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Azure OpenAI Assistants and Azure AI Agent Services: Benefits and Opportunities","conversation":{"__ref":"Conversation:conversation:4386055"},"id":"message:4386055","revisionNum":2,"uid":4386055,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:2204790"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":1172},"postTime":"2025-02-26T06:03:04.434-08:00","lastPublishTime":"2025-02-26T06:03:04.434-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" In the rapidly evolving landscape of artificial intelligence, businesses are increasingly turning to cloud-based solutions to harness the power of AI. Microsoft Azure offers two prominent services in this domain: Azure OpenAI Assistants and Azure AI Agent Services. \n While both services aim to enhance user experiences and streamline operations, they cater to different needs and use cases. \n This blog post will delve into the details of each service, their benefits, and the opportunities they present for businesses. \n \n \n \n Understanding Azure OpenAI Assistants \n What Are Azure OpenAI Assistants? \n Azure OpenAI Assistants are designed to leverage the capabilities of OpenAI's models, such as GPT-3 and its successors. These assistants are tailored for applications that require advanced natural language processing (NLP) and understanding, making them ideal for conversational agents, chatbots, and other interactive applications. \n Key Features \n Pre-trained Models: Azure OpenAI Assistants utilize pre-trained models from OpenAI, which means they come with a wealth of knowledge and language understanding out of the box. This reduces the time and effort required for training models from scratch. \n \n \n Customizability: While the models are pre-trained, developers can fine-tune them to meet specific business needs. This allows for the creation of personalized experiences that resonate with users. \n \n \n \n Integration with Azure Ecosystem: Azure OpenAI Assistants seamlessly integrate with other Azure services, such as Azure Functions, Azure Logic Apps, and Azure Cognitive Services. This enables businesses to build comprehensive solutions that leverage multiple Azure capabilities. \n \n \n \n Benefits of Azure OpenAI Assistants \n \n Enhanced User Experience: By utilizing advanced NLP capabilities, Azure OpenAI Assistants can provide more natural and engaging interactions. This leads to improved customer satisfaction and loyalty. \n \n \n \n Rapid Deployment: The availability of pre-trained models allows businesses to deploy AI solutions quickly. This is particularly beneficial for organizations looking to implement AI without extensive development time. \n \n \n \n Scalability: Azure's cloud infrastructure ensures that applications built with OpenAI Assistants can scale to meet growing user demands without compromising performance. \n \n \n \n \n Understanding Azure AI Agent Services \n What Are Azure AI Agent Services? \n Azure AI Agent Services provide a more flexible framework for building AI-driven applications. Unlike Azure OpenAI Assistants, which are limited to OpenAI models, Azure AI Agent Services allow developers to utilize a variety of AI models, including those from other providers or custom-built models. \n \n \n \n Key Features \n \n Model Agnosticism: Developers can choose from a wide range of AI models, enabling them to select the best fit for their specific use case. This flexibility encourages innovation and experimentation. \n \n \n \n Custom Agent Development: Azure AI Agent Services support the creation of custom agents that can perform a variety of tasks, from simple queries to complex decision-making processes. \n \n \n \n Integration with Other AI Services: Like OpenAI Assistants, Azure AI Agent Services can integrate with other Azure services, allowing for the creation of sophisticated AI solutions that leverage multiple technologies. \n \n \n Benefits of Azure AI Agent Services \n \n Diverse Use Cases: The ability to use any AI model opens a world of possibilities for businesses. Whether it's a specialized model for sentiment analysis or a custom-built model for a niche application, organizations can tailor their solutions to meet specific needs. \n \n \n \n Enhanced Automation: AI agents can automate repetitive tasks, freeing up human resources for more strategic activities. This leads to increased efficiency and productivity. \n \n \n \n Cost-Effectiveness: By allowing the use of various models, businesses can choose cost-effective solutions that align with their budget and performance requirements. \n \n \n Opportunities for Businesses \n \n Improved Customer Engagement \n \n Both Azure OpenAI Assistants and Azure AI Agent Services can significantly enhance customer engagement. By providing personalized and context-aware interactions, businesses can create a more satisfying user experience. For example, a retail company can use an AI assistant to provide tailored product recommendations based on customer preferences and past purchases. \n \n \n Data-Driven Decision Making \n \n AI agents can analyze vast amounts of data and provide actionable insights. This capability enables organizations to make informed decisions based on real-time data analysis. For instance, a financial institution can deploy an AI agent to monitor market trends and provide investment recommendations to clients. \n \n \n Streamlined Operations \n \n By automating routine tasks, businesses can streamline their operations and reduce operational costs. For example, a customer support team can use AI agents to handle common inquiries, allowing human agents to focus on more complex issues. \n \n \n Innovation and Experimentation \n \n The flexibility of Azure AI Agent Services encourages innovation. Developers can experiment with different models and approaches to find the most effective solutions for their specific challenges. This culture of experimentation can lead to breakthroughs in product development and service delivery. \n \n \n Enhanced Analytics and Insights \n \n Integrating AI agents with analytics tools can provide businesses with deeper insights into customer behavior and preferences. This data can inform marketing strategies, product development, and customer service improvements. For example, a company can analyze interactions with an AI assistant to identify common customer pain points, allowing them to address these issues proactively. \n \n \n \n Conclusion \n In summary, both Azure OpenAI Assistants and Azure AI Agent Services offer unique advantages that can significantly benefit businesses looking to leverage AI technology. \n \n Azure OpenAI Assistants provide a robust framework for building conversational agents using advanced OpenAI models, making them ideal for applications that require sophisticated natural language understanding and generation. Their ease of integration, rapid deployment, and enhanced user experience make them a compelling choice for businesses focused on customer engagement. \n \n Azure AI Agent Services, on the other hand, offer unparalleled flexibility by allowing developers to utilize a variety of AI models. This model-agnostic approach encourages innovation and experimentation, enabling businesses to tailor solutions to their specific needs. The ability to automate tasks and streamline operations can lead to significant cost savings and increased efficiency. \n \n Additional Resources \n To further explore Azure OpenAI Assistants and Azure AI Agent Services, consider the following resources: \n Agent Service on Microsoft Learn Docs \n Watch On-Demand Sessions \n Streamlining Customer Service with AI-Powered Agents: \n Building Intelligent Multi-Agent Systems with Azure AI \n Microsoft learn Develop AI agents on Azure - Training | Microsoft Learn \n \n Community and Announcements \n Tech Community Announcement: Introducing Azure AI Agent Service \n Bonus Blog Post: Announcing the Public Preview of Azure AI Agent Service \n AI Agents for Beginners 10 Lesson Course https://aka.ms/ai-agents-beginners 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Automated Documentation Maintenance for Open-source GitHub Repositories","conversation":{"__ref":"Conversation:conversation:4245588"},"id":"message:4245588","revisionNum":11,"uid":4245588,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:2588119"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n \n Codeβlevel documentation of a software system provides explanations of the code functionality and usages. Documentation is crucial for giving clear insights into the code for endβusers and future developers. However, creating and updating documentation manually is a demanding task, requiring significant resources and labour. With the advancement of generative AI, there is a potential to reduce human labour in documentation tasks significantly. We propose DocAider, an automation tool powered by GPTβ4 that integrates the processes of documentation generation and update. DocAider can generate comprehensive and structured documentation in markdown format and update it in response to any changes made in pull requests. The mission of DocAider is to reduce developersβ burden on maintaining documentation for GitHub repositories. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":3156},"postTime":"2024-09-17T00:00:00.026-07:00","lastPublishTime":"2024-09-17T00:00:00.026-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Project Overview \n Comprehensive documentation is crucial for end users in open-source software projects, but manual creation and maintenance are time-consuming and costly. Traditional documentation generators like Pydoc rely on predefined rules and in-line code information. However, emerging generative AI techniques, particularly Large Language Models (LLMs), offer new possibilities for enhanced documentation generation. Developed in partnership with Microsoft and UCL, DocAider aims to create an AI-powered documentation tool that automatically generates and updates code documentation. The tool leverages Github Actions workflows to trigger documentation tasks upon pull requests (PRs) opening, providing valuable insights into continuous documentation maintenance. This approach addresses the challenges of automating documentation and ensures that project documentation remains current with minimal human intervention. This project aims to leverage LLM technologies, combined with Microsoft Semantic Kernel, Microsoft Autogen, and Azure AI Studio, to mitigate the burden of maintaining up-to-date documentation. This system uses a multi-agent architecture where multiple agents work together to complete the task. It offers two innovative features: a recursive update mechanism, which ensures that changes ripple throughout all related documentation, and continuous monitoring and updating code via pull requests. DocAider offers a promising solution for software engineers, with the potential to automatically maintain clean and up-to-date documentation. It allows developers to concentrate