AI in Education

1

Fireside Chat with Sal Khan and Dr. Amy Alzina

00:00 - Welcome: Putting students and teachers first 05:30 - Why we started Khan Academy Districts 12:15 - How AI helps teachers spend more time with students 20:45 - Lessons from the classroom: Dr. Alzina’s experience 32:10 - Keeping student data safe and secure 41:25 - Making the move to personalized learning in your schools 52:40 - Q&A: Addressing the real questions from district leaders As a leader, you know that "innovation" only works if it actually helps a teacher on a Tuesday morning. We’ve moved past the hype of AI to focus on human-centered support that fits into your schools’ existing goals. Watch to see how districts are using Khanmigo to give students a personal tutor and teachers a tireless assistant—all while keeping data safety and human connection at the center.

2

What happens when the model CAN'T fix it? Interview w/ software engineer Landon Gray [Podcast #213]

Today Quincy Larson interviews Landon Gray. He's a software engineer who worked at agencies for years. Then he taught himself AI assisted software development. And now he's helping other devs do the same. Landon's famous for proving that RAG pipelines can be written in Ruby and popularizing Ruby as a language for building machine learning projects. He works as an AI Engineer at a enterprise software company and runs a popular newsletter. We talk about: - How Large Language Models are just the raw fuel, and harnesses are the real engine to get things done - Why building your professional network is so helpful for finding clients and landing job interviews - Why Landon helped port Python machine learning libraries to Ruby, and why he thinks that – now that AI is just an API call away – the Ruby ecosystem is better-positioned than ever. Support for this podcast comes from the 10,113 kind folks who donate to our charity each month. Join them and support our mission at https://donate.freecodecamp.org Get a freeCodeCamp tshirt for $20 with free shipping anywhere in the US: https://shop.freecodecamp.org Links from our discussion: - Landon's Substack newsletter: https://landongray.substack.com Community news section: 1. freeCodeCamp just published a new YouTube course that will teach you beginner Front-end Development skills like HTML, CSS, and JavaScript. You can code along at home and build a variety of projects: your own interactive quiz game, a currency converter app, and even a Trello-style kanban board. Along the way you'll learn how to use APIs and local storage to extend the functionality of these bite-sized apps. (12 hour YouTube course): https://www.freecodecamp.org/news/build-19-web-dev-projects-using-html-css-javascript/ 2. Learn how to properly test your software and ensure it doesn't break when you add new features. Prolific freeCodeCamp instructor Beau Carnes teaches this course. He'll introduce you to the Testing Pyramid and show you how to balanc

3

AI You Can Trust: Turning Your Wakelet Collections into Classroom-Ready Resources!

Join us for a special session celebrating National AI Literacy Day and discover how educators can use AI responsibly and confidently in the classroom. We’ll introduce Wakelet Create, our new AI-powered feature that turns the trusted resources in your Wakelet collections into classroom-ready outputs in seconds. See how you can quickly generate lesson plans, quizzes, exit tickets, tasks, and rubric-aligned feedback - all grounded in the content you already know and trust. Register now to learn how your Wakelet collections can start working smarter for your classroom. ✨

4

AI Foundations for Absolute Beginners

Learn the basics of artificial intelligence. This course is for absolute beginners. This course was created by learnaianywhere.org and released to support the goals of National AI Literacy Day. You can learn more at https://learnaianywhere.org and download the resources used. For more on AI Literacy Day, check out ailiteracyday.org or their YouTube playlist: https://www.youtube.com/watch?v=vihMGH6aqTY&list=PLGhqQNp1xV3McvqOTfJmX2mAuuZqOKMEs ⭐️ Contents ⭐️ - 00:00 Welcome To The Course - 01:46 Prerequisite - 02:51 Symbol Key - 03:19 Lesson 1: What is AI - Objectives - 03:35 Lesson 1: What is AI - What Is AI AI or Not: https://learnaianywhere.org/courses/ai-literacy-for-everyone/ai-or-not - 05:39 Lesson 1: What is AI - How AI Can Help Us Recap Quiz: https://learnaianywhere.org/courses/ai-literacy-for-everyone/recap-quiz-1 - 07:14 Lesson 1: What is AI - Project Time - 09:06 Lesson 2: The Key Parts of Machine Learning - Objectives - 09:27 Lesson 2: The Key Parts of Machine Learning - What is Machine Learning - 12:01 Lesson 2: The Key Parts of Machine Learning - Neuropocket Tutorial - 14:39 Lesson 2: The Key Parts of Machine Learning - AI Tools Can Make Mistake Recap Quiz: https://learnaianywhere.org/courses/ai-literacy-for-everyone/recap-quiz-2 - 16:27 Lesson 2: The Key Parts of Machine Learning - Project Time - 17:20 Lesson 3: How Do Machines Train - Objectives - 18:06 Lesson 3: How Do Machines Train - The Describer Drawer Game - 19:51 Lesson 3: How Do Machines Train - The Describer Drawer Game Demonstration - 23:07 Lesson 3: How Do Machines Train - What Is An Algorithm - 25:37 Lesson 3: How Do Machines Train - The Human Learning Algorithm - 30:25 Lesson 3: How Do Machines Train - The Machine Learning Algorithm Recap Quiz: https://learnaianywhere.org/courses/ai-literacy-for-everyone/recap-quiz-3 - 38:05 Lesson 3: How Do Machines Train - Project Time - 39:07 Lesson 4: Can Machines Be Responsible - Objectives - 39:34 Lesson 4: Can Machines Be Resp

