AI Luminaries
A curated collection of videos featuring top experts in artificial intelligence.
Microsoft Applied Skills via Microsoft Learn Guided project
Microsoft Applied Skills: Resolve GitHub issues by using GitHub Copilot
Overview
To earn this Microsoft Applied Skills credential, learners demonstrate the ability to resolve GitHub Issues by using GitHub Copilot. Candidates for this credential should have a solid understanding of working with GitHub Issues and GitHub Copilot in Visual Studio Code. They should also have experie…
Skills you'll practise
Advantages and disadvantages
Advantages
- Free, official and kept up to date by Microsoft.
- Free sandbox environments for many Azure exercises, no credit card needed.
- Counts toward Microsoft certification exams (AZ-900, AI-900, PL-300…).
- A free, verified credential for passing a real hands-on lab: good proof on a resume.
- From Microsoft, a well-regarded name.
- Free certificate when you finish.
- Completely free.
- Self-paced: start any time.
Disadvantages
- Mostly reading, not video.
- Focused on Microsoft products.
- The assessment is hard without prior practice.
Some points apply to every course of this kind; see how we rank.
Free, with a free credential
- Free: Sign in with any Microsoft account.
- Credential: Pass the lab assessment to earn a free Applied Skills credential for LinkedIn and your resume.
Microsoft is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (86/100).
Similar courses
Generative AI Program
-Learn more and enroll in the program: https://online.stanford.edu/programs/generative-ai-technology-business-and-society-program Recent advancements in generative AI are reshaping industries, pushing technological boundaries, and revolutionizing creative processes. In this fast-changing landscape…
Artificial Intelligence
For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai Delve into the exciting world of Artificial Intelligence with insights and research from the world's top experts. This playlist offers a comprehensive journey, from foundational machine learning con…
Stanford CS229: Machine Learning led by Andrew Ng | Autumn 2018
Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (cluster…
MIT 6.034 Artificial Intelligence, Fall 2010
View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In these lectures, Prof. Patrick Winston introduces the 6.034 material from a conceptual, big-picture perspective. Topics include reasoning, search, constraints, learning, representations, architectures, and probabili…
Large Language Models (LLMs)
Explore the cutting-edge realm of Large Language Models (LLMs) with this expertly curated YouTube playlist. Featuring insights from industry leaders, educational content, and in-depth discussions, this selection highlights the latest advancements in LLM technology.