more on coding while simplifying the onboarding process for new team members. Additionally, it helps reduce costs and boosts overall efficiency. \n \n Project Journey \n This project was completed over 3 months. The few weeks, the team focused on the requirements engineering portion of the project, where we set functional and non-functional requirements, created context and architecture diagrams and broke the project down with the stakeholders, so that it was easy for us to implement in the following months, making sure we included the most important features and requirements. This process also allowed the team to see how much is realistically achievable, and what should be kept as optional if time allowed us to complete. During implementation, our team employed agile methodologies, Git practices, and continuous integration and testing. We chose agile as our development approach because it facilitated constant communication between the team and stakeholders. This strategy proved crucial to our product's success. Bi-weekly meetings with stakeholders allowed us to report progress, plan upcoming tasks and clarify the requirements. Additionally, we held weekly internal meetings for team members to showcase their work and assess overall progress. \n \n Technical Details \n DocAider is an LLM-powered tool that generates and updates documentation automatically. It performs the documentation tasks using a customised GitHub Actions workflow and runs in the background. We developed DocAider by integrating Semantic Kernel and AutoGen. The tools facilitate the development of AI-based software. Furthermore, we deployed and managed Azure OpenAI LLMs on Azure AI Studio. To obtain good results, we used the GPT-4-0125-preview model to create documentation for the source code. The temperature parameter was set between 0 and 0.2 for more deterministic and factual LLM responses. \n \n Documentation Generation \n \n \n AutoGen provides multiple conversation patterns to orchestrate AI agents, such as sequential chats, group chats, nested chats, etc. We used the sequential chats to create documentation. The figure shows our multi-agent architecture, which reduces LLM hallucinations in two ways: appropriate code context information and self-improvement. Four agents perform different tasks in sequence and an agent manager controls the multi-agent conversation. \n \n Code Context Agent creates a graph representation of the entire repository, mapping the relationships between function calls. It then generates comprehensive information about the codebase using the actual source code and the relationship graph. \n Documentation Generation Agent produces baseline documentation taking into account the contextual information passed from the previous agent. The documentation contains three basic sections: overview, class/function/method descriptions and input/output examples. \n Review Agent assesses the baseline documentation, and suggests the improvements. \n Revise Agent modifies the baseline documentation according to the suggestions and returns the improved documentation to Agent Manager. \n Agent Manager controls the conversation process and responds to function calling requests from LLM-configured agents. \n \n By using Semantic Kernel, we built skilled agents for performing specific tasks. AutoGen facilitates agent interactions to complete complex workflows. The LLM function calling capability helps to reduce programming efforts and makes agents flexible. An agent can autonomously execute external functions defined in the associated plugins to complete a variety of tasks. \n \n Documentation Update \n To maintain consistency and accuracy across all related documentation when a class/function in a file is changed, the Documentation Update feature performs the update recursively. If a class/function is modified, the system will automatically update the documentation for all dependent files. This includes documentation of the source file, as well as documentation of files that use functions dependent on the changed class/function. This recursive update feature ensures that all related documentation remains upβtoβdate with the latest changes in the code. \n Additionally, Documentation update on PR Comment allows reviewers to trigger the documentation updates on specified files by commenting in a specific format. The reviewer can specify which file needs an update and provide instructions on what changes should be made. The system will then process this comment and update the documentation as instructed. This feature ensures that precise and targeted documentation updates can be made based on reviewer feedback, improving the overall quality and relevance of the documentation. Furthermore, it removes the need for developers to manually change documentation according to reviewersβ comments. The comment triggering this process needs to be in this format: \n \n βDocumentation {file_path}: {comment}β. For example, βDocumentation main.py: Add more I/O examplesβ. \n \n Results and Outcome \n Our evaluation process involved three stages: a case study executing our system on a wellβknown repository to showcase our system, a comparison of our system against RepoAgent, and a quantitative analysis. Through this process, we could determine our systemβs performance. \n \n Case Study: \n The section presents results from applying our tool to generate and update documentation for the Graphviz repository's Python files. The system produced well-structured documentation, including overviews, global variables, function/class descriptions, and I/O examples, providing clear explanations of file purposes and usage guidelines. When updates were made to the base.py file, adding logging functionality and a new method, the system successfully incorporated these changes while preserving existing content. The system also demonstrated its ability to handle recursive updates, propagating changes from the ParameterBase class in base.py to dependent files like engine.py. Additionally, it responded effectively to a PR comment, requesting more input/output examples, showcasing its capacity to incorporate reviewer feedback. Overall, the multi-agent system proved capable of generating, updating, and maintaining comprehensive documentation across all files in a software repository. \n \n \n Comparison with RepoAgent \n We compared DocAider, a multi-agent documentation system, with RepoAgent, another LLM-based documentation generation tool. While RepoAgent produces lengthy paragraphs, DocAider generates concise, bullet-pointed documentation, aligning with developers' preferences for brevity. DocAider's multi-agent approach potentially enhances accuracy and reduces hallucinations compared to RepoAgent's single-agent system. DocAider also implements a Reviewer and Revisor agent to suggest and apply improvements. A notable feature of DocAider is its HTML-based front-end interface, which improves documentation accessibility and organization - factors highly valued by developers. While our system is well-designed and offers unique features like recursive updates, RepoAgent stands out by providing thorough I/O examples for every function. However, LLMs can make incorrect assumptions as function complexity increases, leading to factual inaccuracies or nonsensical outputs. To mitigate this, we restrict the LLM from making such assumptions, resulting in some functions/classes lacking I/O examples. \n Quantitive Analysis \n \n \n We conducted a quantitative analysis of DocAider's performance across six popular GitHub repositories: collarama, fake-useragent, graphiz, photon, progress, and pywhat. These repositories were selected based on their popularity (over 1000 stars each) and size (small to medium, limited to 20 files per repository). All of them varied in the number of functions and classes. Scores are normalised between 0 and 1, reflecting the presence of these attributes in the documentation. For instance, a score of 1 for Function/Class Description indicates that every class and function in the repository is described in the documentation, while a score of 0.5 for I/O examples means that only half of the functions have I/O examples provided in the documentation. \n DocAider achieved perfect scores (1.0) for function/class descriptions across all repositories, demonstrating consistent performance. For parameters/attributes, most repositories received perfect scores, with only collamara scoring slightly lower at 0.94 due to two functions lacking parameter documentation. I/O examples showed the most variation, with scores ranging from 0.54 (photon and progress) to 0.88 (collamara). Lower scores were often due to specific function types without return values (e.g., class init methods) or complex logic that made example generation challenging. Return value documentation was consistently strong, with all repositories scoring 1.0. \n Overall, DocAider is proficient in many areas, such as generating function/class descriptions and handling most documentation aspects. However, there is room for improvement in consistently documenting I/O examples, particularly for functions with more complex logic. \n \n Lessons Learned \n The development of DocAider provided valuable insights across several key areas. Firstly, the adoption of a multi-agent approach proved crucial in managing system's complexity. Initially, a single-agent design led to issues such as hallucinations and incomplete documentation. By transitioning to a multi-agent architecture, the team was able to distribute tasks across specialized agents, each handling specific aspects of the documentation process. This approach significantly improved the accuracy and reliability of the documentation while also enhancing system scalability. The success of this strategy highlighted the importance of modular design and task specialization in complex AI-driven systems. Secondly, prompt engineering emerged as a critical and unexpectedly challenging aspect of the project. The quality of generated documentation was heavily dependent on the prompts given to the Large Language Models (LLMs). Initial struggles with overly broad or contextually lacking prompts led to irrelevant or inaccurate outputs. Through iterative testing and refinement, the team developed more precise and context-aware prompts, significantly improving documentation quality. This experience underscored the complexity and importance of effective prompt engineering in applications requiring high accuracy and relevance. Lastly, the team learned the critical importance of managing dependency versions. An incident where a new version of Semantic Kernel (1.3.0) caused the software to crash in Docker due to API changes highlighted the need for version consistency across development and deployment environments. This experience emphasized the importance of carefully managing and aligning dependency versions to ensure system stability and functionality. \n \n Team Contributions \n Jakupov Dias (Team Leader): Team management, Stakeholder communication, development