5

Deploying AI Models with Hugging Face – Hands-On Course

This tutorial is a comprehensive, end-to-end guide to the Hugging Face ecosystem, showing how modern AI moves from research ideas to real, deployed systems. Rather than focusing on a single model or task, the course presents Hugging Face as the operating system of modern AI—connecting models, datasets, libraries, demos, and deployment into one coherent, practical workflow. Source Code (GitHub): https://github.com/MOHAMMEDFAHD/Hugging-Face/tree/main/Hugging-Face-Course Hugging Face Atlas Page: https://programming-ocean.com/knowledge-hub/hugging-face-atlas.php Course developed by @programmingoceanacademy ⭐️ Chapters ⭐️ — 0:00:00 Introduction — 0:01:22 Transformers Library in Hugging Face — 2:07:45 Audio Models in Hugging Face — 2:59:08 Diffusers Library in Hugging Face — 3:56:03 Video Models in Hugging Face — 4:35:37 Gradio Library in Hugging Face — 6:18:37 Spaces and Deployment in Hugging Face ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp 🎉 Thanks to our Champion and Sponsor supporters: 👾 @omerhattapoglu1158 👾 @goddardtan 👾 @akihayashi6629 👾 @kikilogsin 👾 @anthonycampbell2148 👾 @tobymiller7790 👾 @rajibdassharma497 👾 @CloudVirtualizationEnthusiast 👾 @adilsoncarlosvianacarlos 👾 @martinmacchia1564 👾 @ulisesmoralez4160 👾 @_Oscar_ 👾 @jedi-or-sith2728 👾 @justinhual1290 -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

6

Create a Marketing Funnel with Excel + Copilot

Set-Up Info: https://media.datacamp.com/cms/set-up-info-create-a-marketing-funnel-with-excel--copilot.pdf Laura Wiedel, the Senior Director of Lifecycle & Retention at DataCamp, will walk you through building a customer marketing funnel using Excel and Copilot. You’ll learn how to measure each stage of the customer journey, use AI assistance to analyze and visualize your data, and work through a real-world case study that brings marketing analytics to life.

7

Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494

Jensen Huang is the co-founder and CEO of NVIDIA, the world's most valuable company and the engine powering the AI computing revolution. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep494-sb See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc. *Transcript:* https://lexfridman.com/jensen-huang-transcript *CONTACT LEX:* *Feedback* - give feedback to Lex: https://lexfridman.com/survey *AMA* - submit questions, videos or call-in: https://lexfridman.com/ama *Hiring* - join our team: https://lexfridman.com/hiring *Other* - other ways to get in touch: https://lexfridman.com/contact *EPISODE LINKS:* NVIDIA: https://nvidia.com NVIDIA on X: https://x.com/nvidia NVIDIA AI on X: https://x.com/NVIDIAAI NVIDIA on YouTube: https://youtube.com/@NVIDIA NVIDIA on Instagram: https://www.instagram.com/nvidia/ NVIDIA on LinkedIn: https://www.linkedin.com/company/nvidia/ NVIDIA on Facebook: https://www.facebook.com/NVIDIA/ NVIDIA on GitHub: https://github.com/NVIDIA Nemotron: https://developer.nvidia.com/nemotron *SPONSORS:* To support this podcast, check out our sponsors & get discounts: *Perplexity:* AI-powered answer engine. Go to https://lexfridman.com/s/perplexity-ep494-sb *Shopify:* Sell stuff online. Go to https://lexfridman.com/s/shopify-ep494-sb *LMNT:* Zero-sugar electrolyte drink mix. Go to https://lexfridman.com/s/lmnt-ep494-sb *Fin:* AI agent for customer service. Go to https://lexfridman.com/s/fin-ep494-sb *Quo:* Phone system (calls, texts, contacts) for businesses. Go to https://lexfridman.com/s/quo-ep494-sb *OUTLINE:* 0:00 - Introduction 0:33 - Extreme co-design and rack-scale engineering 3:18 - How Jensen runs NVIDIA 22:40 - AI scaling laws 37:40 - Biggest blockers to AI scaling laws 39:23 - Supply chain 41:18 - Memory 47:24 - Power 52:43 - Elon and Colossus 56:11 - Jensen's approach to engineering and leadership 1:01:37 - China 1:09:50 - TSMC and Taiwan 1:15:04 - NVIDIA's moat 1:20:41 -

