Udemy - Agentic AI Engineering with Claude Code

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Udemy - Agentic AI Engineering with Claude Code (Size: 1.9 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
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  1 - Foundations of Agentic AI
  1. What is Agentic AI.mp4 96.1 MB
  2 - Core Agent Architecture
  3 - Memory & Context Systems
  4 - Tool Use & Integration
  5 - Multi-Agent Systems
  10. Single Agent → Multi-Agent Systems.mp4 85.5 MB
  11. Agent Orchestration Patterns.mp4 182.4 MB
  12. Communication Between Agents.mp4 127.4 MB
  6 - Autonomous Loops & Optimization
  13. Feedback Loops & Self-Improvement.mp4 95.1 MB
  14. Debugging & Safety.mp4 135.8 MB
  7 - Real-World Agent Projects
  15. Project 1 — AI Content Agent.mp4 110.7 MB
  16. Project 2 — Business Automation Agent.mp4 93.1 MB
  17. Project 3 — Multi-Agent System.mp4 116 MB
  8 - Scaling & Future Systems
  18. Scaling Agentic Systems.mp4 103.2 MB
  19. Building Your AI Operating System.mp4 79.5 MB
  9 - Wrap-Up
  20. From Builder to AI Architect.mp4 74.8 MB
  8. Tool Calling & Skill Execution.mp4 81.5 MB
  9. External Integrations.mp4 64.8 MB
  6. Short-Term vs Long-Term Memory.mp4 117.7 MB
  7. Building Context-Aware Agents.mp4 72.3 MB
  3. Agent Components Deep Dive.mp4 84.8 MB
  4. Planning & Reasoning Systems.mp4 108.4 MB
  5. Decision Making in Agents.mp4 79.6 MB
  2. From Skills to Agents.mp4 87.5 MB

Description


Agentic AI Engineering with Claude Code
https://WebToolTip.com
Published 3/2026

Created by Data Science Academy

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Level: All Levels | Genre: eLearning | Language: English | Duration: 20 Lectures ( 5h 2m ) | Size: 2 GB
Design, build, and scale autonomous AI systems with memory, tools, and multi-agent workflows
What you'll learn

✓ Design and build autonomous AI agents that can plan, reason, and execute multi-step tasks independently

✓ Implement tool calling and integrations to connect AI agents with APIs, databases, and real-world systems

✓ Develop memory systems (short-term and long-term) to create context-aware and intelligent AI behavior

✓ Build and orchestrate multi-agent systems with supervisor-worker architectures and task delegation

✓ Apply planning and decision-making techniques to enable goal-driven and adaptive AI workflows

✓ Optimize and scale AI systems for performance, cost efficiency, and real-world deployment
Requirements

● Basic understanding of Python or any programming language (helpful but not mandatory)

● Familiarity with AI tools like ChatGPT or Claude is beneficial

● A laptop or computer with internet access

● Willingness to learn by building real projects and experimenting

● Basic understanding of APIs or workflows (optional, will be covered)

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