9 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
Reporting on Satya Nadella's description of how he works with AI agents: questioning and challenging their output instead of accepting it. A concrete example of how a major executive says he uses AI day to day.
Microsoft's corporate sustainability hub, covering its carbon-negative, water-positive and zero-waste commitments, annual environmental sustainability reports, and progress data — relevant context for the footprint of AI data centers.
Microsoft's community skilling programme that partners with local community colleges and vocational schools to train people for entry-level datacenter and digital-infrastructure jobs. The five parts are aligned curriculum, a hands-on datacenter lab, mentoring from Microsoft datacenter staff, work experience at a Microsoft datacenter, and scholarships or financial grants. It runs in cohorts through named partner schools rather than as an online course you sign up for.
Why I recommend it: The honest version: this page is the program overview, not an application. The training is delivered by a local partner school, so start at the locations list and go to the school nearest you for dates, entry requirements and what the school itself charges — Microsoft's scholarships cover tuition, fees and certification exams only for students who qualify, so ask the school in writing what you would owe if you don't get one. Microsoft says more than 12,500 people have enrolled since 2018 across at least 14 countries; treat any jobs or salary figures the program quotes as its own marketing, not a promise of a Microsoft job.
Site of the DeepMind co-founder now running Microsoft AI, with his writing on AI and containment.
From the site: Personal site of Mustafa Suleyman, AI pioneer and author.
Why I recommend it: He runs a major AI business and writes about restraining AI. Both things are true at once, which is worth holding in mind while reading.
Microsoft's open-source toolkit for red-teaming AI systems: automated attack prompts, scoring of the responses, and repeatable runs. Free.
From the site: The Python Risk Identification Tool for generative AI (PyRIT) is an open source framework built to empower security professionals and engineers to proactively identify risks in generative AI system...
Why I recommend it: Built by the team that red-teams Microsoft's own AI products, and released as-is. Best paired with a written idea of what you are testing for.
Draft code of conduct for MAI models, outlining intended behaviors, values, limits and accountability principles. Open for public consultation as Microsoft AI develops its Humanist AI approach.
Why I recommend it: Read this if you want to understand how a major AI lab is framing responsible model behavior, and to form your own view before the consultation closes.
21 structured lessons on prompt engineering and building generative AI applications, with practical exercises in Python and TypeScript.
Why I recommend it: The best free course for actually building something. Work one lesson at a time and keep the code you write — that is your proof of skill.
Free learning paths for Microsoft 365, Azure, Power Platform, and Copilot, with certification prep.
Why I recommend it: If your target roles run on Microsoft tools, this is the official free path and it lines up with the paid exams.
A detailed walkthrough of Microsoft LEAP: eligibility, the application and essay stages, cohort timelines, tracks offered, and what the 16 weeks actually involve.
In plain terms: This guide explains the Microsoft LEAP program, a paid returnship for people re-entering tech after a career break. You can check eligibility rules, learn the hiring timeline, and use interview prep frameworks to strengthen your application.
Why I recommend it: Read this before you touch the LEAP application. It saves you from the common mistakes in the essay stage.
