generate professional-looking explainer content. Learn how to create engaging short videos with Azure AI by following our open-source AI Video Playbook. Conclusion Azure Container Apps is designed to simplify modern application development by providing a fully managed, serverless container environment. Whether you need to scale microservices, integrate AI capabilities, enhance security with VNETs, or streamline CI/CD workflows, Azure Container Apps offers a comprehensive solution. By leveraging its built-in features such as automatic scaling, revision-based rollbacks, and deep observability, developers can deploy and manage applications with confidence. These one-minute videos provide a quick technical overview of how Azure Container Apps empowers you to build scalable, resilient applications with ease. FREE Content Check out our other FREE content to learn more about Azure services and Generative AI: Generative AI for Beginners - A JavaScript Adventure! Learn more about Azure AI Agent Service LlamaIndex on Azure JavaScript on Azure Container Apps JavaScript at MicrosoftConstruyendo una Aplicación Web con Inteligencia Artificial usando Python
En la segunda sesión del GitHub Copilot Bootcamp LATAM, organizado por Microsoft Reactor, el ingeniero Manuel Ortiz, Embajador de Microsoft Learn y líder comunitario en GitHub, guió a desarrolladores en la creación de una aplicación web con capacidades de inteligencia artificial. Este taller práctico combinó fundamentos de desarrollo backend en Python con técnicas avanzadas de integración de modelos de lenguaje de Azure OpenAI. Introducción a Azure Open AI Azure Open AI es una colaboración entre Microsoft y OpenAI que permite a los desarrolladores integrar modelos avanzados de inteligencia artificial en sus aplicaciones utilizando la infraestructura de Azure. Esto ofrece acceso a modelos poderosos como GPT-4, que pueden ser utilizados para una variedad de tareas, desde procesamiento de lenguaje natural hasta generación de texto. Configuración de Azure Open AI Para comenzar a usar Azure Open AI, debes seguir algunos pasos básicos: Crear una Cuenta en Azure: Si aún no tienes una cuenta, puedes crear una en el portal de Azure. Los estudiantes pueden solicitar créditos gratuitos para usar los servicios de Azure. Crear un Servicio Azure Open AI: Accede al portal de Azure y busca "Azure Open AI". Haz clic en "Crear" y selecciona tu suscripción y grupo de recursos. Elige la región y configura el nombre del servicio, que debe ser alfanumérico y sin caracteres especiales. Selecciona el plan de precios adecuado y finaliza la creación del servicio. Obtener las Credenciales: Después de crear el servicio, necesitarás las credenciales (clave de API y endpoint) para autenticar tus solicitudes. Estas credenciales se pueden encontrar en la sección de "Claves y Endpoints" del servicio creado. Integración con Python y Flask Python es uno de los lenguajes de programación más populares para el desarrollo de aplicaciones de inteligencia artificial debido a su simplicidad y vasta biblioteca de herramientas. Durante la configuración, puedes usar varias bibliotecas y herramientas que facilitan el desarrollo de IA con Python, incluyendo: TensorFlow: Una biblioteca de código abierto para aprendizaje automático. Keras: Una API de alto nivel para redes neuronales, que funciona sobre TensorFlow. Scikit-learn: Una biblioteca para aprendizaje automático en Python. Flask: Un microframework para desarrollo de aplicaciones web. Una vez configurado el servicio Azure Open AI, puedes integrarlo en tus aplicaciones Python usando Flask. Aquí tienes un ejemplo de cómo hacerlo: Instalación de las Bibliotecas Necesarias: Crea un entorno virtual e instala las bibliotecas necesarias, como flask y openai. Configuración del Proyecto: Crea un archivo .env para almacenar tus credenciales de forma segura. Configura tu aplicación Flask para cargar estas credenciales y conectarse al servicio Azure Open AI. Creación del Modelo de IA: Utiliza la biblioteca openai para enviar prompts al modelo y recibir respuestas. Integra estas respuestas en tu aplicación web para proporcionar funcionalidades de IA a los usuarios. Ejemplo de Código Aquí tienes un ejemplo simplificado de cómo configurar y usar Azure Open AI en una aplicación Flask: from flask import Flask, request, render_template import openai import os app = Flask(__name__) # Cargar las credenciales del archivo .env openai.api_key = os.getenv("AZURE_OPENAI_API_KEY") openai.api_base = os.getenv("AZURE_OPENAI_ENDPOINT") @app.route("/", methods=["GET", "POST"]) def index(): response_text = "" if request.method == "POST": prompt = request.form["prompt"] response = openai.Completion.create( engine="text-davinci-003", prompt=prompt, max_tokens=100 ) response_text = response.choices.text.strip() return render_template("index.html", response_text=response_text) if __name__ == "__main__": app.run(debug=True) Beneficios de Azure Open AI Acceso a Modelos Avanzados: Utiliza los modelos más recientes y poderosos de OpenAI. Escalabilidad: La infraestructura de Azure permite escalar tus aplicaciones según sea necesario. Seguridad y Conformidad: Benefíciate de las robustas medidas de seguridad y conformidad de Azure. Sigue aprendiendo Si deseas aprender más sobre estas técnicas, mira las grabaciones del GitHub Copilot Bootcamp, comienza a utilizar el GitHub Copilot gratuito y descubre cómo transformar tu manera de programar utilizando inteligencia artificial.