8

Introduction to Pooling Layer in CNN | Max Pooling, Average Pooling

Understanding CNNs becomes much easier once you master one key concept — the Pooling Layer. In this video, Varun sir will break down the Introduction to Pooling Layer in CNN, covering both Max Pooling and Average Pooling in a simple and practical way. Whether you’re a beginner in Deep Learning or preparing for exams, interviews, or projects — this video will give you a clear and strong foundation. #cnn #ann #deeplearning #neuralnetworks -------------------------------------------------------------------------------------------------------------------------------------- Timestamps: 00:07 – Introduction to Pooling 01:18 – Memory Requirement Problem in CNN 03:45 – Max Pooling 05:56 – Types of Pooling -------------------------------------------------------------------------------------------------------------------------------------- 🔹 Gate Smashers Shorts: Watch quick concepts & short videos here: https://www.youtube.com/@GateSmashersShorts 🔹 Subscribe for more shorts and motivational content: https://www.youtube.com/@varunainashots Subject-wise playlist Links: -------------------------------------------------------------------------------------------------------------------------------------- ►Design and Analysis of algorithms (DAA): https://www.youtube.com/playlist?list=PLxCzCOWd7aiHcmS4i14bI0VrMbZTUvlTa ►Software Engineering (Complete Playlist): https://www.youtube.com/playlist?list=PLxCzCOWd7aiEed7SKZBnC6ypFDWYLRvB2 ►Database Management System: https://www.youtube.com/playlist?list=PLxCzCOWd7aiFAN6I8CuViBuCdJgiOkT2Y ►Cloud Computing: https://www.youtube.com/playlist?list=PLxCzCOWd7aiHRHVUtR-O52MsrdUSrzuy4 ► Theory of Computation https://www.youtube.com/playlist?list=PLxCzCOWd7aiFM9Lj5G9G_76adtyb4ef7i ►Artificial Intelligence: https://www.youtube.com/playlist?list=PLxCzCOWd7aiHGhOHV-nwb0HR5US5GFKFI ►Computer Networks (Complete Playlist): https://www.youtube.com/playlist?list=PLxCzCOWd7aiGFBD2-2joCpWOLUrDLvVV_ ►Operating System: https://www.y

9

#352 AI Agents at Work: What Actually Breaks (and How to Fix It) with Danielle Crop, WNS

AI agents are spreading across the data and AI industry, promising to automate everything from research to outreach. At the same time, teams are learning that these tools can hallucinate, leak data, or act in surprising ways. In day-to-day work, the challenge is deciding which tasks to hand off, what data to share, and how to keep the output trustworthy. Do your agents actually add value, or just add noise? Are they running in a secured, ring-fenced environment? How do you balance playful experimentation with critical checking when an agent confidently gets a key fact wrong? Danielle leads go-to-market strategy at WNS, Capgemini's AI transformation services arm. Previously, Danielle was Chief Data Officer at American Express and Albertsons. She also write The Remix substack on technology trends, and is an Editorial Board Member for CDO Magazine. In the episode, Richie and Danielle explore AI agents at work, experimentation with guardrails, data privacy, access, tone controls, OpenClaw automation wins and failures, token costs, tying AI plans to P&L strategy, shifts in careers and hiring, how data teams handle unstructured data governance, and much more. Find DataFramed on DataCamp https://www.datacamp.com/podcast and on your preferred podcast streaming platform: Apple Podcasts: https://podcasts.apple.com/us/podcast/dataframed/id1336150688 Spotify: https://open.spotify.com/show/02yJXEJAJiQ0Vm2AO9Xj6X?si=d08431f59edc4ccd Links Mentioned in the Show: WNS - https://www.wns.com/ AI-Native Course: Intro to AI for Work - https://www.datacamp.com/courses/introduction-to-ai-for-work Catch Danielle speaking at RADAR—April 1 - https://events.datacamp.com/radar-ai-human Related Episode: AI Agents Are the New Shadow IT (And Your Governance Isn’t Ready) with Stijn Christiaens, CEO at Collibra - https://www.datacamp.com/podcast/ai-agents-are-the-new-shadow-it New to DataCamp? Learn on the go using the DataCamp mobile app - https://www.datacamp.com/mobile Empower your busin

10

Claude Code Essentials

Learn how to use Claude Code to build real-world agentic coding workflows. Course developed by @ExamProChannel Additional recoruces: https://www.exampro.co/exp-claudecode-01 ⭐️ Contents ⭐️ Introduction - 00:00:00 Intro & Meet your Instructor - 00:01:06 Claude Code Essentials & Guest Instructor Core Concepts and Foundations - 00:07:29 Agentic Coding Tools & Comparisons - 00:14:01 What is a Code Harness & Claude Code? - 00:16:59 The Agentic Loop: Tool Calls & Models - 00:24:23 Claude Modes & Additional Resources - 00:26:43 Subscription, Usage & Auth Errors - 00:31:34 System Requirements & Doctor CLI - 00:38:24 Install CLI: PowerShell, CMD, Linux & VSC - 01:10:45 Interactive Mode & Ctrl+C - 01:14:05 Auth Tokens, Stats & Usage Limits - 01:31:04 Sessions: Resume, Fork & Context Commands - 01:46:18 Compact, Clear, Rename & Rewind - 01:56:07 Status, Logout & Usage Commands - 02:04:18 ccusage & API Key Setup - 02:26:39 Cost Command & Third-Party Providers - 02:39:09 API Keys: Bedrock, Foundry & Vertex AI - 03:01:44 btw, Voice & Export Commands - 03:07:09 Claude Code Projects & Scope - 03:13:05 Status Line & Session Data - 03:23:14 Settings & Permission Rules (Bash, MCP, WebFetch) - 04:04:16 Permission Modes & CLI/GUI Editing - 04:16:43 Sandboxing & Dangerous Scenarios - 04:55:13 VIM Mode & Model Configuration - 05:00:10 Fast Mode & Image Reasoning - 05:10:18 Effort Command & Headless Tasks - 05:27:46 Escaping Logic & Debug Mode - 05:34:21 Dev Containers with Claude Code - 05:54:24 Common Workflow Follow Along - 06:17:31 Notification Hooks & Security Hooks Surfaces - 07:16:55 Claude Code Surfaces: Desktop & Web - 07:35:28 Claude Chrome & Browser Extensions - 07:45:25 VS Code & JetBrains IDE Integration - 07:59:11 GitHub Actions & Remote Control - 08:40:48 Computing Follow Along Advanced - 08:42:36 Security Review & Output Styles - 08:58:05 Simplify Command & Scheduling - 09:07:42 Code Review & Agent SDK - 09:15:12 Persistent Context: Claude.md & Rules - 09:47:03 Claude Au

