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Mastering AutoGen Building Multi-Agent Systems - OneDDL - 08-21-2024
![[Image: 3d45900d1747d96d3e60f68cb4e9dbe9.jpeg]](https://i123.fastpic.org/big/2024/0821/e9/3d45900d1747d96d3e60f68cb4e9dbe9.jpeg)
Free Download Mastering AutoGen Building Multi-Agent Systems
Published 7/2024
Created by Paulo Dichone | Software Engineer, AWS Cloud Practitioner & Instructor
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 43 Lectures ( 3h 27m ) | Size: 2.64 GB
Mastering Multi-Agent Systems for Research Automation and Visualization with AutoGen
What you'll learn:
Understand and Implement Multi-Agent Systems
Automate Research Paper Retrieval and Analysis
Apply Agentic Design Patterns in Real-World Scenarios
Customize Multi-Agent Systems with AutoGen
Requirements:
Basic Python Programming
Familiarity with Natural Language Processing (NLP) Concepts and LLM, ML
Description:
In this hands-on course, you will explore the power of AutoGen to build and customize multi-agent systems for automating complex workflows. This comprehensive guide will take you through the fundamental concepts of multi-agent systems, effective implementation strategies, and best practices for using AutoGen. You will learn how to configure and deploy various types of agents, such as AssistantAgent and UserProxyAgent, and see how these agents can collaborate to accomplish sophisticated tasks.What You Will Learn:Multi-Agent Systems: Understand the core principles of multi-agent systems and their benefits in automating complex workflows.Agentic Design Patterns: Learn about different agentic design patterns and how to apply them to solve real-world problems efficiently.Automation of Research Tasks: Discover how to automate the retrieval, analysis, and visualization of research papers, enhancing productivity and insight generation.Advanced NLP and LLM Techniques: Gain practical knowledge in configuring and utilizing large language models (LLMs) and natural language processing (NLP) techniques to process and analyze textual data.Visualization and Data Presentation: Master the creation of visual tools such as bar charts to present your analysis results effectively.Enterprise Use Cases: Explore enterprise-level use cases and best practices for integrating AutoGen into professional workflows.If want to master AutoGen and build multi-agent systems that are highly customizable, then this course is for you.
Who this course is for:
Data Scientists and Analysts
AI and Machine Learning Enthusiasts
Software Developers and Engineers
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