| 1 - Download Course Materials.html | 0 B | ||
| 1 -Architecting Modular, Extensible AI Agents.mp4 | 18.5 MB | ||
| 1 -Building AI Agents.pdf | 4.4 MB | ||
| 1 -Definition and types of agents.mp4 | 14.6 MB | ||
| 1 -How Agents Communicate.mp4 | 13.2 MB | ||
| 1 -Rule-based vs ML-based decision logic.mp4 | 12.1 MB | ||
| 1 -Structuring agent memory (short-term vs long-term).mp4 | 10 MB | ||
| 1 -Types of sensors.mp4 | 16.2 MB | ||
| 1 -What are AI agents.mp4 | 15.2 MB | ||
| 1 -What are effectors and how do agents take actions.mp4 | 11.6 MB | ||
| 2 -Agent lifecycle and core design principles.mp4 | 18.7 MB | ||
| 2 -Communication Channels for Agents.mp4 | 16.2 MB | ||
| 2 -Digital Effectors – Acting in Software Environments.mp4 | 12.9 MB | ||
| 2 -Incorporating LLMs for reasoning and planning.mp4 | 12.1 MB | ||
| 2 -Preprocessing and interpreting sensor data.mp4 | 15.3 MB | ||
| 2 -Real-World Applications of AI Agents.mp4 | 15.7 MB | ||
| 2 -Tools & Frameworks for Building Agents.mp4 | 18.3 MB | ||
| 2 -Using vector stores, databases, and context caching.mp4 | 12.7 MB | ||
| 3 -Contextual Conversation Management.mp4 | 12.8 MB | ||
| 3 -Dynamic Knowledge Updates & Queries.mp4 | 13.4 MB | ||
| 3 -Error Handling & Safety Layers in Agents.mp4 | 14 MB | ||
| 3 -Feedback mechanisms.mp4 | 11.7 MB | ||
| 3 -Foundational elements.mp4 | 11.8 MB | ||
| 3 -Multi-step decision chains and memory use.mp4 | 14.3 MB | ||
| 3 -Overview of agent architecture and what learners will build.mp4 | 14.8 MB | ||
| 3 -Simulated vs Real-Time Perception.mp4 | 11.8 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 28 total files | |||
Building AI Agents: Core Component/ Intelligent Architecture
https://WebToolTip.com
Published 9/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 49m | Size: 342 MB
Core Components and Intelligent Architectures
What you'll learn
Understand the core components of AI agents and their architectures.
Build agents with sensors, effectors, memory, and decision-making engines.
Use tools and frameworks like LangChain, CrewAI, and AutoGen to create agents.
Design, test, and deploy a personalized AI agent as a final project.
Requirements
No prerequisites required — just curiosity and interest in AI. Basic programming knowledge is helpful but not mandatory.
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