Learn how to develop innovative AI solutions with updated Azure skilling paths
The rapid evolution of generative AI is reshaping how organizations operate, innovate, and deliver value. Professionals who develop expertise in generative AI development, prompt engineering, and AI lifecycle management are increasingly valuable to organizations looking to harness these powerful capabilities while ensuring responsible and effective implementation. In this blog, we’re excited to share our newly refreshed series of Plans on Microsoft Learn that aim to supply your team with the tools and knowledge to leverage the latest AI technologies, including: Find the best model for your generative AI solution with Azure AI Foundry Create agentic AI solutions by using Azure AI Foundry Build secure and responsible AI solutions and manage generative AI lifecycles From sophisticated AI agents that can autonomously perform complex tasks to advanced chat models that enable natural human-AI collaboration, these technologies are becoming essential business tools rather than optional enhancements. Let’s take a look at the latest developments and unlock their full potential with our curated training resources from Microsoft Learn. Simplify the process of choosing an AI model with Azure AI Foundry Choosing the optimal generative AI model is essential for any solution, requiring careful evaluation of task complexity, data requirements, and computational constraints. Azure AI Foundry streamlines this decision-making process by offering diverse pre-trained models, fine-tuning capabilities, and comprehensive MLOps tools that enable businesses to test, optimize, and scale their AI applications while maintaining enterprise-grade security and compliance. Our Plan on Microsoft Learn titled Find the best model for your generative AI solution with Azure AI Foundry will guide you through the process of discovering and deploying the best models for creating generative AI solutions with Azure AI Foundry, including: Learn about the differences and strengths of various language models Find out how to integrate and use AI models in your applications to enhance functionality and user experience. Rapidly create intelligent, market-ready multimodal applications with Azure models, and explore industry-specific models. In addition, you’ll have the chance to take part in a Microsoft Azure Virtual Training Day, with interactive sessions and expert guidance to help you skill up on Azure AI features and capabilities. By engaging with this Plan on Microsoft Learn, you’ll also have the chance to prove your skills and earn a Microsoft Certification. Leap into the future of agentic AI solutions with Azure After choosing the right model for your generative AI purposes, our next Plan on Microsoft Learn goes a step further by introducing agentic AI solutions. A significant evolution in generative AI, agentic AI solutions enable autonomous decision-making, problem-solving, and task execution without constant human intervention. These AI agents can perceive their environment, adapt to new inputs, and take proactive actions, making them valuable across various industries. In the Create agentic AI solutions by using Azure AI Foundry Plan on Microsoft Learn, you’ll find out how developing agentic AI solutions requires a platform that provides scalability, adaptability, and security. With pre-built AI models, MLOps tools, and deep integrations with Azure services, Azure AI Foundry simplifies the development of custom AI agents that can interact with data, make real-time decisions, and continuously learn from new information. You’ll also: Learn how to describe the core features and capabilities of Azure AI Foundry, provision and manage Azure AI resources, create and manage AI projects, and determine when to use Azure AI Foundry. Discover how to customize with RAG in Azure AI Foundry, Azure AI Foundry SDK, or Azure OpenAI Service to look for answers in documents. Learn how to use Azure AI Agent Service, a comprehensive suite of feature-rich, managed capabilities, to bring together the models, data, tools, and services your enterprise needs to automate business processes There’s also a Microsoft Virtual Training Day featuring interactive sessions and expert guidance, and you can validate your skills by earning a Microsoft Certification. Safeguard your AI systems for security and fairness Widespread AI adoption demands rigorous security, fairness, and transparency safeguards to prevent bias, privacy breaches, and vulnerabilities that lead to unethical outcomes or non-compliance. Organizations must implement responsible AI through robust data governance, explainability, bias mitigation, and user safety protocols, while protecting sensitive data and ensuring outputs align with ethical standards. Our third Plan on Microsoft Learn, Build secure and responsible AI solutions and manage generative AI lifecycles, is designed to introduce the basics of AI security and responsible AI to help increase the security posture of AI environments. You’ll not only learn how to evaluate and improve generative AI outputs for quality and safety, but you’ll also: Gain an understanding of the basic concepts of AI security and responsible AI to help increase the security posture of AI environments. Learn how to assess and improve generative AI outputs for quality and safety. Discover