11

Stride Convolution | Stride-1, Stride-2, Stride-3

In this video, Varun sir will break down Stride-1, Stride-2, and Stride-3 with clear examples so you can easily grasp how stride affects feature maps in Convolutional Neural Networks (CNNs). Whether you're preparing for exams, interviews, or building your deep learning foundation, this video will make the concept stick to your mind. #ann #cnn #deeplearning #neuralnetworks 🔹 Gate Smashers Shorts: Watch quick concepts & short videos here: https://www.youtube.com/@GateSmashersShorts 🔹 Subscribe for more shorts and motivational content: https://www.youtube.com/@varunainashots -------------------------------------------------------------------------------------------------------------------------------------- Timestamps: 00:00 – Introduction to Convolution 00:40 – What is Stride? 02:02 – Stride-1 04:02 – Stride-2 06:06 – Edge Case & Floor Value Concept 07:01 – Padding Concept -------------------------------------------------------------------------------------------------------------------------------------- 🔹 Gate Smashers Shorts: Watch quick concepts & short videos here: https://www.youtube.com/@GateSmashersShorts 🔹 Subscribe for more shorts and motivational content: https://www.youtube.com/@varunainashots Subject-wise playlist Links: -------------------------------------------------------------------------------------------------------------------------------------- ►Design and Analysis of algorithms (DAA): https://www.youtube.com/playlist?list=PLxCzCOWd7aiHcmS4i14bI0VrMbZTUvlTa ►Software Engineering (Complete Playlist): https://www.youtube.com/playlist?list=PLxCzCOWd7aiEed7SKZBnC6ypFDWYLRvB2 ►Database Management System: https://www.youtube.com/playlist?list=PLxCzCOWd7aiFAN6I8CuViBuCdJgiOkT2Y ►Cloud Computing: https://www.youtube.com/playlist?list=PLxCzCOWd7aiHRHVUtR-O52MsrdUSrzuy4 ► Theory of Computation https://www.youtube.com/playlist?list=PLxCzCOWd7aiFM9Lj5G9G_76adtyb4ef7i ►Artificial Intelligence: https://www.youtu

12

🎧 LoFi Beats for Coding & Focus: Calm Beats to Study, Build, and Think

A calm playlist for coding, studying, or focused work. Whether you're debugging, reading, or building exciting new things after taking one of DeepLearning.AI's courses, this mix is designed to help you stay in flow without distractions. What you’ll find here: • Soft, consistent rhythms for long work sessions • Minimal vocals to avoid breaking focus • A steady pace for deep thinking (and deep learning 😉) Use it while: • Coding or debugging • Studying or taking notes • Reading technical material • Working through projects — DeepLearning.AI creates courses to help you understand and build with AI. This playlist is here to support the moments in between, when you’re practicing, learning, and figuring things out. Check out our course catalog: https://learn.deeplearning.ai/

13

CS50 for Business - Lecture 4 - Approaching Artificial Intelligence

This is Lecture 4 of CS50 for Business on Approaching Artificial Intelligence. Explore the fundamentals of artificial intelligence, including game playing algorithms, reinforcement learning, neural networks, and natural language processing. To take this course for a certificate, register at cs50.edx.org/business. *** This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming. *** HOW TO SUBSCRIBE http://www.youtube.com/subscription_center?add_user=cs50tv HOW TO TAKE CS50 edX: https://cs50.edx.org/ Harvard Extension School: https://cs50.harvard.edu/extension Harvard Summer School: https://cs50.harvard.edu/summer OpenCourseWare: https://cs50.harvard.edu/x HOW TO JOIN CS50 COMMUNITIES Bluesky: https://bsky.app/profile/cs50.harvard.edu Discord: https://discord.gg/cs50 Ed: https://cs50.edx.org/ed Facebook Group: https://www.facebook.com/groups/cs50/ Faceboook Page: https://www.facebook.com/cs50/ GitHub: https://github.com/cs50 Gitter: https://gitter.im/cs50/x Instagram: https://instagram.com/cs50 LinkedIn Group: https://www.linkedin.com/groups/7437240/ LinkedIn Page: https://www.linkedin.com/school/cs50/ Medium: https://cs50.medium.com/ Quora: https://www.quora.com/topic/CS50 Reddit: https://www.reddit.com/r/cs50/ Slack: https://cs50.edx.org/slack Snapchat: https://www.snapchat.com/add/cs50 SoundCloud: https://soundcloud.com/cs50 Stack Exchange: https://cs50.stackexchange.com/ Telegram: https://t.me/cs50x Threads: https://www.threads.net/@cs50 TikTok: https://www.tiktok.com/@cs50 Twitter: https://twitter.com/cs50 Twitter Community: https://twitter.com/i/communities/1722308663522594923 YouTube: http://www.youtube.com/cs50 HOW TO FOLLOW DAVID J. MALAN Facebook: https://www.facebook.com/dmalan GitHub: https://github.com/dmalan Instagram: https://www.instagram.com/davidjmalan/ LinkedIn: https://www.linkedin.com/in/malan/ Quora: https://www.quora.com/profile/David-J-Malan Threads: https://www.th

