Data Science
85 TopicsAI-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.39KViews11likes3CommentsIntroducing Data Science for Beginners
Our team of Azure Cloud Advocates, Program Managers, and Student Ambassadors are pleased to bring a new addition to the For Beginners Curriculum series: Data Science for Beginners. Data Science for Beginners is a free, MIT-licensed open-source curriculum of 20 lessons that focus on the foundations of Data Science and requires no prior knowledge to get started.15KViews6likes2CommentsDiscover the Future of Data Engineering with Microsoft Fabric for Technical Students & Entrepreneurs
Microsoft Fabric is an all-in-one analytics solution for enterprises that covers everything from data movement to data science, Real-Time Analytics, and business intelligence. It offers a comprehensive suite of services, including data lake, data engineering, and data integration, all in one place. This makes it an ideal platform for technical students and entrepreneurial developers looking to streamline their data engineering and analytics workflows.6.2KViews4likes1CommentCopilot Explains - Error troubleshooting in Jupyter Notebooks
Data scientists and AI engineers love to work with Jupyter Notebooks because they make so much easier to look at the result of each and every data exploration step or data modeling experiment and take decisions accordingly. However, Jupyter notebooks are not immune to errors and sometimes understanding error messages - in particular if you aren’t a native English speaker or you are a beginner - and troubleshooting code might be painful and time consuming.5.2KViews3likes1Comment