of Documentation Update, Recursive Update, Update on PR comment, prompt engineering. \n Chengqi Ke: development of Retrieval Augmented Generation and multi-agent communication using Semantic Kernel and AutoGen. \n Fatima Hussain: development of GitHub workflows, evaluation of DocAider's performance and effectiveness. \n Tanmay Thaware: development of Retrieval Augmented Generation, evaluation of DocAider's performance. \n Tomas Kopunec: development of Abstract Syntax Tree, Recursive Update and HTML front-end . \n Zena Wang: development of GitHub workflows and handled deployment, packaging the tool into a Docker image. \n \n Future Work \n DocAider's current implementation successfully automates code documentation, but there are several areas for future improvement. First, enhancing the tool's ability to provide comprehensive and accurate I/O examples is a priority. This can be achieved by refining agent prompts and potentially integrating context-specific agents to better interpret complex functions. Second, future evaluations should extend to larger, more complex repositories to assess DocAider's scalability and performance beyond small and medium sized projects. This expansion was previously limited by budget constraints. Third, while initial attempts to use Retrieval-Augmented Generation (RAG) didn't significantly improve documentation quality due to limited contextual knowledge in the repository, future iterations could explore more effective RAG implementations. For instance, retrieving test cases from repositories could enhance the accuracy of I/O examples, and RAG could support the development of repository-specific chatbots to assist developers. Lastly, DocAider's modular and loosely coupled multi-agent design allows for significant scalability potential. The system can easily integrate new features such as code validation, static analysis, or security evaluation without major architectural changes. This flexibility extends to adding or replacing agents, supporting various LLM models, and expanding language support beyond Python, all while maintaining core functionality. \n \n Conclusion \n DocAider successfully automated the creation and upkeep of accurate, up-to-date documentation, significantly reducing the manual workload for developers. By leveraging AI tools like Microsoft AutoGen, Semantic Kernel, and Azure AI Studio, the project addressed key challenges in maintaining consistent, real-time documentation. \n While budget constraints, missing I/O examples, and the limitations of LLMs posed challenges, the project established a solid foundation for future improvements. Beyond solving the immediate need for documentation management, DocAider raised the bar for efficiency and accuracy in software development, showcasing the potential of AI-driven solutions for more advanced applications. \n \n \n Call To Action \n We invite you to explore DocAider further and consider how its innovative approach to documentation maintenance can be applied in your projects. Here are some steps you can take and explore the tools we used: \n \n Connect with Us: Feel free to reach out to our team for more information or collaboration opportunities. \n AutoGen: https://www.microsoft.com/en-us/research/project/autogen/ \n Semantic Kernel: https://learn.microsoft.com/en-us/semantic-kernel/overview/?tabs=Csharp \n \n \n \n Special Thanks to Contributors \n Each contributorβs continuous support and involvement all plays a crucial role in the success of the project, here, we present a special thanks to all following contributors. \n \n Lee Stott, Principal Cloud Advocate Manager at Microsoft \n Diego Colombo, Principal Software Engineer at Microsoft \n Jens Krinke, Senior Lecturer and Academic Supervisor \n \n \n \n Team \n The team involved in developing this project included 6 members. All of us are Masters students at UCL studying Software Systems Engineering \n Dias Jakupov - Team Leader - Full Stack Developer \n GitHub URL: https://github.com/Dias2406/ \n LinkedIn URL: https://www.linkedin.com/in/dias-jakupov-a05258221/ \n Chengqi Ke - Full Stack Developer \n GitHub URL: https://github.com/CQ-Ke/ \n LinkedIn URL: http://linkedin.com/in/chengqi-ke-9b91a8313/ \n Tomas Kopunec - Full Stack Developer \n GitHub URL: https://github.com/TomasKopunec/ \n LinkedIn URL: https://www.linkedin.com/in/tomas-kopunec-425b0199/ \n Fatima Hussain - Full Stack Developer \n GitHub URL: https://github.com/fatimahuss/ \n LinkedIn URL: http://linkedin.com/in/fatima-noor-hussain/ \n Tanmay Thaware - Full Stack Developer \n GitHub URL: https://github.com/tanmaythaware/ \n LinkedIn URL: http://linkedin.com/in/tanmaythaware/ \n Zena Wang - Full Stack Developer \n GitHub URL: https://github.com/ZenaWangqwq/ \n LinkedIn URL: https://www.linkedin.com/in/zena-wang-b63a8822b/ \n \n \n \n \n ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"17675","kudosSumWeight":1,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MjQ1NTg4LTYyMDExMGlDOTE4OEY1MDU5OTBFOUY3?revision=11\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MjQ1NTg4LTYyMDExMWkyMTdBNDE0NEU2QzI4MzBC?revision=11\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDM","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MjQ1NTg4LTYyMDE1OGlCN0EzNEQyQjY5OTEwMDc4?revision=11\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDQ","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MjQ1NTg4LTYyMDE1NWlCM0NGMUI4N0ExOEU5MkIy?revision=11\"}"}}],"totalCount":4,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":null,"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:3584897":{"__typename":"Conversation","id":"conversation:3584897","topic":{"__typename":"BlogTopicMessage","uid":3584897},"lastPostingActivityTime":"2024-09-05T08:18:34.332-07:00","solved":false},"User:user:1373657":{"__typename":"User","uid":1373657,"login":"bethanyjep","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/dS0xMzczNjU3LTQwNDc3MWk3RUMzMkU1RkYxQUQ5RDUz"},"id":"user:1373657"},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNTg0ODk3LTM5MTUxNmk5MEI5RkQzRTc4QjgyOTVC?revision=4\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNTg0ODk3LTM5MTUxNmk5MEI5RkQzRTc4QjgyOTVC?revision=4","title":"bethanyjep_0-1659014312819.png","associationType":"BODY","width":1600,"height":900,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNTg0ODk3LTM5MTUxN2kxN0JFMDQzNDI2RTE5REEz?revision=4\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNTg0ODk3LTM5MTUxN2kxN0JFMDQzNDI2RTE5REEz?revision=4","title":"bethanyjep_1-1659014361495.png","associationType":"BODY","width":888,"height":225,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNTg0ODk3LTM5MTUxOWlBMDM4NUU4MDFFQTRFMjM5?revision=4\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNTg0ODk3LTM5MTUxOWlBMDM4NUU4MDFFQTRFMjM5?revision=4","title":"bethanyjep_2-1659014361500.png","associationType":"BODY","width":1600,"height":856,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNTg0ODk3LTM5MTUxOGk4RTU2N0Y5QjJBRkQ4MDIz?revision=4\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zNTg0ODk3LTM5MTUxOGk4RTU2N0Y5QjJBRkQ4MDIz?revision=4","title":"bethanyjep_3-1659014361503.png","associationType":"BODY","width":1600,"height":353,"altText":null},"BlogTopicMessage:message:3584897":{"__typename":"BlogTopicMessage","subject":"How to get a Microsoft Discounted Student Certificationt.","conversation":{"__ref":"Conversation:conversation:3584897"},"id":"message:3584897","revisionNum":4,"uid":3584897,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1373657"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Certifications are a way to stand out from the rest. Other than boosting your confidence, certifications can help you land a new job, get a promotion, or even attract more clients. Microsoft certification offers numerous opportunities, not just for developers but also low code citizen developers. As a student, you can jump start your career with free fundamental certifications. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":280039},"postTime":"2022-07-28T06:51:44.698-07:00","lastPublishTime":"2023-11-07T10:57:33.355-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" \n Certifications are a way to stand out from the rest. Other than boosting your confidence, certifications can help you land a new job, get a promotion or even attract more clients. Microsoft certification offers numerous opportunities, not just for developers but also low code citizen developers. As a student, you can jump start your career with free fundamental certifications. \n \n \n Student Certification Discount \n \n What is the Certification Process? \n \n \n Create your account on Microsoft Learn \n \n The first place to start your certification is Microsoft Learn. Microsoft Learn contains a collection of learning paths and modules to skill you up on different technology areas as well as soft skills. The platform is comprehensive and will get you well on your way to certification. Once on the landing page, click sign in the top right and sign up to the platform using your Microsoft account. \n \n \n Pick and prepare for a certification of your choice \n \n Microsoft Fundamental certifications are based on different technology areas and industry roles. To get started, you need to identify and select the right path for you. Remember, you can still come back and do the other certification exams at a future date. Once you select the certification of your choice, take time to prepare and skill up on the selected area. \n \n \n Verify your student status and claim your benefits. \n \n \n Sit for the exam and become Microsoft Certified! \n \n \n You have prepared for the exam, done the practice tests and are now ready to sit for the exam. On the exam day, ensure you are well prepared, have stable internet connection, and proper identification documents. \n \n Showcase your achievement. \n \n It is now time to celebrate your success. Once you have successfully passed your exam, you will receive a digital badge. Share the badge with your networks and add it to your LinkedIn profile. \n \n You are now certified, what next? \n Certifications help you stand out and open you up to more opportunities. Whether you are starting out in your career or looking for a career shift, certifications guide you in the right direction. Below are some success stories from past individuals who got certified: \n \n Certifications can spark confidence amidst unexpected changes \n Sheryl Netley builds new career on Microsoft Power Platform and Dynamics 365 \n How the Microsoft Certification community can help you and your career \n \n 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Studio AI Toolkit : Building Phi-3 GenAI Applications","conversation":{"__ref":"Conversation:conversation:4179355"},"id":"message:4179355","revisionNum":7,"uid":4179355,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:2282848"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Port Forwarding, a valuable feature within the AI Toolkit, serves as a crucial gateway for seamless communication with the GenAI model. Whether it's through a straightforward API call or leveraging the SDKs, this functionality greatly enhances our ability to harness the power of the LLM/SLM. By enabling Port Forwarding, a plethora of new scenarios unfold, unlocking the full potential of our interactions with the model. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":9211},"postTime":"2024-07-04T00:00:00.030-07:00","lastPublishTime":"2024-07-04T09:50:39.713-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Level up your Generative AI development with Microsoftβs AI Toolkit! In the previous blog, we explored how AI Toolkit empowers you to run LLMs/SLMs locally. \n \n AI toolkit lets us to, \n \n Run pre-optimized AI models locally: Get started quickly with models designed for various setups, including Windows 11 running with DirectML acceleration or direct CPU, Linux with NVIDIA GPUs, or CPU-only environments. \n Test and integrate models seamlessly: Experiment with models in a user-friendly playground or use a REST API to incorporate them directly into your application. \n Fine-tune models for specific needs: Customize pre-trained models (like popular SLMs Phi-3 and Mistral) locally or in the cloud to enhance performance, tailor responses, and control their style. \n Deploy your AI-powered features: Choose between cloud deployment or embedding them within your device applications. \n \n Port Forwarding, a valuable feature within the AI Toolkit, serves as a crucial gateway for seamless communication with the GenAI model. Whether it's through a straightforward API call or leveraging the SDKs, this functionality greatly enhances our ability to harness the power of the LLM/SLM. By enabling Port Forwarding, a plethora of new scenarios unfold, unlocking the full potential of our interactions with the model. \n \n Port forwarding is like setting up a special path for data to travel between two devices over the internet. In the context of AI Toolkit, port forwarding involves configuring a pathway for communication between the LLM and external applications or systems, enabling seamless data exchange and interaction. \n \n AI toolkit auto forwards the port to 5272 by default. If needed this can be modified or new ports can be added. This can be seen the moment we load the AI Toolkit extension on VS Code. A notification can be seen on the right side of the screen stating the βYour application running on port 5272 is availableβ \n \n The 5272 is default port assigned by AI Toolkit, if we wish to add more ports, that can be done by navigating to the PORTS terminal on VS Code and then clicking on the βAdd Portsβ button. \n \n In this, we can see the section βForwarded addressβ. This is the address which will be used for communicating with the SLM. For this tutorial, Phi-3 will be used. This is a Small Language Model from Microsoft. It can be downloaded from the Model Catalog section. \n \n Testing and comprehending the API Endpoint on POSTMAN: \n \n Testing out an application from the API testing application, gives a clear knowledge about the API specification. This can also be done using the coding language, but for this demonstration, I will be showcasing it through the POSTMAN application. Postman application needs to be downloaded and installed on the local machine. Also sign up and create an account if you donβt have one. Once the application is launched, click on create a new request, it will be displayed as β+ββ icon. \n \n In order to do this testing, we would need some basic information about the API that we are testing. Details like Request method, Request URL, request body, type of the request body, authentication type are some of the mandatory things which will be needed. For the Visual Studio Code AI Toolkit API with Phi-3-mini-128k-cuda-int4-onnx model, the details are as follows, \n Authentication: None \n Request method: POST \n Request URL: \n \n \n \n \n http://127.0.0.1:5272/v1/chat/completions \n \n \n \n \n Request Body type: Raw/JSON \n Request Body: \n \n \n \n \n {\n \"model\": \"Phi-3-mini-128k-cuda-int4-onnx\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Hi\"\n }\n ],\n \"temperature\": 0.7,\n \"top_p\": 1,\n \"top_k\": 10,\n \"max_tokens\": 100,\n \"stream\": false\n}\n\n \n \n \n \n \n Authentication will be defaulting to None. So, it can be retained here to None as it is. HTTP request method here would be POST. The Request URL must be checked according to the Port that has been assigned, if it is the default port which is assigned by the visual studio ai toolkit, it will be 5272. Incase, it is changed to any other port, it must be changed in the URL as well. This will be a HTTP request and the URL must contain the URL address, followed by the port and the routes must be set as shown above. \n The βmodelβ parameter in the request body must have the same model that is being loaded in the VS Code AI Toolkit β playground section. \n \n Request body type must be set to Raw and from the dropdown, select JSON. \n \n The streaming parameter must be set to false, else the response will be streamed and divided into sub-classes of JSON which is hard to comprehend. In-case if the application needs streaming, then the parameter can be set to TRUE. \n Once these are ready, use the Send button and wait for the response. If the API call is successful, 200 OK will be displayed and a response body will be visible in the Body tab. \n \n NOTE: The VS Code AI Toolkit must be running in the background, and load the model in the playground before sending the API response in Postman. \n The response of the above request is as follows, \n \n Meanwhile, this will also be reflected on the VS Code AI toolkit Output window as well. \n \n The response body carries quite a lot of information, the answer that will be used in the application is in the βcontentβ division. The code must navigate to the first section of the choices then the messages and finally to the content section. In python, it can be done by, \n \n \n \n \n chat_completion.choices[0].messages.content \n \n \n \n \n This will be further used while building the playground application in the later part of this tutorial. \n The response body also provides some more useful information like the ID, created stamp, finish reason to name a few. The role parameter shows that the response is from the model and hence shows βassistantβ. \n Code snippet can also be generated with the POSTMAN app, which can be then used for testing the API. Following is the example for the Python Code using the HTTP Client. \n \n \n Using the VS Code AI Toolkit with Python: \n \n \n \n \n from openai import OpenAI\n \nclient = OpenAI(\n base_url=\"http://127.0.0.1:5272/v1/\",\n api_key=\"xyz\" # required by API but not used\n)\n \nchat_completion = client.chat.completions.create(\n messages=[\n {\n \"role\": \"user\",\"content\": \"What is the capital of India?β\",\n }\n ],\n model=\"Phi-3-mini-128k-cuda-int4-onnx\",\n) \nprint(chat_completion.choices[0].message.content)\n \n \n \n \n \n The Python script interacts with an API (local instance of OpenAI's API) to get a chat completion. Step-by-step explanation of Python Implementation: \n \n Importing the OpenAI library: The script starts by importing the OpenAI class from the openai package. This class is used to interact with OpenAI's API. It can be installed using the simple python command as follows. \n \n \n \n \n \n pip install openai \n \n \n \n \n Although we are not communicating to the OpenAIβs API, we are utilizing the OS library to interact with the model running in local machine. \n \n Create an OpenAI client instance: Initialize an OpenAI client with a base URL pointing to http://127.0.0.1:5272/v1/, which suggests the API is hosted locally rather than on OpenAI's cloud servers. An API key, \"XYZ\", is also provided, which is noted as required by the API but not used in this context. The API key can be set to anything and not necessarily XYZ. \n Create a chat completion request: The script then creates a chat completion request using the chat.completions.create method of the client. This method is called with two parameters: \n \n \n messages: A list containing a single message dictionary where the role is set to \"user\" and the content is the question \" What is the capital of India?\". This structure mimics a chat interaction where a user asks a question. \n model: Specifies the model to use for generating the completion, in this case, \"Phi-3-mini-128k-cuda-int4-onnx\". This indicates a specific model configuration. \n \n \n Print the response: Finally, the script prints the content of the first message from the response's choices. API returns a list of possible completions (choices), and it accesses the content of the message from the first choice to display the answer to the user's question as demonstrated in the POSTMAN section. \n \n Run the code in a new VS Code window. Preferably use a virtual environment to execute this code. Python is a prerequisite. To learn more, click here. \n \n Execute the code using, the command \n \n \n \n \n python <filename>.py #replace filename with the respective filename. \n \n \n \n \n or click on the run button on the top right side of the Visual Studio Code window. \n \n The response is now printed on the terminal. \n \n Developing Basic Application: \n Similarly, we can use it in applications as well. To demonstrate, lets build a basic application using Streamlit and python. Streamlit turns python scripts into shareable web apps in minutes. To know more click here. To install streamlit, use the following command in the python terminal/VS Code terminal. \n \n \n \n \n pip install streamlit \n \n \n \n \n The following script creates a web-based chat interface using streamlit where users can input queries, which are then sent to an AI model via a local OpenAI API server. The AI's responses are displayed back in the chat interface, facilitating a conversational interaction. \n \n \n \n \n import streamlit as st\nfrom openai import OpenAI\n\nclient = OpenAI(\n base_url=\"http://127.0.0.1:5272/v1/\",\n api_key=\"xyz\" # required by API but not used\n)\n\nst.title(\"Chat with Phi-3\")\nquery = st.chat_input(\"Enter query:\")\n\nif query:\n with st.chat_message(\"user\"):\n st.write(query)\n\n chat_completion = client.chat.completions.create(\n messages=[\n {\"role\": \"user\",\"content\": \"You are a helpful assistant and provides structured answers.