Watch online lectures from Microsoft’s computer scientists, learn in-depth views and perspectives from Microsoft researchers, and keep up with ongoing conversations at the cutting edge of research. View thousands of publications, videos, datasets, blogs, webinars, and tutorials on intelligence, systems, theory, and other sciences. Here are some topical views into this vast database of cool research resources.
Learn the basics of data science in this course produced in partnership with the University of California, Berkeley. It combines three perspectives valuable for all data science learners: internal thinking, computational thinking, and real-word relevance.
Earn certifications that show you are keeping pace with today’s technical roles and requirements. Select out of 9 job roles to discover their certification paths. All certifications present a free learning path to master core concepts at your speed and on your schedule.
Create learning environments that empower students to be independent and creative learners; build skills in reading, language, and STEM; and prepare them for their futures.
Learn how open data can generate more value and better outcomes; access tools and resources to advance data collaboration, explore projects using over 30 open data repositories and data sharing models for societal benefit, and find links to resources that support open data sharing.
Explore a free public web search engine powered by advances in machine learning, semantic inference, and knowledge discovery to search through over 250 million academic publications and literature on over 700,000 topics from more than 48,000 journals through Microsoft Academic.
Explore an open source version of the Microsoft Research open data repository. The code can be used to instantiate a highly customizable cloud based data repository to host and share datasets with flexible licensing on infrastructure with a high level of security and privacy.
Datasheets for Datasets proposes a framework for every dataset to be accompanied with a datasheet documenting its motivation, composition, collection process, recommended uses, and so on to facilitate communication between dataset creators and consumers.