how to help reduce risks by using Azure AI Content Safety to detect, moderate, and manage harmful content. Learn more by taking part in an interactive, expert-guided Microsoft Virtual Training Day to deepen your understanding of core AI concepts. Got a skilling question? Our new Ask Learn AI assistant is here to help Beyond our comprehensive Plans on Microsoft Learn, we’re also excited to introduce Ask Learn, our newest skilling innovation! Ask Learn is an AI assistant that can answer questions, clarify concepts, and define terms throughout your training experience. Ask Learn is your Copilot for getting skilled in AI, helping to answer your questions within the Microsoft Learn interface, so you don’t have to search elsewhere for the information. Simply click the Ask Learn icon at the top corner of the page to activate! Begin your generative AI skilling journey with curated Azure skilling Plans Azure AI Foundry provides the necessary platform to train, test, and deploy AI solutions at scale, and with the expert-curated skilling resources available in our newly refreshed Plans on Microsoft learn, your teams can accelerate the creation of intelligent, self-improving AI agents tailored to your business needs. Get started today! Find the best model for your generative AI solution with Azure AI Foundry Create agentic AI solutions by using Azure AI Foundry Build secure and responsible AI solutions and manage generative AI lifecyclesIngeniería de prompts con GitHub Copilot: Potenciando el desarrollo de software con IA
GitHub Copilot está revolucionando el desarrollo con inteligencia artificial. 🚀 En el Bootcamp de GitHub Copilot LATAM, exploramos cómo usarlo para escribir mejor código, refactorizar proyectos y automatizar tareas. Desde prompts estratégicos hasta pruebas unitarias y trabajo con grandes bases de código, esta sesión cubrió herramientas clave para maximizar la productividad. ¿Listo para llevar tu desarrollo al siguiente nivel? Únete al desafío, accede a recursos exclusivos y mejora tus habilidades con GitHub Copilot. 🔥 #GitHubCopilot #IA #DesarrolloContributor Stories: Deepanshu Katara
If you’ve ever engaged with the content on the Microsoft Learn platform, the material you utilized was likely written or co-authored by dedicated contributors. These contributors, often volunteers, generously offer their time and expertise to fill knowledge gaps within our content portfolio by suggesting valuable updates to our material, sharing their knowledge within the Microsoft community, and/or answering questions on the Q&A area of the Microsoft Learn platform. In this interview series, we aim to acquaint ourselves with some of these valuable contributors. Through these conversations, we seek to understand their motivations for sharing their knowledge on Microsoft Learn and gain insights into their experiences. Welcome and congratulations on being our spotlighted contributor this month: Deepanshu Katara, a dedicated Lead Systems Engineer based in India. With around eight years of experience as a Cloud and DevOps Architect, Deepanshu has led high-impact projects for global clients in the retail, healthcare, and technology sectors. At EPAM Systems, Deepanshu spearheaded cloud migration and digital transformation initiatives using Azure DevOps, Terraform, and Bicep, ensuring seamless application deployment and operational excellence. Deepanshu is an active member of Microsoft Community Champions. This program identifies, engages, and rewards technology experts who frequently provide high-quality answers to customers' questions on Microsoft Learn Q&A. Deepanshu is an Azure technology subject matter expert (SME), specifically focuses on Azure Q&A. He has answered over 1,000+ questions - supporting thousands of Azure users on Microsoft Learn Q&A by unblocking them from technical roadblocks. Meet Deepanshu Deepanshu Katara, Lead Systems Engineer at Epam Systems and Microsoft MVP. Priyanka: Hi Deepanshu! It's great to have you with us today. Could you start by telling us a bit about your background and experience? Deepanshu: Absolutely, Priyanka! I’m happy to. I thrive in collaborative environments where I can mentor teams and drive innovation. My experience includes architecting Kubernetes infrastructure, implementing secure cloud solutions, and automating deployments. Additionally, I actively contribute to the Azure community by organizing and hosting the weekly Azure Tech Talk series, which fosters knowledge-sharing and collaboration within the organization. My dedication to excellence and innovation is evident in my commitment to mentoring, integrating Agile methodologies, and architecting secure, scalable cloud solutions. With years of experience as a Cloud and DevOps Architect, I bring a wealth of expertise in multi-cloud engineering, DevOps practices, and Infrastructure as Code (IaC). My journey has involved leading and contributing to high-impact projects for global clients across retail, healthcare, and technology sectors. Priyanka: That’s wonderful to hear! Thank you for sharing your impressive background, Deepanshu. Your extensive experience in multi-cloud engineering, DevOps practices, and Infrastructure as Code (IaC) is commendable. What inspired you to begin your journey with Microsoft Learn and the Microsoft Tech Community? Deepanshu: My journey as a top contributor began as a curious user