14

Adobe Acrobat Studio: One of the Best AI Document Assistants (2026)

If you’re constantly digging through PDFs, presentations, transcripts, and reports to find information or to make connections between your documents, you’re not alone. Most of us spend far too much time manually searching through documents instead of actually getting work done. In this video, you’ll learn how to use one of the best AI document assistants with Adobe Acrobat Studio and its powerful PDF Spaces feature to bring multiple file types together into one intelligent workspace that summarizes content, answers your questions in natural language, provides citations, and even adapts responses with custom AI Assistants for different goals. You’ll see how to: • Create a PDF Space containing up to 100 files • Generate AI summaries across multiple documents • Ask questions and receive responses with citations from your documents • Switch AI personas for different analytical perspectives • Generate a podcast as a document summary • Build an AI-powered workspace for research, onboarding, contract review, and more This video gives you a practical look at how to increase productivity with AI using one of the best AI document assistant workspaces available today. Host: Garrick Chow Sponsor: Adobe #AdobeAcrobat #AIAssistant #DocumentProductivity #PDF 📚 RESOURCES Try Adobe Acrobat: https://adobe.ly/TryAcrobatStudio ⌚ TIMESTAMPS 00:00 - Introduction 00:41 - What makes an effective AI document assistant? 01:35 - Create a PDF Space 03:25 - Explore the PDF Space 04:35 - Ask AI Assistant about your files 05:30 - Use-case scenarios 06:51 - Choose different AI personas 08:30 - Generate podcast summaries 09:46 - Conclusion📩 NEWSLETTER - Get the latest high-quality tutorial and tips and tricks videos emailed to your inbox each week: https://newsletter.kevinstratvert.com 🔽 CONNECT WITH ME - Official website: http://www.kevinstratvert.com - LinkedIn: https://www.linkedin.com/in/kevinstratvert/ - Discord: https://bit.ly/KevinStratvertDiscord - Twitter: https://twitter

15

CS50 for Business - Lecture 2 - Designing Data Structures

This is Lecture 2 of CS50 for Business on Designing Data Structures. Explore the essentials of data structures, such as arrays, linked lists, trees, and hash tables, and understand their trade-offs for efficient memory use and algorithm performance. To take this course for a certificate, register at cs50.edx.org/business. *** This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming. *** HOW TO SUBSCRIBE http://www.youtube.com/subscription_center?add_user=cs50tv HOW TO TAKE CS50 edX: https://cs50.edx.org/ Harvard Extension School: https://cs50.harvard.edu/extension Harvard Summer School: https://cs50.harvard.edu/summer OpenCourseWare: https://cs50.harvard.edu/x HOW TO JOIN CS50 COMMUNITIES Bluesky: https://bsky.app/profile/cs50.harvard.edu Discord: https://discord.gg/cs50 Ed: https://cs50.edx.org/ed Facebook Group: https://www.facebook.com/groups/cs50/ Faceboook Page: https://www.facebook.com/cs50/ GitHub: https://github.com/cs50 Gitter: https://gitter.im/cs50/x Instagram: https://instagram.com/cs50 LinkedIn Group: https://www.linkedin.com/groups/7437240/ LinkedIn Page: https://www.linkedin.com/school/cs50/ Medium: https://cs50.medium.com/ Quora: https://www.quora.com/topic/CS50 Reddit: https://www.reddit.com/r/cs50/ Slack: https://cs50.edx.org/slack Snapchat: https://www.snapchat.com/add/cs50 SoundCloud: https://soundcloud.com/cs50 Stack Exchange: https://cs50.stackexchange.com/ Telegram: https://t.me/cs50x Threads: https://www.threads.net/@cs50 TikTok: https://www.tiktok.com/@cs50 Twitter: https://twitter.com/cs50 Twitter Community: https://twitter.com/i/communities/1722308663522594923 YouTube: http://www.youtube.com/cs50 HOW TO FOLLOW DAVID J. MALAN Facebook: https://www.facebook.com/dmalan GitHub: https://github.com/dmalan Instagram: https://www.instagram.com/davidjmalan/ LinkedIn: https://www.linkedin.com/in/malan/ Quora: https://www.quora.com/profile/David-J-Malan Threads: https