\"},\n {\"role\": \"user\", \"content\": query}\n ],\n model=\"Phi-3-mini-128k-cuda-int4-onnx\",\n )\n with st.chat_message(\"assistant\"):\n st.write(chat_completion.choices[0].message.content)\n \n \n \n \n \n Since the above code is using the streamlit, the startup command is also given in a different syntax, the command is as follows, \n \n \n \n \n streamlit run <filename>.py #replace filename with the respective filename. \n \n \n \n \n Upon successful execution, the streamlit pops up a new window in the Microsoft edge with the webpage. \n \n This is how we can create GenAI applications by using the models running on local VS Code AI Toolkit environment. In the upcoming blog, lets see how to apply retrieval augmented generation using the AI Toolkit framework. \n ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"11439","kudosSumWeight":1,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTc5MzU1LTU5NjA5M2k1RkJCOEVDNzAyNDc1RDJE?revision=7\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTc5MzU1LTU5NjA5NGlGQTY3Nzg1NkQ1OUMzODND?revision=7\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDM","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTc5MzU1LTU5NjA5NmkxOEIzNDcyRkYxMzYxMTND?revision=7\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDQ","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTc5MzU1LTU5NjA5N2kyNUQ2NEIxNzgyMjhFQjY5?revision=7\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDU","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTc5MzU1LTU5NjA5OGk5QjUzNTIxRDNCQTNBNzAy?revision=7\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDY","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTc5MzU1LTU5NjEwMWlGRjQzOTYwNDM5MTY1NjMx?revision=7\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDc","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTc5MzU1LTU5NjEwMmlDRkNGQ0YyNEIzQTRCQTVB?revision=7\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDg","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTc5MzU1LTU5NjEwNGk5N0I2MTVFMzRGNEEyRUFF?revision=7\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDk","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTc5MzU1LTU5NjEwNWlGNjNFNDJGQzZBMzRGRjdF?revision=7\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDEw","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTc5MzU1LTU5NjEwNmk0MzAwNzAyQkJFQ0JEMkIz?revision=7\"}"}}],"totalCount":10,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":null,"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:4104500":{"__typename":"Conversation","id":"conversation:4104500","topic":{"__typename":"BlogTopicMessage","uid":4104500},"lastPostingActivityTime":"2024-04-11T06:54:31.573-07:00","solved":false},"User:user:1387388":{"__typename":"User","uid":1387388,"login":"abrilurena","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/dS0xMzg3Mzg4LTM3MDg4OGk0NzRCRjE5MDhDQkM4RjdF"},"id":"user:1387388"},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTA0NTAwLTU2NzY0M2k5ODVBQ0Q5RUY0RDNDMDI1?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTA0NTAwLTU2NzY0M2k5ODVBQ0Q5RUY0RDNDMDI1?revision=5","title":"carlottacaste_1-1710502631069.png","associationType":"TEASER","width":975,"height":264,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTA0NTAwLTU2NzY2NWk5MjNBODcxMkY5QkY4RjEw?revision=5\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTA0NTAwLTU2NzY2NWk5MjNBODcxMkY5QkY4RjEw?revision=5","title":"carlottacaste_1-1710502631069.png","associationType":"BODY","width":975,"height":264,"altText":null},"BlogTopicMessage:message:4104500":{"__typename":"BlogTopicMessage","subject":"Β‘Γnete al Microsoft Learn AI Skills Challenge y aprende con las charlas de Learn Live!","conversation":{"__ref":"Conversation:conversation:4104500"},"id":"message:4104500","revisionNum":5,"uid":4104500,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1387388"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Β‘PrepΓ‘rate para las certificaciones de Inteligencia Artificial, todo mientras aprendes en vivo! y ΓΊnete al Microsoft Learn AI Skills Challenge para obtener la posibilidad de conseguir un voucher para presentar un examen de certificaciΓ³n, descubre mΓ‘s sobre cΓ³mo puedes lograrlo en este blog. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":2697},"postTime":"2024-04-11T00:00:00.069-07:00","lastPublishTime":"2024-04-11T06:54:31.573-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Todas las semanas desde el 20 de marzo al 18 abril acompÑñanos en este viaje emocionante de aprendizaje con nuestra serie interactiva en vivo en la que estarΓ‘s en compaΓ±Γa de expertos y programadores de todo el mundo. Aprende con nuestros mΓ³dulos de Microsoft Learn en tiempo real, adquiriendo no solo conocimientos, sino tambiΓ©n badges (insignias digitales). Β‘PrepΓ‘rate para las certificaciones, todo mientras aprendes en vivo! \n \n RegΓstrate ahora en: https://aka.ms/AISkillsChallenge para una experiencia de autoaprendizaje y obtener la posibilidad de presentar gratis un examen de certificaciΓ³n de Microsoft (lΓmite de uno por cliente, se aplican tΓ©rminos y condiciones). \n \n Γnete a esta serie de charlas en vivo en https://aka.ms/ai-skills-challenge-learn-live para obtener mΓ‘s conocimientos sobre Inteligencia Artificial y otras Γ‘reas de interΓ©s de la mano de expertos. Si te perdiste alguna charla, recuerda que las puedes ver en nuestro canal de YouTube. \n \n Esta serie estΓ‘ enfocada en el revolucionario mundo de la IA generativa y su aplicaciΓ³n en diversos entornos empresariales. Es una oportunidad para: \n \n los emprendedores de IA que crean estrategias comerciales \n los cientΓficos de datos que profundizan en los grandes modelos de lenguaje (LLM) \n los desarrolladores de software que diseΓ±an soluciones de generaciΓ³n aumentada de recuperaciΓ³n (RAG). \n \n \n Primeros pasos con la IA generativa \n \n Tendremos 9 charlas y talleres en vivo entre el 20 de marzo y el 18 de abril para aprender mΓ‘s sobre el potencial de la IA generativa en diferentes Γ‘reas profesionales. Los Microsoft MVP, Microsoft Cloud Advocates y MLSA te guiaran durante este trayecto para que comiences tu viaje hacia la IA generativa. Puedes encontrar las sesiones: Microsoft Learn AI Skills Challenge ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"1860","kudosSumWeight":0,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTA0NTAwLTU2NzY0M2k5ODVBQ0Q5RUY0RDNDMDI1?revision=5\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuMXwyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MTA0NTAwLTU2NzY2NWk5MjNBODcxMkY5QkY4RjEw?revision=5\"}"}}],"totalCount":2,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":null,"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:4047474":{"__typename":"Conversation","id":"conversation:4047474","topic":{"__typename":"BlogTopicMessage","uid":4047474},"lastPostingActivityTime":"2024-04-07T23:19:50.341-07:00","solved":false},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MDQ3NDc0LTU0ODUzN2lDRDcxNzVBMjU5OEMyN0U0?revision=7\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MDQ3NDc0LTU0ODUzN2lDRDcxNzVBMjU5OEMyN0U0?revision=7","title":"shreyan19991580_4-1706908376677.jpeg","associationType":"TEASER","width":1377,"height":608,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MDQ3NDc0LTU0ODUzM2k0MjhGMzcwQjdENTYzQkMy?revision=7\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MDQ3NDc0LTU0ODUzM2k0MjhGMzcwQjdENTYzQkMy?revision=7","title":"shreyan19991580_0-1706908376644.png","associationType":"BODY","width":1387,"height":520,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MDQ3NDc0LTU0ODUzNGk2OTI5M0U2MTQzQkNDMURG?revision=7\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MDQ3NDc0LTU0ODUzNGk2OTI5M0U2MTQzQkNDMURG?revision=7","title":"shreyan19991580_1-1706908376651.png","associationType":"BODY","width":1920,"height":1023,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MDQ3NDc0LTU0ODUzNWk3RjYwMzlGMzA4QjA2NEZE?revision=7\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MDQ3NDc0LTU0ODUzNWk3RjYwMzlGMzA4QjA2NEZE?revision=7","title":"shreyan19991580_2-1706908376658.png","associationType":"BODY","width":1471,"height":861,"altText":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MDQ3NDc0LTU0ODUzNmlDQjk0QUI2NjRGQzQwNDdD?revision=7\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MDQ3NDc0LTU0ODUzNmlDQjk0QUI2NjRGQzQwNDdD?revision=7","title":"shreyan19991580_3-1706908376666.png","associationType":"BODY","width":1465,"height":869,"altText":null},"BlogTopicMessage:message:4047474":{"__typename":"BlogTopicMessage","subject":"An Overview of LIDA: Generate Visualizations and Infographics of Tabular Data using LLMs!","conversation":{"__ref":"Conversation:conversation:4047474"},"id":"message:4047474","revisionNum":7,"uid":4047474,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:2282848"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Large Language Models (LLMs) have demonstrated impressive capabilities on various data-related tasks, but they still have some limitations. One of them is the ability to generate effective visualizations from structured data sources such as CSV or Excel files. In this article, we will explore a new framework that addresses this challenge by combining LLMs with Granular Data. The framework is called LIDA, and it was recently open-sourced by Microsoft. LIDA is a powerful library that enhances the interaction between LLMs and Granular Data, enabling richer and more expressive data analysis and visualization. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":6565},"postTime":"2024-02-05T00:27:46.268-08:00","lastPublishTime":"2024-02-05T00:57:57.999-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Generative AI is increasing its boundaries by expanding to every field. Things which merely seemed like a fiction a few years ago are now reality, thatβs how Generative AI has proven its existence. To back this up, huge organizations around the world have been inculcating and implementing OpenAI at their firm level to increase the efficiency of work and to aid its workforce. \n \n Generative AI which was initially limited to text further moved to multimedia and today we have models like DALL-E and GPT-4 Vision which have proven their potential. \n \n All the LLMs have been showcasing their power over the data, but still there are couple of things which LLMs were not able to do to their fullest. Tasks like visualizations needed some improvement. Today we will be looking into such a framework which was again open sourced recently by Microsoft. This is none other than LIDA. LIDA is a powerful library which augments the Granular Data like CSV, Excel, etc. and the LLMs together. \n \n LIDA is a library designed for creating data visualizations and faithful infographics. It is agnostic to grammar, meaning it can seamlessly integrate with any programming language and various visualization libraries such as matplotlib, seaborn, Altair, d3, etc. Furthermore, LIDA is compatible with multiple large language model providers like OpenAI, Azure OpenAI Services, PaLM, Cohere, and Hugging face. \n \n LIDA comprises of 4 modules β \n \n 1.SUMMARIZER: This converts data into a rich but compact natural language summary \n 2.GOAL EXPLORER: This enumerates visualization goals given the data. \n 3.VISGENERATOR: This generates, refines, executes and filters visualization code \n 4.INFOGRAPHER: This is the module that yields data-faithful stylized graphics using IGMs. \n \n LIDA provides a python API, and a hybrid user interface (direct manipulation and multilingual natural language) for interactive chart, infographics and data story generation. \n \n LIDA can be installed using a simple command in python,( Use a python terminal/VS Code to run this