seeking solutions to my Azure-related questions on a Q&A platform. Initially, I relied heavily on the community to resolve challenges, and this invaluable resource shaped my early understanding of Azure. Over time, as I gained knowledge and practical experience, I realized the power of shared expertise and decided to give back by contributing to the same platform that had once guided me. This transition from a learner to a contributor marked the beginning of a fulfilling journey. What keeps me motivated is the dual benefit of contributing: helping others while continuously growing myself. Sharing expertise not only allows me to support the community but also ensures I stay updated with the latest technologies and tools in Azure. Engaging with diverse questions and scenarios sharpens my problem-solving skills and deepens my technical knowledge. Additionally, it helps me refine my soft skills, such as communication and mentorship, enabling me to articulate complex concepts clearly and effectively. This mutual exchange of learning and giving back makes contributing a deeply rewarding experience, fueling my passion to remain an active participant in the community. Priyanka: It's truly inspiring to hear how you transitioned from a learner to a top contributor and how your dedication to helping others has fueled your own growth. Your commitment to fostering a knowledge-sharing culture and driving innovation within the Azure community is commendable. I’d love to know what led you to start contributing to Microsoft Learn. What inspired you to take that step and become an active participant in the community? Deepanshu: Contributing to the Microsoft Learn platform has been pivotal in advancing my career and enhancing my skill set. Engaging with the community has allowed me to explore a wide range of Azure technologies and scenarios beyond my daily responsibilities. This exposure has significantly broadened my technical expertise, keeping me up-to-date with the latest advancements in Azure and related tools. Additionally, crafting detailed and precise responses to complex queries has honed my problem-solving abilities and improved my capability to communicate technical concepts effectively. This experience has also boosted my confidence in sharing knowledge and mentoring others, positively impacting my leadership skills. It has strengthened my ability to think critically and adapt quickly to new challenges. By actively contributing, I have not only solidified my understanding of Azure technologies but also gained recognition within the community, opening doors to new opportunities and collaborations in my professional journey. 🙂 Priyanka: That's fantastic! Having real-time visibility of potential problems on the Q&A site, along with exposure to diverse solutions, can significantly impact someone's technical growth. I'm glad to hear that you're enjoying it and making a difference by helping hundreds of users. Could you shed some light on your experience partnering with Microsoft as part of Microsoft Community Champions so far? Deepanshu: Partnering with Microsoft through the Azure Community Champions program has been an incredibly collaborative and empowering experience. One recent example that stands out is when I needed assistance in designing an audit framework for Azure resources at the management group level. The task was complex and required a thorough understanding of Azure's hierarchical resource organization, policies, and best practices. Reaching out to the community of fellow champions proved invaluable. I received exceptional support and insights from other champions who shared their expertise, tools, and real-world experiences, helping me craft a robust and scalable framework. This experience highlighted the strength of the Azure Community Champions program as not just a knowledge-sharing platform but a collaborative network where professionals support each other in solving advanced technical challenges. It reaffirmed the value of being part of such a passionate and knowledgeable group, fostering continuous learning and mutual growth while contributing to impactful Azure solutions. Priyanka: I’m glad you got that little nudge to join our Microsoft Q&A Community and to contribute to it – sounds like it was an excellent experience for you. What advice would you give to people who want to start contributing to technical community forums? Deepanshu: For those looking to start contributing to forums, my advice is to begin by identifying areas you are passionate about or technologies you frequently use. Start small—explore existing open-source projects, participate in discussions, or address issues flagged by the community. You don’t need to be an expert; even updating documentation, fixing minor bugs, or sharing feedback can make a significant impact. Platforms like MS Q&A and other community forums provide an excellent starting point for discovering projects and interacting with contributors. Consistency and collaboration are key to building your presence in the open-source community. Approach your contributions with a learning mindset and focus on adding value while honing your skills. Don’t hesitate to ask questions or seek guidance from experienced contributors; open source thrives on inclusivity and mentorship. Over time, contributing will enhance your technical expertise and improve your