16

CS50 for Business - Lecture 1 - Analyzing Algorithms

This is Lecture 1 (the second!) of CS50 for Business on Analyzing Algorithms. Learn how to analyze and optimize algorithms for searching and sorting with in-depth explanations of time complexities and practical examples. To take this course for a certificate, register at cs50.edx.org/business. *** This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming. *** HOW TO SUBSCRIBE http://www.youtube.com/subscription_center?add_user=cs50tv HOW TO TAKE CS50 edX: https://cs50.edx.org/ Harvard Extension School: https://cs50.harvard.edu/extension Harvard Summer School: https://cs50.harvard.edu/summer OpenCourseWare: https://cs50.harvard.edu/x HOW TO JOIN CS50 COMMUNITIES Bluesky: https://bsky.app/profile/cs50.harvard.edu Discord: https://discord.gg/cs50 Ed: https://cs50.edx.org/ed Facebook Group: https://www.facebook.com/groups/cs50/ Faceboook Page: https://www.facebook.com/cs50/ GitHub: https://github.com/cs50 Gitter: https://gitter.im/cs50/x Instagram: https://instagram.com/cs50 LinkedIn Group: https://www.linkedin.com/groups/7437240/ LinkedIn Page: https://www.linkedin.com/school/cs50/ Medium: https://cs50.medium.com/ Quora: https://www.quora.com/topic/CS50 Reddit: https://www.reddit.com/r/cs50/ Slack: https://cs50.edx.org/slack Snapchat: https://www.snapchat.com/add/cs50 SoundCloud: https://soundcloud.com/cs50 Stack Exchange: https://cs50.stackexchange.com/ Telegram: https://t.me/cs50x Threads: https://www.threads.net/@cs50 TikTok: https://www.tiktok.com/@cs50 Twitter: https://twitter.com/cs50 Twitter Community: https://twitter.com/i/communities/1722308663522594923 YouTube: http://www.youtube.com/cs50 HOW TO FOLLOW DAVID J. MALAN Facebook: https://www.facebook.com/dmalan GitHub: https://github.com/dmalan Instagram: https://www.instagram.com/davidjmalan/ LinkedIn: https://www.linkedin.com/in/malan/ Quora: https://www.quora.com/profile/David-J-Malan Threads: https://www.threads.net/@davidjmal

17

CS50 for Business - Lecture 0 - Interpreting Information

This is Lecture 0 (the very first!) of CS50 for Business, in which you'll learn all about Interpreting Information. Discover the fundamentals of computer science, from binary data to algorithms, and learn how technology processes information to solve real-world problems efficiently. To take this course for a certificate, register at cs50.edx.org/business. *** This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming. *** HOW TO SUBSCRIBE http://www.youtube.com/subscription_center?add_user=cs50tv HOW TO TAKE CS50 edX: https://cs50.edx.org/ Harvard Extension School: https://cs50.harvard.edu/extension Harvard Summer School: https://cs50.harvard.edu/summer OpenCourseWare: https://cs50.harvard.edu/x HOW TO JOIN CS50 COMMUNITIES Bluesky: https://bsky.app/profile/cs50.harvard.edu Discord: https://discord.gg/cs50 Ed: https://cs50.edx.org/ed Facebook Group: https://www.facebook.com/groups/cs50/ Faceboook Page: https://www.facebook.com/cs50/ GitHub: https://github.com/cs50 Gitter: https://gitter.im/cs50/x Instagram: https://instagram.com/cs50 LinkedIn Group: https://www.linkedin.com/groups/7437240/ LinkedIn Page: https://www.linkedin.com/school/cs50/ Medium: https://cs50.medium.com/ Quora: https://www.quora.com/topic/CS50 Reddit: https://www.reddit.com/r/cs50/ Slack: https://cs50.edx.org/slack Snapchat: https://www.snapchat.com/add/cs50 SoundCloud: https://soundcloud.com/cs50 Stack Exchange: https://cs50.stackexchange.com/ Telegram: https://t.me/cs50x Threads: https://www.threads.net/@cs50 TikTok: https://www.tiktok.com/@cs50 Twitter: https://twitter.com/cs50 Twitter Community: https://twitter.com/i/communities/1722308663522594923 YouTube: http://www.youtube.com/cs50 HOW TO FOLLOW DAVID J. MALAN Facebook: https://www.facebook.com/dmalan GitHub: https://github.com/dmalan Instagram: https://www.instagram.com/davidjmalan/ LinkedIn: https://www.linkedin.com/in/malan/ Quora: https://www.quora.com/p

18

When AI Discovers the Next Transformer — Robert Lange

Robert Lange, founding researcher at Sakana AI, joins Tim to discuss *Shinka Evolve* — a framework that combines LLMs with evolutionary algorithms to do open-ended program search. The core claim: systems like AlphaEvolve can optimize solutions to fixed problems, but real scientific progress requires co-evolving the problems themselves. GTC is coming, the premier AI conference, great opportunity to learn about AI. NVIDIA and partners will showcase breakthroughs in physical AI, AI factories, agentic AI, and inference, exploring the next wave of AI innovation for developers and researchers. Register for virtual GTC for free, using my link and win NVIDIA DGX Spark (https://nvda.ws/4qQ0LMg) In this episode: • Why AlphaEvolve gets stuck — it needs a human to hand it the right problem. Shinka tries to invent new problems automatically, drawing on ideas from POET, PowerPlay, and MAP-Elites quality-diversity search. • The *architecture* of Shinka: an archive of programs organized as islands, LLMs used as mutation operators, and a UCB bandit that adaptively selects between frontier models (GPT-5, Sonnet 4.5, Gemini) mid-run. The credit-assignment problem across models turns out to be genuinely hard. • Concrete results — state-of-the-art circle packing with dramatically fewer evaluations, second place in an AtCoder competitive programming challenge, evolved load-balancing loss functions for mixture-of-experts models, and agent scaffolds for AIME math benchmarks. • Are these systems actually thinking outside the box, or are they parasitic on their starting conditions? When LLMs run autonomously, "nothing interesting happens." Robert pushes back with the stepping-stone argument — evolution doesn't need to extrapolate, just recombine usefully. • The AI Scientist question: can automated research pipelines produce real science, or just workshop-level slop that passes surface-level review? Robert is honest that the current version is more co-pilot than autonomous researcher.