command) \n \n pip install lida \n \n \n \n \n After collecting all the packages, LIDA is now ready on your local machine!! \n \n Note: For LIDA to get properly installed in local machine, the python version should be 3.10 or higher (preferably, use Conda). Install the library via pip. \n Once this installation is done, setup the API key, \n \n \n export OPENAI_API_KEY=<your key> \n \n Or If using Azure OpenAI Services \n \n export AZURE_OPENAI_API_KEY=<your key>β \n \n \n LIDA comes with an optional bundled UI and web API which can be explored using the following command, \n \n \n lida ui --port=8080 --docs \n \n \n Note: If you are not able to set your API key in the .env file, then follow the following steps: \n \n Launch βControl Panelβ Γ βSystem and Securityβ \n βSystemβ \n βAdvanced system settingsβ \n Switch to βAdvancedβ tab \n βEnvironment variablesβ \n Choose βUser Variableβ (so that only you are able to access the keys and not any other accounts) \n To add a new environment variable: Choose βNewβ \n Enter the variable name βOPENAI_API_KEYβ and the actual API string then save it. \n \n \n Upon successful execution, we can now see a webpage. \n \n \n There is a section named βDemoβ on this webpage. This is like a playground of LIDA. Upload any .csv or .json which needs to be visualized and the model which needs to be used. One can also select the library needed for visualization. \n For demonstration purposes I have used the βstocks.csvβ file which is already available on the webpage and following are the results, \n \n \n \n One can also Refine, Get explanation , Evaluate and Get some recommendations from LIDA. \n LIDA treats visualizations as code and provides a clean API for generating, executing, editing, explaining, evaluating and repairing visualization code. \n \n Data Summarization \n Goal Generation \n Visualization Generation \n Visualization Editing \n Visualization Explanation \n Visualization Evaluation and Repair \n Visualization Recommendation \n Infographic Generation \n \n System Architecture for LIDA is as follows: \n \n \n \n LIDA: Automatic Generation of Grammar Agnostic Visualizations and Infographics with Large Language Models from Victor Dibia on Vimeo. \n \n In conclusion, LIDA is a great tool which will enable Data Enthusiasts to explore data in a easier way using the power of Generative AI! 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GitHub y Microsoft acaban de anunciar una nueva iniciativa para ayudarte a impulsar tu carrera en tecnologΓa mediante el lanzamiento de la serie de charlas y talleres en vivo βGitHub Foundationsβ para ayudarte a prepΓ‘rate para esta certificaciΓ³n. Desde el 26 de marzo hasta el 16 de abril, comienza y crece tu carrera en tecnologΓa al comprender los temas bΓ‘sicos y fundamentales en GitHub. AprenderΓ‘s a como colaborar en un proyecto y con equipos para aumentar tu conocimiento mediante el uso de diferentes herramientas como GitHub Copilot, GitHub Codespaces y mΓ‘s. \n \n Β‘Comienza a trabajar en proyectos reales utilizando diversas herramientas de GitHub y mucho mΓ‘s! ","introduction":"","metrics":{"__typename":"MessageMetrics","views":5110},"postTime":"2024-03-19T11:03:11.588-07:00","lastPublishTime":"2024-03-20T05:07:06.220-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" GitHub y Microsoft acaban de anunciar una nueva iniciativa para ayudarte a impulsar tu carrera en tecnologΓa mediante el lanzamiento de la serie de charlas y talleres en vivo βGitHub Foundationsβ para ayudarte a prepΓ‘rate para esta certificaciΓ³n. Desde el 26 de marzo hasta el 16 de abril, comienza y crece tu carrera en tecnologΓa al comprender los temas bΓ‘sicos y fundamentales en GitHub. AprenderΓ‘s a como colaborar en un proyecto y con equipos para aumentar tu conocimiento mediante el uso de diferentes herramientas como GitHub Copilot, GitHub Codespaces y mΓ‘s . Β‘Comienza a trabajar en proyectos reales utilizando diversas herramientas de GitHub y mucho mΓ‘s! \n \n Β‘RegΓstrate aquΓ y descubre como puedes obtener un voucher gratuito para esta certificaciΓ³n! \n \n \n Descubre lo esencial en 4 sesiones. Recuerda que todas estas sesiones son a partir de las 9 am (UTC-6), misma zona horaria que en Ciudad de MΓ©xico. \n \n \n \n \n Fecha \n SesiΓ³n \n \n \n \n 26 de Marzo del 2024 \n 9 AM (UTC-6) \n \n **Misma zona horaria que en Ciudad de MΓ©xico \n \n \n IntroducciΓ³n a GitHub y sus certificaciones \n Una sesiΓ³n introductoria para explorar los conceptos bΓ‘sicos de GitHub, asΓ como los conceptos fundamentales de Git con ejemplos prΓ‘cticos sobre cΓ³mo usar ambos. \n \n \n \n \n 2 de Abril 2024 \n 9 AM (UTC-6) \n \n \n IntroducciΓ³n a GitHub Codespaces \n En esta sesiΓ³n, se compartirΓ‘n los aspectos bΓ‘sicos de GitHub Codespaces y cΓ³mo empezar a usarlo. TambiΓ©n se incluirΓ‘n ejemplos prΓ‘cticos de cΓ³mo puedes incorporar Codespaces en tus diferentes proyectos, junto con sus beneficios. \n \n \n \n \n 9 de Abril del 2024 \n 9 AM (UTC-6) \n \n \n \n Descubre GitHub Copilot \n Descubre cΓ³mo usar y aprovechar al mΓ‘ximo GitHub Copilot con ejemplos sencillos y con la ayuda de pequeΓ±as tareas que puedes probar. \n \n \n \n \n \n \n 16 de Abril del 2024 \n 9 AM (UTC-6) \n \n \n \n Trabaja con un repositorio de GitHub \n Aprende a ser mΓ‘s eficaz con prΓ‘cticas de desarrollo modernas utilizando GitHub y aplicando ciclos de vida de software. Ideal para cualquier persona que le interesa descubrir tΓ©cnicas de colaboraciΓ³n en equipo para desarrollo de software. \n \n \n \n \n \n \n \n ΒΏPor quΓ© registrarme? \n AdemΓ‘s de poder tener la oportunidad de obtener un voucher gratuito para presentar esta certificaciΓ³n (regΓstrate y conoce mΓ‘s informaciΓ³n sobre esto en: https://aka.ms/GitHubFoundationsSeries), al participar en la serie \"GitHub Foundation Certification\", tendrΓ‘s los beneficios de: \n \n \n AdquirirΓ‘s habilidades esenciales para trabajar de manera efectiva en GitHub. \n Aprender de la mano de expertos a travΓ©s de ejemplos prΓ‘cticos y prΓ‘cticos. \n Desarrollar una sΓ³lida comprensiΓ³n de GitHub y los conceptos fundamentales de Git. \n Explorar herramientas como GitHub Codespaces y GitHub Copilot para mejorar tu productividad y eficiencia en proyectos de software. \n Integrar prΓ‘cticas de desarrollo modernas en tu flujo de trabajo. \n \n \n \n Comienza a prepΓ‘rate para esta certificaciΓ³n con estos recursos educativos gratuitos: https://aka.ms/learn/github-foundations \n \n Explora una colecciΓ³n de cursos oficiales disponibles en Microsoft Learn diseΓ±ados para prepararte para esta certificaciΓ³n de GitHub Foundations. DespuΓ©s de completar un curso, puedes descargar o compartir fΓ‘cilmente tu diploma. \n \n Simplemente accede a tu Perfil y has clic en la opciΓ³n \"Logros\" para ver la lista de mΓ³dulos completados - haz clic aqui para ver un mini video tutorial sobre cΓ³mo puedes hacer esto. \n \n \n ΒΏListo para el viaje? \n Β‘Aprovecha la oportunidad de fortalecer tus habilidades de GitHub y avanzar en tu carrera como programador! Β‘AcompÑñanos en la serie \"GitHub Foundations Certification\" (Fundamentos de la certificaciΓ³n de GitHub) y comienza este emocionante viaje de aprendizaje y crecimiento! \n \n PrepΓ‘rate para transformar tu forma de colaborar, desarrollar e innovar con GitHub - Β‘Registrate ahora! 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Learn AI Skills Challenge","conversation":{"__ref":"Conversation:conversation:3869868"},"id":"message:3869868","revisionNum":14,"uid":3869868,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:102838"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n Join Microsoft's AI Skills Challenge 2023 to enhance your technical expertise in Artificial Intelligence. Register now to access exclusive resources, hands-on labs, and interactive learning sessions. Boost your knowledge in generative AI, machine learning, cognitive services, natural language processing, and computer vision to stay ahead in the ever-evolving world of AI. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":33120},"postTime":"2023-07-12T00:04:00.057-07:00","lastPublishTime":"2023-07-12T00:04:00.057-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" \n Learn and develop essential AI skills with the Microsoft Learn AI Skills Challenge \n Sign up for the Microsoft Learn AI Skills Challenge and you'll get a head start on immersive and curated AI training content across Microsoft products and services, as well as four awesome AI-themed challenges. Whether you're just starting out or looking to change careers, this program will teach you the essentials of AI, Machine Learning, MLOps, and Cognitive Services. You will receive a Microsoft Learn AI Skills Challenge badge and certificate of achievement if you complete at least one of the four eligible tasks before August 14th, 2023. Refer to the official rules for more information. \n Register for the Microsoft AI Skills Challenge here: https://aka.ms/AISkillsChallengeExperiences \n \n As you go through the challenges, you'll have the opportunity to try out new experiences that are suited to your learning preferences and goals. Join your local active technical community, attend live sessions, build a strong network, and develop in-demand AI skills for today's job market. \n \n \n \n As mentioned, you'll have your choice between four awesome AI-themed challenges to review and complete in this Microsoft Learn AI Skills Challenge. The challenges include: \n \n AI Builder Challenge \n This challenge introduces you to AI Builder, teaches you how to create models, and demonstrates how to use them in Power Apps and Power Automate. You'll learn how to build topics, custom entities, and variables to capture, extract, and store data in a bot. Register here: AI Builder Challenge \n \n Cognitive Services Challenge \n Azure Cognitive Services are AI functionality building blocks that can be integrated into applications. You'll learn about provisioning, securing, and deploying cognitive services. You can use this tool to build intelligent solutions that extract semantic meaning from text and support common computer vision apps. \n \n Register here: Cognitive Services Challenge \n \n Machine Learning Challenge \n Many modern services rely on predictive machine learning models, which are at the heart of artificial intelligence. Learn how to construct and publish models in Azure Machine Learning without writing code. You'll also look at the many development tools available for interacting with the workspace. \n \n Register here: Machine Learning Challenge \n \n Machine Learning Operations (MLOps) Challenge \n DevOps principles are applied to machine learning projects in machine learning operations (MLOps). While using Python to train, store, and utilize a machine learning model, you will gain an understanding of how to incorporate fundamental concepts like source control, automation, and CI/CD to create an end-to-end MLOps solution. \n \n Register here: Machine Learning Operations (MLOps) Challenge \n \n \n With our selection of live seminars and workshops for beginners, be