AI-900: Microsoft Azure AI Fundamentals Study Guide
This comprehensive study guide provides a thorough overview of the topics covered in the Microsoft Azure AI Fundamentals (AI-900) exam, including Artificial Intelligence workloads, fundamental principles of machine learning, computer vision and natural language processing workloads. Learn about the exam's intended audience, how to earn the certification, and the skills measured as of April 2022. Discover the important considerations for responsible AI, the capabilities of Azure Machine Learning Studio and more. Get ready to demonstrate your knowledge of AI and ML concepts and related Microsoft Azure services with this helpful study guide.How to Build an AI-Powered Developer Newsletter with Power Platform and ChatGPT3
Build a developer newsletter with Power Platform and ChatGPT3 to help developers stay up to date with the latest trends in technology. This solution will do the heavy lifting by taking advantage of the power of ChatGPT3 and Power Platform. You can generate a newsletter by following the steps outlined in this guide such as signing up for the OpenAI API, creating an adaptive card, and building a solution in Power Automate. Once the solution is established, you can run it and adjust the trigger to get the desired results. Use ChatGPT3 to generate a newsletter from the text input from Teams, and use Power Automate to send an email to the desired recipients.120 Days Study Plan to Become an AI-Focused Full-Stack Software Engineer
Hello there, my name is Oumaima, and I am an MLSA student ambassador from Morocco, studying at the University Of The People. Welcome to the first step in my exciting, unpredictable journey, one I’ve chosen to embark on with you! For the past three years, I’ve watched the AI industry evolve dramatically. Generative AI has shifted from a fascinating experiment to an integral part of our everyday lives, whether at school, work, or even in our personal routines. In fact, my ChatGPT app is now my go-to therapist, lawyer, and all-around advisor! As a software engineering student for over three years, I’ve seen the growth of generative AI up close. But this shift didn’t just inspire me; it made me realize that I don’t want to remain only a consumer of this technology. I want to contribute to it! Seeing AI’s ability to mimic human thought, draw connections from vast amounts of information, and deliver impressive results sparked something in me. It showed me that the best way to break into AI might just be to use AI itself as my guide. That’s when the idea came to ask ChatGPT O1-preview for a personalized study plan, crafted uniquely for me. It takes into account my available time, coding background, learning preferences, mental health, and energy. Here’s how my journey began with a simple prompt: I want to become an AI-focused full-stack software engineer and have 120 days to dedicate to this goal. Please create a detailed 120-day study plan tailored for me, dedicating 3-4 hours daily. The study plan should: - Cover all essential topics including programming foundations, data structures and algorithms (DS&A), mathematics for AI, machine learning fundamentals, deep learning, advanced AI topics, integrating AI into applications, web development basics for AI integration, advanced web development, full-stack project development, scripting, DevOps, and career development. - Include weekly breakdowns and daily tasks. - Provide recommended resources for each topic (e.g., online courses, tutorials, documentation). - Suggest hands-on projects or exercises to apply the concepts learned. - Incorporate tips for success, such as active engagement, seeking feedback, balancing depth and breadth, and maintaining well-being. - Emphasize developing all the skills that will make me an irreplaceable software developer, including scripting and DevOps skills. - Conclude with a summary and final advice. Please ensure the plan is structured, comprehensive, and practical for someone balancing work and study. Then it generated the following plan, that I tried to follow by using Microsoft Learn learning paths that offer in depth trainings on each topic I got: Days 1–25: Programming Foundations & Data Structures and Algorithms (DS&A) Microsoft Learn path suggestion: Python for beginners Days 26–50: Mathematics for AI & Machine Learning Fundamentals Microsoft Learn path suggestion: Introduction to machine learning Days 51–80: Deep Learning & Advanced AI Topics Microsoft Learn path suggestion: Train and evaluate deep learning models Days 81–100: Integrating AI into Applications Microsoft Learn path suggestion: Microsoft Azure AI Fundamentals: Generative AI Days 101–115: Advanced Web Development & Full-Stack Project Development Microsoft Learn path suggestion: Build an AI web app by using Python and Flask Days 116–120: Portfolio Projects and Industry Trends. Not going to lie, the roadmap turned out to be even more exciting than I’d expected! When I asked for it, I specified that it should guide me through developing problem-solving skills directly tied to full-stack development. I wanted a path that not only sharpens my abilities but also allows me to build interesting, hands-on applications where I can see the results of what I’m learning. And now, my friends, the journey has officially begun! I’ll be following the roadmap closely, documenting my weekly progress to learn AI, noting the challenges, and celebrating the accomplishments. The goal is to see if artificial intelligence can really help create a customized study plan that aligns with my personal goals, circumstances, and unique learning rhythm. So, stay tuned — this is only the beginning! See you in my first step with DSA!Mastering Azure OpenAI Services: A Comprehensive Learning Path for Aspiring AI Engineers
Are you a computer science student looking to delve into the world of Azure OpenAI Services? Look no further! In this Microsoft Learning Pathway, "Develop Generative AI solutions with Azure OpenAI Service," you'll embark on an exciting journey to harness the power of OpenAI's vast language models like ChatGPT, GPT, Codex, and Embeddings. These models are pivotal for creating innovative Natural Language Processing (NLP) solutions that can comprehend, converse, and generate content.Azure OpenAI Services in teaching and education
With the advent of Large language models(LLMs) like GPT-3, we see a transformation in education. In this article, I present my views on the future of education considering these developments. The views presented here are based on my teaching - but are a personal perspective. Today, there is a lot of excitement and speculation about GPT-3, and it is natural to ask how intelligent GPT-3 is and whether it approaches human-level intelligence. But in many ways, that's the wrong question to ask. Instead, exploring the idea of how we can build ChatGPT-like functionality using our own data is more interesting. When framed this way, we focus on the pragmatic and ignore the esoteric. If the industry adopts the 'co-pilot first approach.', educators must follow this trend to keep up with the new job roles. This will need a complete rethinking of many of the current ideas on education and the adoption of some new ideas that I proposed in this article. The conversation changes from: 'chatGPT is used for exam cheating or not' to: How can I empower my students to take up jobs of the future if the co-pilot first mode of work becomes a default?'