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Make your Own Agents in Copilot | Complete Tutorial

Copilot Agents are specialized AI assistants that can handle tasks or answer questions within specific, defined parameters. You can use agents in Copilot or make your own agents using the Copilot Agent Builder or Copilot Studio. Agents can even work autonomously or link to applications, facilitating workflows across multiple applications. This video shows how agents work in general, then shows how to put agents to work immediately in Microsoft 365 Copilot. Microsoft provides several pre-made agents. There are also third-party agents that make Copilot act as an AI front-end for different apps and services. This video also shows how to easily create your own agent using the Copilot Agent Builder, or how to build more advanced agents using Copilot Studio. What you’ll learn: - What are Agents - Using Agents in Microsoft 365 Copilot - Use Agents provided by Microsoft, including the Researcher and Analyst Agents - Analyze and modify spreadsheets using the Agent Mode in Excel - Expand Copilot with 3rd Party Agents - Create your own Agent easily with the Copilot Agent Builder - Build more complex agents using Copilot Studio - Publish agents from Copilot Studio for your teammates and external users Host: Nick Brazzi #Copilot #MicrosoftCopilot #aiagents ⌚ TIMESTAMPS 00:00 – Overview of Agents in Microsoft 365 03:20 – Use Built-in Agents 10:34 – The Researcher and Analyst Agents 14:51 – Third Party Agents 19:54 – Excel’s Agent mode 25:12 – Copilot Agent Builder – Make Simple Agents 34:22 – Copilot Studio Licensing and Credits 37:19 - Build an Agent in Copilot Studio 46:14 – Define Conversation Topics in Copilot Studio 52:04 – Publish an Agent for Teammates 56:34 – Publish an Agent for External Partners 📩 NEWSLETTER Get the latest high-quality tutorial and tips and tricks videos emailed to your inbox each week: https://newsletter.kevinstratvert.com 🔽 CONNECT WITH ME Official website: http://www.kevinstratvert.com LinkedIn: / kevinstratvert Discord: https://bit.

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Stanford CS221 | Autumn 2025 | Lecture 20: Fireside Chat, Conclusion

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques Please follow along with the course schedule: https://stanford-cs221.github.io/autumn2025/ Follow the playlist: https://youtube.com/playlist?list=PLoROMvodv4rMeDqwS1yFl3j3sR_-MQNEN&si=bVivXjDfVEQKky1D Teaching Team Percy Liang, Associate Professor of Computer Science (and courtesy in Statistics)

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Stanford CS221 | Autumn 2025 | Lecture 19: AI Supply Chains

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques Please follow along with the course schedule: https://stanford-cs221.github.io/autumn2025/ Follow the playlist: https://youtube.com/playlist?list=PLoROMvodv4rMeDqwS1yFl3j3sR_-MQNEN&si=bVivXjDfVEQKky1D Teaching Team Percy Liang, Associate Professor of Computer Science (and courtesy in Statistics)

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Stanford CS221 | Autumn 2025 | Lecture 18: AI & Society

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques Please follow along with the course schedule: https://stanford-cs221.github.io/autumn2025/ Follow the playlist: https://youtube.com/playlist?list=PLoROMvodv4rMeDqwS1yFl3j3sR_-MQNEN&si=bVivXjDfVEQKky1D Teaching Team Percy Liang, Associate Professor of Computer Science (and courtesy in Statistics)

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Stanford CS221 | Autumn 2025 | Lecture 17: Language Models

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques Please follow along with the course schedule: https://stanford-cs221.github.io/autumn2025/ Follow the playlist: https://youtube.com/playlist?list=PLoROMvodv4rMeDqwS1yFl3j3sR_-MQNEN&si=bVivXjDfVEQKky1D Teaching Team Percy Liang, Associate Professor of Computer Science (and courtesy in Statistics)

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Stanford CS221 | Autumn 2025 | Lecture 16: Logic II

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques Please follow along with the course schedule: https://stanford-cs221.github.io/autumn2025/ Teaching Team Percy Liang, Associate Professor of Computer Science (and courtesy in Statistics)

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Stanford CS221 | Autumn 2025 | Lecture 15: Logic I

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques Please follow along with the course schedule: https://stanford-cs221.github.io/autumn2025/ Follow the playlist: https://youtube.com/playlist?list=PLoROMvodv4rMeDqwS1yFl3j3sR_-MQNEN&si=bVivXjDfVEQKky1D Teaching Team Percy Liang, Associate Professor of Computer Science (and courtesy in Statistics)

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Stanford CS221 | Autumn 2025 | Lecture 14: Bayesian Networks and Learning

