Computer Science vs. Software Engineering: Explore Their Differences
October 21, 2024
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(13 reviews)
Recommended experience
Beginner level
If you have basic Python coding experience and you’re interested in automating complex workflows using AI agents, this course is for you.
(13 reviews)
Recommended experience
Beginner level
If you have basic Python coding experience and you’re interested in automating complex workflows using AI agents, this course is for you.
Use the AutoGen framework to build multi-agent systems with diverse roles and capabilities for implementing complex AI applications.
Implement agentic design patterns: Reflection, Tool use, Planning, and Multi-agent collaboration using AutoGen.
Learn directly from the creators of AutoGen, Chi Wang and Qingyun Wu.
Only available on desktop
In AI Agentic Design Patterns with AutoGen you’ll learn how to build and customize multi-agent systems, enabling agents to take on different roles and collaborate to accomplish complex tasks using AutoGen, a framework that enables development of LLM applications using multi-agents.
In this course you’ll create: 1. A two-agent chat that shows a conversation between two standup comedians, using “ConversableAgent,” a built-in agent class of AutoGen for constructing multi-agent conversations. 2. A sequence of chats between agents to provide a fun customer onboarding experience for a product, using the multi-agent collaboration design pattern. 3. A high-quality blog post by using the agent reflection framework. You’ll use the “nested chat” structure to develop a system where reviewer agents, nested within a critic agent, reflect on the blog post written by another agent. 4. A conversational chess game where two agent players can call a tool and make legal moves on the chessboard, by implementing the tool use design pattern. 5. A coding agent capable of generating the necessary code to plot stock gains for financial analysis. This agent can also integrate user-defined functions into the code. 6. Agents with coding capabilities to complete a financial analysis task. You’ll create two systems where agents collaborate and seek human feedback. The first system will generate code from scratch using an LLM, and the second will use user-provided code. You can use the AutoGen framework with any model via API call or locally within your own environment. By the end of the course, you’ll have hands-on experience with AutoGen’s core components and a solid understanding of agentic design patterns. You’ll be ready to effectively implement multi-agent systems in your workflows.
DeepLearning.AI is an education technology company that develops a global community of AI talent. DeepLearning.AI's expert-led educational experiences provide AI practitioners and non-technical professionals with the necessary tools to go all the way from foundational basics to advanced application, empowering them to build an AI-powered future.
Hands-on, project-based learning
Practice new skills by completing job-related tasks with step-by-step instructions.
No downloads or installation required
Access the tools and resources you need in a cloud environment.
Available only on desktop
This project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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In Projects, you'll complete an activity or scenario by following a set of instructions in an interactive hands-on environment. Projects are completed in a real cloud environment and within real instances of various products as opposed to a simulation or demo environment.
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