ready to explore the fascinating world of artificial intelligence! They will be jam-packed with advice, tactics, and hands-on activities to assist students in developing a solid foundation in AI. This is a must-attend event for anybody interested in AI, regardless of your level of expertise or goals. \n \n \n \n \n \n Livestream \n \n \n Description \n \n \n Presenter \n \n \n Registration Link \n \n \n \n Introduction to GitHub Copilot July 18th, 2023 - Noon EST \n Get ready to level up your coding skills with our upcoming live session on GitHub Copilot! We're covering everything from installing this tool to making the most of its features in your day-to-day work. Join the fun, learn something new, and let's supercharge your development toolkit together with GitHub Copilot - see you on the stream! \n Burke Holland and Gwyneth PeΓ±a-Siguenza \n Register Now \n \n \n Prompt Engineering, with GitHub Copilot & Azure OpenAI July 20th, 2023 - 11:30AM EST \n \n \n In this session, we'll take you through LLMs, Prompt engineering and generative AI tools like GitHub Copilot and ChatGPT. We'll focus on a narrative of building an e-commerce application, frontend and backend. \n \n \n Chris Noring and Korey Stegared-Pace \n Register Now \n \n \n Let's code a drone using Azure OpenAI Services July 25th, 2023 - 11:30AM EST \n \n During this livestream, we will explore the power of Azure OpenAI Services and GPT models by integrating them with a drone. Using these services, we will (try to) control the device intuitively using natural language. With GPT models' ability to answer follow-up questions, admit mistakes, challenge incorrect premises, and reject inappropriate requests, the possibilities for intuitive and seamless interaction with technology are endless. \n But that's not all - during the session, you'll get to witness live coding that will enable you to control the drone using language commands. And the best part? GPT will be generating the code based on your own words! You can ask the drone to \"fly to the end of the room\" or \"find an empty chair\", and GPT models will generate the code to make it happen. \n \n Bruno Capuano \n Register Now \n \n \n It's not just words: LLMs in Computer Vision August 1st, 2023 - 10:00AM EST \n Let's explore how LLMs enhanced Computer Vision in Azure and how you can embed image analysis and image generation capabilities into your solution. \n Carlotta Castelluccio \n Register Now \n \n \n Convert your Excel sheet into Power Platform Apps using AI August 7th, 2023 - Noon EST \n We all have one of those Excel sheet that start just as a quick thing and became way too big. In this session we will use AI to transform it into a Power App. \n Frank Boucher \n Register Now \n \n \n Let's build a PlugIn for ChatGPT and BingChat August 17th, 2023 - Noon EST \n \n \n In this workshop, we will create a plugin for ChatGPT from scratch. We will see examples in different programming languages such as Javascript, .NET, or Python. We will also explore the architecture that supports a plugin and how this model can be used for other platforms like BingChat. \n \n Bruno Capuano \n Register Now \n \n \n \n \n \n \n When does the challenge run? \n \n \n The Microsoft Learn AI Skills Challenge starts on July 17, 2023 at 4:00 PM (16:00) UTC and ends on August 14, 2023, at 4:00 PM (16:00) UTC. \n \n \n If you are participating in the \"Pitch your AI Solution\" experience, you will have 1 additional week to submit your 3-minute pitch video by August 21. Learn more \n \n \n How do I start this challenge? \n \n \n You will need to register for this challenge using your Microsoft Learn profile. Once the challenge begins, you will see the modules you will need to complete. \n \n \n If you donβt have a Microsoft Learn profile, that is okay. You can create one as you register. \n \n \n \n How does the challenge work? \n \n \n The challenge starts on July 17, 2023 at 4:00 PM (16:00) UTC and ends on August 14, 2023 at 4:00 PM (16:00) UTC. \n \n \n There are 4 challenges available to choose from. \n \n \n By completing at least one of the challenges before August 14th, you will be eligible to receive a badge and certificate of completion. You will receive the same badge and certificate irrespective of the number of challenges completed. \n \n \n \n Still have questions? \n \n See the contest official rules for more details. \n 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Resources for Startups, Students and Developers at GitHub Universe 2023","conversation":{"__ref":"Conversation:conversation:3968973"},"id":"message:3968973","revisionNum":19,"uid":3968973,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:102838"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n \n Explore the dynamic offerings at GitHub Universe 2023, via a collaboration between Microsoft and GitHub, designed to empower developers, students, and startups. Delve into resources and workshops covering AI programming, application security, and developer experience enhancements. Uncover an array of resources shared during the event, including cloud skills challenges preparing for GitHub Certification, AI applications, and GitHub Copilot for seamless coding. Microsoft extends support to startups through the Founders Hub, provides Azure credits for student experimentation, and offers GitHub Codespaces for Startups and students can benefit from diverse open-source curricula spanning AI, data science, machine learning, web development, and IoT. Access these invaluable resources conveniently through provided QR codes, ensuring a comprehensive and enriching learning experience for all attendees. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":12803},"postTime":"2023-11-08T03:01:00.057-08:00","lastPublishTime":"2023-11-09T01:22:37.852-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" GitHub Universe 2023 starts today focusing on enabling developers, enterprise leaders, and security professionals through two days of expert sessions, workshops, and networking opportunities. Opportunities to learn about harnessing AI as a paired programmer, applying AI to application security, and enhancing the overall developer experience will be discussed and shared throughout the conference. The following are resources of note that Microsoft and GitHub have collaborated on that might be of interest to those adopting services announced at this year's event. \n Microsoft / GitHub Services \n \n \n \n GitHub Universe Cloud Skills Challenge A great precursor to prepare for the GitHub's Certification offering, the GitHub Universe Cloud Skills Challenge offers participants a great start on learning how to harness Copilot as a AI-paired programmer. Microsoft will also issue a certificate at the end of the challenge if you complete all the Microsoft Learn modules included. β \n https://aka.ms/challenge/github \n lenge QR Code \n \n \n Microsoft Founders Hub Microsoft for Startups Founders Hub helps startups radically accelerate innovation by providing access to industry-leading AI services, expert guidance, and the essential technology needed to build a future-proofed startup. \n https://aka.ms/MSStartupFoundersHub \n \n \n \n Azure for Students This program provides eligible students with $100 in Azure service credits to be used over the course of a year. Azure service credits can be used to experiment with and learn about Azure products and services. Signing up does not require a credit card, but you must verify your academic status using your organization's email address. \n https://aka.ms/azure4student \n \n \n \n GitHub Codespaces Teachers can take advantage of GitHub Codespaces by using it with GitHub Classroom. GitHub Codespaces can provide students with cloud-based development environments that require no local setup. Verified teachers can also get a free monthly allowance of GitHub Codespaces hours to use in GitHub Classroom. \n https://aka.ms/GitHubCodespacesEDU \n \n \n \n GitHub Copilot GitHub Copilot is an AI pair programmer that can help students learn new languages and frameworks by providing examples and documentation. It draws context from comments and code to suggest individual lines and whole functions instantly. GitHub Copilot is free to use for verified students and teachers and can be used with Visual Studio Code. \n https://aka.ms/Copilot4Students \n \n \n \n Microsoft Power Platform Microsoft Power Platform is a set of tools that enable users to create apps, automate processes, analyze data, and build virtual agents with low-to-no-code. \n https://aka.ms/PowerPlatEDU \n \n \n \n \n \n Open-Source Curriculum \n \n \n \n Generative AI for Beginners - *NEW* Learn the fundamentals of building Generative AI applications with our 12-lesson comprehensive course by Microsoft Cloud Advocates. Each lesson covers a key aspect of Generative AI principles and application development. Throughout this course, we will be building our own Generative AI startup so you can get an understanding of what it takes to launch your ideas. \n https://aka.ms/genai-beginners \n \n \n \n AI for Beginners This 12-week curriculum teaches the fundamentals of Artificial Intelligence (AI). Explore various approaches, including neural networks and deep learning, with practical implementation in popular frameworks like TensorFlow and PyTorch. In addition, you will learn about AI applications in image and text processing, as well as the lesser-known techniques of genetic algorithms and multi-agent systems. \n https://aka.ms/ai-beginners \n \n \n \n Data Science for Beginners This 12-week curriculum teaches the fundamentals of Data Science and covers basic principles of data science, including ethical concepts, data preparation, different ways of working with data, data visualization, data analysis, real-world use cases of data science, and more. \n https://aka.ms/datascience-beginners \n \n \n \n Machine Learning for Beginners This 12-week curriculum teaches classic machine learning concepts, using primarily Scikit-learn as a library and avoiding deep learning. Pairs well with the AI for Beginners and Data Science for Beginners curriculum. \n https://aka.ms/ml-beginners \n \n \n \n Web Dev for Beginners This 12-week curriculum teaches JavaScript, CSS, and HTML basics. The 24 lessons include pre- and post-lesson quizzes, extensive written instructions, solutions, assignments, and more. Our project-based curriculum builds hands-on skills. Project-based learning improves skills and retention. \n https://aka.ms/webdev-beginners \n \n \n \n IoT for Beginners This 12-week curriculum covers the journey of food from farm to table. This includes farming, logistics, manufacturing, retail and consumer - all popular industry areas for IoT devices. \n https://aka.ms/iot-beginners \n \n \n \n \n \n GitHub Codespace Templates \n \n \n \n Introduction to JavaScript This Codespaces template teaches JavaScript use to create a personal portfolio frontend web application using the React framework. No setup time needed from you or your students, allowing you to focus