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques Please follow along with the course schedule: https://stanford-cs221.github.io/autumn2025/ Follow the playlist: https://youtube.com/playlist?list=PLoROMvodv4rMeDqwS1yFl3j3sR_-MQNEN&si=bVivXjDfVEQKky1D Teaching Team Percy Liang, Associate Professor of Computer Science (and courtesy in Statistics)

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Stanford CS221 | Autumn 2025 | Lecture 13: Bayesian Networks and Gibbs Sampling

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques Please follow along with the course schedule: https://stanford-cs221.github.io/autumn2025/ Follow the playlist: https://youtube.com/playlist?list=PLoROMvodv4rMeDqwS1yFl3j3sR_-MQNEN&si=bVivXjDfVEQKky1D Teaching Team Percy Liang, Associate Professor of Computer Science (and courtesy in Statistics)

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Stanford CS221 | Autumn 2025 | Lecture 12: Bayesian Networks I

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques Please follow along with the course schedule: https://stanford-cs221.github.io/autumn2025/ Follow the playlist: https://youtube.com/playlist?list=PLoROMvodv4rMeDqwS1yFl3j3sR_-MQNEN&si=bVivXjDfVEQKky1D Teaching Team Percy Liang, Associate Professor of Computer Science (and courtesy in Statistics)

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Choosing an AI Career in 2026? Understand Every AI Role Before You Start | CampusX

In this video, we break down a complete AI roadmap for 2026 — from the fundamentals to advanced topics like Machine Learning, Deep Learning, NLP, Transformers, and Generative AI. Instead of trying to learn every new tool, this roadmap focuses on building strong fundamentals and a clear learning path so you can progress toward becoming an AI Engineer or Data Scientist. Roadmap: https://roadmap.sh/r/ai-roadmap-for-2026---final-draft CampusX AI Courses: https://learnwith.campusx.in/s/store Notes: https://learnwith.campusx.in/s/store/courses/YouTube%20Notes Queries? - https://www.instagram.com/campusx.official What you’ll learn in this video: • Programming foundations for AI • Python and essential AI development tools • Mathematics required for ML and AI • Machine Learning fundamentals and algorithms • Deep Learning and neural networks • NLP and Transformers • Generative AI and Large Language Models • Important AI frameworks and tools • How to build AI projects for your portfolio • Career path to become an AI engineer 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Find Study Partner: https://discord.gg/PsWu8R87Z8 E-mail us at support@campusx.in ⌚Chapters⌚ 00:00:00 - Introduction and goal of the AI roadmap 00:03:40 - Why most people fail to learn AI 00:08:20 - How the roadmap is structured (end-to-end plan) 00:15:10 - Programming foundations required for AI 00:28:40 - Python and essential tools for AI development 00:45:30 - Mathematics required for AI (linear algebra, statistics, probability) 01:05:20 - Machine Learning fundamentals and algorithms 01:28:30 - Deep Learning concepts and neural networks 01:50:40 - Natural Language Processing and transformers 02:07:30 - Generative AI and Large Language Models 02:27:00 - AI tools, frameworks, and development stack 02:46:30 - Building real AI projects and portfolio 03:02:30 - Career roadmap and how to become an AI engin

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The Dangerous Illusion of AI Coding? - Jeremy Howard

Dive into the realities of AI-assisted coding, the origins of modern fine-tuning, and the cognitive science behind machine learning with fast.ai founder Jeremy Howard. In this episode, we unpack why AI might be turning software engineering into a slot machine and how to maintain true technical intuition in the age of large language models. GTC is coming, the premier AI conference, great opportunity to learn about AI. NVIDIA and partners will showcase breakthroughs in physical AI, AI factories, agentic AI, and inference, exploring the next wave of AI innovation for developers and researchers. Register for virtual GTC for free, using my link and win NVIDIA DGX Spark (https://nvda.ws/4qQ0LMg) Jeremy Howard is a renowned data scientist, researcher, entrepreneur, and educator. As the co-founder of fast.ai, former President of Kaggle, and the creator of ULMFiT, Jeremy has spent decades democratizing deep learning. His pioneering work laid the foundation for modern transfer learning and the pre-training and fine-tuning paradigm that powers today's language models. Key Topics and Main Insights Discussed: - The Origins of ULMFiT and Fine-Tuning - The Vibe Coding Illusion and Software Engineering - Cognitive Science, Friction, and Learning - The Future of Developers RESCRIPT: https://app.rescript.info/public/share/BhX5zP3b0m63srLOQDKBTFTooSzEMh_ARwmDG_h_izk https://app.rescript.info/api/public/sessions/62d06c0336c567d6/pdf Jeremy Howard: https://x.com/jeremyphoward https://www.answer.ai/ --- TIMESTAMPS (fixed): 00:00:00 Introduction & GTC Sponsor 00:04:30 ULMFiT & The Birth of Fine-Tuning 00:12:00 Intuition & The Mechanics of Learning 00:18:30 Abstraction Hierarchies & AI Creativity 00:23:00 Claude Code & The Interpolation Illusion 00:27:30 Coding vs. Software Engineering 00:30:00 Cosplaying Intelligence: Dennett vs. Searle 00:36:30 Automation, Radiology & Desirable Difficulty 00:42:30 Organizational Knowledge & The Slope 00:48:00 Vibe Coding as a Slot Machine 00:54:00

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