collaboration and problem-solving skills, creating opportunities for personal and professional growth. Priyanka: Awesome insight and advice, thanks! One final question for you. One purpose of this interview is to learn a little about the person behind the contributions. What do you like to do in your spare time? Do you have any hobbies? Deepanshu: Outside of work, I am an avid sports enthusiast and love engaging in physical activities. I frequently participate in corporate cricket tournaments and enjoy playing basketball. Athletics have always been a significant part of my life—I used to compete in the shot put, which instilled in me discipline and a love for competition. Staying active through sports not only keeps me physically fit but also enhances my teamwork and focus, qualities I bring into my professional life. In addition to sports, I enjoy spending my free time watching movies and relaxing with my son, who bring immense joy and relaxation to my routine. These activities provide a perfect balance to my tech-driven career, keeping me refreshed and inspired while offering opportunities for connection and leisure. Priyanka: That's wonderful to hear! Engaging in sports and physical activities is a fantastic way to stay fit and maintain a healthy work-life balance. Participating in corporate cricket tournaments and playing basketball must be a lot of fun. Well, it was wonderful meeting you today. Before we finish up, is there anything else you’d like to share about your experience contributing? Deepanshu: Thanks, Priyanka. It was nice to meet you, as well! I'd like to share that contributing to the community has been an incredibly rewarding experience. It has allowed me to learn, grow, and connect with like-minded professionals continuously. The support and collaboration within the community have been invaluable, and I'm grateful for the opportunity to give back and help others on their journey. Thank you for having me! Priyanka: It was great having you, Deepanshu. I wish you the best of luck in all your endeavors. Kudos to you for all the great work you have been doing with the online communities and Microsoft Learn Q&A forum. Thank you. Keep up with Deepanshu: Personal website: https://dkatara.wordpress.com/ LinkedIn: https://www.linkedin.com/in/deepanshu-katara-1ab365152 X (formerly Twitter): https://x.com/imkatara Credly: https://www.credly.com/users/deepanshu-katara Medium: https://medium.com/@dkatara.pandit Contribute at Microsoft: To Contribute to Microsoft Learn, visit Microsoft Learn Contributor Home. To be a part of Microsoft Community Champions Program and contribute to the Microsoft Learn Q&A for Azure sign up using this formRAG Time: Ultimate Guide to Mastering RAG!
RAG Time is a brand-new AI learning series designed to help developers unlock the full potential of Retrieval-Augmented Generation (RAG). If you’ve been looking for a way to build smarter, more efficient AI systems—join us in RAG Time, every Wednesday 9AM PT from March 5 through April 2 on Microsoft Developer YouTube. What's in RAG Time? RAG Time is a five-part learning journey, with new videos and blog posts releasing every week in March. The series features: 🔥 Expert-led discussions breaking down RAG fundamentals and best practices 🎤 Exclusive leadership interviews with AI leaders ⚡ Hands-on demos & real-world case studies showing RAG in action 🎨 Creative doodle summaries making complex concepts easier to grasp and remember 🛠 Samples & resources in the RAG Time repository so you can start building today What You’ll Learn The series is structured into five learning journeys, each tackling a crucial aspect of RAG-powered AI: 📌 March 5th, 9AM PT - Journey 1: RAG and Knowledge Retrieval Fundamentals – Start with the basics! Learn how RAG, search indexing, and vector search work together to create smarter AI retrieval systems. 📌 March 12th, 9AM PT - Journey 2: Build the Ultimate Retrieval System for RAG – Go beyond the fundamentals with hybrid search, semantic ranking, and relevance tuning to refine how AI retrieves the most relevant information. 📌 March 19th, 9AM PT - Journey 3: Optimize Your Vector Index for Scale – Learn how to scale vector search efficiently, optimize storage, and implement advanced techniques like quantization and Matryoshka learning for large-scale AI applications. 📌 March 26th, 9AM PT - Journey 4: RAG for All Your Data: Multimodal and Beyond – Move beyond text-based retrieval! Discover how to integrate images, audio, and structured data into your RAG workflows and leverage multimodal pipelines for next-level AI capabilities. 📌 April 2nd, 9AM PT - Journey 5: Hero Use Cases for RAG – Explore real-world implementations, industry-leading examples, and best practices, while diving into Responsible AI considerations to ensure ethical and impactful solutions. Why You Should Watch If you're a developer, data scientist, or AI enthusiast, this series is built for you! Whether you’re just getting started or looking to master enterprise-grade retrieval systems, RAG Time delivers practical knowledge, hands-on resources, and expert insights to help you stay ahead. Journey starts here 🚀 Start your journey from the RAG Time repo: https://aka.ms/rag-time. You'll find all the information about the video series, samples, documentation and doodles in the repo! Share your experience and feedback on GitHub discussions.