on the content and lessons. \n https://aka.ms/JSTeachingTemplate \n \n \n \n Introduction to Python This template repository quickly creates a normalized environment to teach or learn Python. This template uses Codespaces, a development environment that's hosted in the cloud with Visual Studio Code, a powerful text editor. \n https://aka.ms/PyTeachingTemplate \n \n \n \n Intro to .NET \n Extend and use for your Web Development lessons in minutes. This .NET Codespaces template provides you a normalized environment for you to build your class on. \n \n https://aka.ms/dotNetTeachingTemplate \n \n \n \n \n \n We'll be reviewing this list of resources to update as needed. Feel free to comment below regarding any resource you'd like to see added. \n 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Ways to Make Open Source Contributions to Microsoft","conversation":{"__ref":"Conversation:conversation:3820868"},"id":"message:3820868","revisionNum":10,"uid":3820868,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1784638"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Dive into open-source, level up with Microsoft, and shape the tech industry! ","introduction":"","metrics":{"__typename":"MessageMetrics","views":5346},"postTime":"2023-05-16T01:41:46.926-07:00","lastPublishTime":"2023-11-01T03:44:11.553-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Hey there! I am Kiran Amin Panjwani, a Beta Microsoft Learn Student Ambassador from DHA Suffa University in Karachi, Pakistan. As an aspiring web developer and community builder, I am passionate about web development, open-source contributions, and helping my peers with my knowledge. In this blog post, I will share my experience and knowledge about how you can contribute to Microsoft repositories like Microsoft's Learn Docs and Academic content. \n \n Microsoft technologies such as Azure, Microsoft 365, GitHub, and Microsoft repositories have always fascinated me. However, my enthusiasm extends beyond just using these technologies. I am passionate about open-source development, a thriving community that fosters collaboration, innovation, and inclusivity. Open-source development is a place where developers, designers, and tech enthusiasts worldwide work together on projects and software that are free and open to everyone. Anyone who is passionate about technology is welcome to contribute to this community, whether by fixing bugs, adding new features, or improving documentation. The opportunities for growth and learning in this community are vast, and contributing to open-source projects can help individuals build valuable experience, develop their skills, and establish a professional network. What's more, the high-quality software produced by this community benefits society as a whole. Working alongside like-minded individuals dedicated to making technology accessible and useful to everyone is an incredible opportunity that the open-source community provides. \n \n The most popular platform used for contributions worldwide is GitHub. GitHub is a web-based platform that provides tools for developers to collaborate on projects, share code, and manage versions of their codebase, and it has become an essential tool for individuals and organizations of all sizes. GitHub has over 56 million registered users and hosts over 100 million repositories. Users can create and manage repositories, which are a storage space for code that can be accessed by multiple users, with just a few clicks, making it an ideal tool for students looking to collaborate on projects or accelerate their careers by contributing to open-source software. GitHub also provides extensive documentation and tutorials to help users get started, making it accessible even to those with limited programming experience. Additionally, GitHub enables users to track changes made to the codebase over time, making it easier to identify and address any issues or bugs that arise. If you do not have a GitHub account yet, you are encouraged to sign up today. \n If you're passionate about technology, eager to learn, and looking to make a valuable contribution, be sure to check out ππ’ππ«π¨π¬π¨ππ'π¬ ππππππ¦π’π ππ¨π§πππ§π πππ©π¨π¬π’ππ¨π«π². \n This platform provides comprehensive access to technical and academic content, including learning modules, projects, and documentation that cover various topics related to Microsoft technologies. By exploring the repository, you can enhance your skills, knowledge, and stay updated with the latest trends in the industry. Additionally, the Microsoft Academic Content Repository is a collaborative space where everyone interested in technology can contribute their own projects and documentation. By adding your own work to the repository, you can help others learn and grow, while also improving your own skills and building your portfolio. And if you want to see an example of a project in action, you can check out my Tracker Expense project on the repository by clicking on the link below: (https://github.com/microsoft/AcademicContent/blob/main/league-content/web-mobile.md). \n \n \n This project was designed to help users understand and implement the basic functions of JavaScript, along with the deployment of Azure Static Web Apps. It also teaches users how to use local storage to save data. By adding this project to the repository, I helped newcomers understand front-end development and the implementation of Azure Static Web Apps. So don't hesitate to explore the Microsoft Academic Content Repository to enhance your skills and learn something new. \n \n In addition to providing access to technical and academic content, the Microsoft Learn Student Program offers students a unique opportunity to contribute to their learning modules on a broader scale. As an MLSA, you can participate in the Bug Bash program, a Microsoft Learn Student Ambassador initiative that helps identify and report bugs or issues related to Microsoft's products and services. The program involves a group of students collaborating to identify and report bugs in specific products or services, such as Microsoft Teams or Windows. By doing so, students help Microsoft improve the quality of its products, services, and learning modules by identifying and addressing/reporting issues on GitHub. \n Participating in the Bug Bash program is an excellent way for students to learn about software development, testing, and bug reporting while interacting with other students and professionals in the technology industry. It provides them with valuable skills and experience that can help them in their careers. The program even offers rewards to the winners who find and report the most bugs, incentivizing students to get involved and make a difference. If you're interested in joining the program, you can visit the official website to learn how to get started or check out the Readme.md provided in their GitHub repository: \n \n \n \n Additionally, Microsoft offers various learning modules that you can access to improve your skills and learn new technologies simultaneously. These modules cover a wide range of topics and are designed to help you develop the skills and knowledge you need to succeed in the technology industry. Whether you're just starting or looking to advance your career, these modules can help you reach your goals. \n \n \n \n As an MLSA, I had the opportunity to participate in the Bug Bash program and contribute to the improvement of Microsoft's learning modules. During this time, I identified and reported two bugs in the Microsoft Azure Static Web Apps documentation. If you're interested in seeing the issues I found, you can check them out through these links: [https://github.com/microsoft/studentambassadors/issues/27], [https://github.com/microsoft/studentambassadors/issues/21]. \n \n If you're curious about other issues that students have found and reported, you can explore them through this link: [https://github.com/microsoft/studentambassadors/issues]. It's always interesting to see the variety of bugs that have been identified, as well as the creative solutions that have been suggested to fix them. Through the Bug Bash program, students have the chance to make a real impact and contribute to the development of cutting-edge technology. \n In addition to Bug Bash Program and Microsoft's Academic Content Repository, there are a few other exciting resources that students can take advantage of to further their knowledge and skills in the world of technology. One such resource is the Open-Source Show on Microsoft Learn. This show is designed to provide students with insights into the world of open-source technology and how it is shaping the future of software development. The show features expert guests who share their experiences and best practices for building open-source software solutions. By tuning in, students can gain valuable insights and learn new skills that they can apply in their own projects. \n Another resource that can benefit students is Open-Source Thursdays on Microsoft Reactor. This program offers students the opportunity to collaborate with other like-minded individuals on open-source projects. Each Thursday, students can join the Reactor's virtual space and work on different open-source projects under the guidance of expert mentors. This program provides students with a supportive environment to learn new skills, build their portfolios, and connect with other professionals in the tech industry. By working on open-source projects, students can gain practical experience, hone their skills, and contribute to the community. \n \n In conclusion, contributing to open-source projects is an excellent way for students to learn and grow as developers, while also making technology accessible and useful to everyone. It provides them with a unique perspective on the industry and the various technologies used in software development, enhancing their understanding of the software development lifecycle and helping them build a diverse skill set that is highly sought after in the tech industry. \n \n Contributing to Microsoft's open-source projects can be an especially rewarding experience that boosts confidence and gives back to the community. Microsoft plays an important role in providing numerous opportunities to students to learn from experts and peers. Microsoft repositories, such as the Academic Content Repository, and programs like \"Bug Bash,\" \"Open-Source Thursdays,\" and \"Open-Source Show on Microsoft Learn\" are excellent opportunities for students to gain invaluable experience and the skills required to understand the workings of big organizations and their frameworks. By collaborating with like-minded individuals and working together to make a difference, students can establish a professional network and create a meaningful impact on society. \n \n Why not leverage these opportunities to jumpstart your tech career and create a meaningful impact by seizing them and exploring where your passion for technology can lead you? \n 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