Stanford University · YouTube
AI Luminaries
A curated collection of videos featuring top experts in artificial intelligence.
In 44 episodes, Adriene Hill teaches you Statistics! This course is based on the 2018 AP Statistics curriculum and introduces everything from basic descriptive statistics to data collection to hot topics in data analysis like Big Data and neural networks. By the end of the course, you will be able to:
*Identify questions that can be answered using statistics
*Describe patterns, trends, associations, and relationships in data both numerically and graphically
*Justify a conclusion using evidence from data, definitions, or statistical inference
*Apply statistical models to make inferences and predictions from data sets
*Understand how statistics are used broadly in the world and interpret their meaning, like in newspapers or scientific studies
Some points apply to every course of this kind; see how we rank.
Crash Course is in Tier 3: good universities, respected companies, nonprofits and well-known teachers of our institution ranking (78/100).
Stanford University · YouTube
A curated collection of videos featuring top experts in artificial intelligence.
Stanford University · YouTube
-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…
Stanford University · YouTube
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 University · YouTube
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…
Massachusetts Institute of Technology · YouTube
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…
Stanford University · YouTube
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.