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This full course on AI agents is segmented into three chapters: foundational understanding of AI agents, hands-on tutorials for building various AI use cases, and strategies for monetization. You’ll gain insights into the anatomy of AI agents, practical steps for creating them using no-code platforms, and real-world applications to seize the growing opportunities in AI.

Timestamps:
0:00 - What We’re Covering
2:39 - Why Learn to Build AI Agents?
5:39 - What Are AI Agents?
6:40 - Chatbot or Agent?
8:44 - Anatomy of an AI Agent
12:34 - The Three Ingredients
13:58 - The Web, APIS, and Tools Explained
17:04 - Anatomy of a Tool
18:40 - Schemas: API Instruction Manuals
23:00 - Advanced Tools Use
26:11 - Conversational or Automated Agents
29:23 - Real-World Applications
32:39 - Foundations Summary
35:00 - What We’re Building
38:34 - Build 1
1:11:12 - Build 2
1:47:44 - Build 3
3:01:29 - Build 4
3:35:29 - The Real Opportunity
3:39:47 - Three Ways to Win
3:41:30 - Extending Your Knowledge Gap
3:45:49 - Getting Your First Clients
3:48:46 - Next Steps

#sponsored Build your first AI agent for free https://botpress.com/?utm_source=youtube&utm_medium=cpc&utm_campaign=aimaster&utm_term=buildchatgptagent

🚀 Become an AI Master – All-in-one AI Learning https://whop.com/c/become-pro/ylqxkdp1c5k
📹Get a Custom Promo Video From AI Master https://collab.aimaster.me/

Want to build AI agents but think you need to code? Wrong. In this video, I show you exactly how to create production-ready AI agents from scratch using three platforms: OpenAI Agent Builder, Botpress, and Zapier AI Agents.

You'll see the full workflow—from blank canvas to live agent—including:
✅ Knowledge base setup with RAG
✅ Real-time testing and deployment
✅ Multi-channel publishing (WhatsApp, Slack, web chat)
✅ Lead collection workflows
✅ Cost comparison and scaling strategies

🎯 WHAT YOU'LL LEARN:
• How to use ChatGPT to write agent prompts for you
• Setting up FAQ bots, customer support agents, and lead collectors
• Connecting knowledge bases (PDFs, websites, Notion)
• Deploying agents across WhatsApp, websites, and messaging platforms
• Why most platforms mark up LLM costs 30-50% (and how to avoid it)
• Which platform fits your use case: internal tools vs customer-facing agents

⚙️ PLATFORMS COVERED:
→ OpenAI Agent Builder: Fast setup, internal tools, shareable links
→ Zapier AI Agents: Automation workflows, trigger-based actions
→ Botpress: Production-grade agents, 190+ integrations, no LLM markup

📂 TIMESTAMPS:

0:00 — Build AI Agents Without Coding
1:09 — How to Build an AI Agent with OpenAI
3:49 — How to Build an AI Agent with Botpress
6:26 — Knowledge Base & RAG System
8:00 — Choosing Your LLM Model
8:41 — Testing & Deployment
9:11 — How to Build an AI Agent with Zapier
12:32 — Lead Collection Workflows in Botpress
15:32 — Deployment Across Channels
17:21 — Why Botpress for Production

🚀 START BUILDING TODAY:
The hardest part isn't building—it's starting. Pick one platform, sign up, and build your first agent this week. Start with a simple FAQ bot or lead collector, test it, deploy it, and scale from there.

💬 Built something cool? Tag me—I want to see it.

🔔 SUBSCRIBE for more AI tool comparisons, agent tutorials, and no-code automation workflows.

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#AIAgents #NoCoding #ChatGPT #Botpress #Zapier #AIAutomation #CustomerSupport

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New Claude Code Update is INSANE! (AI Coding Revolution)

Anthropic just released a massive update to Claude Code Desktop that transforms your computer into an autonomous AI coding machine. Discover how it handles everything from live app previews to automated PR merges while streamlining your entire development workflow. Learn why this update is a game-changer for developers and how to start using it today.

00:00 - Intro: The Massive Claude Update
01:04 - Live App Previews & Auto-Fixing
02:07 - Automated Local Code Reviews
02:47 - CI Failure Handling & Auto-Fix
03:26 - PR Monitoring & Auto-Merge
04:21 - Session Mobility Explained
04:48 - The Future of AI Development
06:59 - How to Get Started with Claude Code

MIT 18.06 Linear Algebra, Spring 2005
Instructor: Gilbert Strang
View the complete course: http://ocw.mit.edu/18-06S05
YouTube Playlist: https://www.youtube.com/playli....st?list=PLE7DDD91010

1. The Geometry of Linear Equations

License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu

This video introduces the fundamentals of protein design and summarizes the trajectory of the course with a focus on (1) the foundational biochemistry that protein structure prediction and design hinge on and (2) deep learning / machine learning principles overview.

Video from the Rosetta Commons PPI Workshop (February 2025)
Video Instructor: Amrita Nallathambi (UNC Chapel Hill)

Credits:
Instructor: Amrita Nallathambi
Teaching Assistants: Yehlin Cho, Cyrus Haas, and Matthew Hvasta,
RC Leadership and NSF Sponsor Grant PIs: Julia Koehler Leman & Jeffrey Gray
RC Education Director: Ashley Vater
Videographer: Canyon Florey
Rosetta Workshop Participants

00:00 - Introduction
00:20 - Deep Learning Revolution for Proteins
01:50 - The Transformer
03:38 - AlphaFold2 Overview
06:22 - AlphaFold2 Inputs
09:48 - AlphaFold2 Outputs
13:29 - Graph Neural Networks
16:24 - ProteinMPNN Loss
17:35 - Diffusion models
18:30 - RFDiffusion
19:52 - Inputs and Outputs
20:43 - Potentials