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๐Ÿ’ป ย  Accessing Utils File and Helper Functions

In each notebook on the top menu:

1: ย  Click on "File"

2: ย  Then, click on "Open"

You will be able to see all the notebook files for the lesson, including any helper functions used in the notebook on the left sidebar. See the following image for the steps above.


๐Ÿ’ป ย  Downloading Notebooks

In each notebook on the top menu:

1: ย  Click on "File"

2: ย  Then, click on "Download as"

3: ย  Then, click on "Notebook (.ipynb)"


๐Ÿ’ป ย  Uploading Your Files

After following the steps shown in the previous section ("File" => "Open"), then click on "Upload" button to upload your files.


๐Ÿ“— ย  See Your Progress

Once you enroll in this courseโ€”or any other short course on the DeepLearning.AI platformโ€”and open it, you can click on 'My Learning' at the top right corner of the desktop view. There, you will be able to see all the short courses you have enrolled in and your progress in each one.

Additionally, your progress in each short course is displayed at the bottom-left corner of the learning page for each course (desktop view).


๐Ÿ“ฑ ย  Features to Use

๐ŸŽž ย  Adjust Video Speed: Click on the gear icon (โš™) on the video and then from the Speed option, choose your desired video speed.

๐Ÿ—ฃ ย  Captions (English and Spanish): Click on the gear icon (โš™) on the video and then from the Captions option, choose to see the captions either in English or Spanish.

๐Ÿ”… ย  Video Quality: If you do not have access to high-speed internet, click on the gear icon (โš™) on the video and then from Quality, choose the quality that works the best for your Internet speed.

๐Ÿ–ฅ ย  Picture in Picture (PiP): This feature allows you to continue watching the video when you switch to another browser tab or window. Click on the small rectangle shape on the video to go to PiP mode.

โˆš ย  Hide and Unhide Lesson Navigation Menu: If you do not have a large screen, you may click on the small hamburger icon beside the title of the course to hide the left-side navigation menu. You can then unhide it by clicking on the same icon again.


๐Ÿง‘ ย  Efficient Learning Tips

The following tips can help you have an efficient learning experience with this short course and other courses.

๐Ÿง‘ ย  Create a Dedicated Study Space: Establish a quiet, organized workspace free from distractions. A dedicated learning environment can significantly improve concentration and overall learning efficiency.

๐Ÿ“… ย  Develop a Consistent Learning Schedule: Consistency is key to learning. Set out specific times in your day for study and make it a routine. Consistent study times help build a habit and improve information retention.

Tip: Set a recurring event and reminder in your calendar, with clear action items, to get regular notifications about your study plans and goals.

โ˜• ย  Take Regular Breaks: Include short breaks in your study sessions. The Pomodoro Technique, which involves studying for 25 minutes followed by a 5-minute break, can be particularly effective.

๐Ÿ’ฌ ย  Engage with the Community: Participate in forums, discussions, and group activities. Engaging with peers can provide additional insights, create a sense of community, and make learning more enjoyable.

โœ ย  Practice Active Learning: Don't just read or run notebooks or watch the material. Engage actively by taking notes, summarizing what you learn, teaching the concept to someone else, or applying the knowledge in your practical projects.


๐Ÿ“š ย  Enroll in Other Short Courses

Keep learning by enrolling in other short courses. We add new short courses regularly. Visit DeepLearning.AI Short Courses page to see our latest courses and begin learning new topics. ๐Ÿ‘‡

๐Ÿ‘‰๐Ÿ‘‰ ๐Ÿ”— DeepLearning.AI โ€“ All Short Courses [+]


๐Ÿ™‚ ย  Let Us Know What You Think

Your feedback helps us know what you liked and didn't like about the course. We read all your feedback and use them to improve this course and future courses. Please submit your feedback by clicking on "Course Feedback" option at the bottom of the lessons list menu (desktop view).

Also, you are more than welcome to join our community ๐Ÿ‘‰๐Ÿ‘‰ ๐Ÿ”— DeepLearning.AI Forum


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Welcome to AI Agentic Design Patterns with AutoGen, built in partnership with Microsoft. I'm joined by the instructors Chi Wang, who is principal researcher at Microsoft, and Qingyun Wu, who's an assistant professor at Penn State University, both of whom are co-creators of AutoGen. Thanks, Andrew. I'm excited to be here. Thank you. Great to be here with you, Andrew. This course is an introduction to AutoGen, a multi-agent conversational framework that enables you to quickly create multiple agents with different roles, persona tasks, and capabilities to implement complex AI applications using different AI agentic design patterns. Let's say you're interested in analyzing financial data. The task may require writing code to collect and analyze share prices. Then synthesizing your findings into a report. This might take a person days of research and coding and writing. A multi-agent system can streamline this process by enabling you to create and hire agents that work for you as a researcher, data collector, co-writer, and executor. Your agents can also iteratively review, critique, and improve the results until it meets your standard. This is just one example of the many practical applications of a multi-agent framework. And Chi and Qingyun will guide you through six lessons, each featuring its own unique design process and use case. In this course, you'll learn about how to train core components by exploring the building agent conversable agent. You'll create and customize a lively conversation between two standup comedian agents while exploring their interactive capabilities. Then you will learn about a multi-agent interaction pattern called Sequential chats. This allows you to build conversational agents that work step by step to carry out a list of tasks in a sequence. We'll illustrate this with a customer onboarding application. You will also explore the agent reflection framework in two practical scenarios. The first one will use multiple agents to produce a well-written blogpost, the second as tools to agents to create a conversational chess game. In both of these examples, you will learn another interaction pattern called a nested chat, which means when the agent is given a task, it calls a bunch of other agents and iterates with them for a while before it returns the result. If we think of you, the developer, as a manager of a handful of agents, then nested chat corresponds to letting an agent that you manage also in turn, manage their own agents. You also learn about a very powerful capability tool use. In which you can provide a user-defined function. For example, a function to check of certain chess moves are legal and give that to the agent to use. And for applications where you might not have a predefined function or predefined piece of code to provide, you'll also learn about coding and code execution, which means asking the agent to write the code it needs, which after checking for correctness, it could then execute that code it did wrote. Maybe in a sandbox environment to computer result needed for a task. You'll see both tool use as well as code writing and execution illustrated in the financial analysis example. And finally you learn best practices for building custom multi-agent group chats. We'll illustrate this with examples of generating a detailed report. This complex task requires planning. In other words, the agent has to decide on a sequence of actions to take, such as guiding data, analyzing, writing, and revising. You see how we can add a planning agent into the group chat and control how the work flows from one agent to another agent, so as to execute the needed individual tasks in the right sequence. Many people have worked to create this course. I'd like to thank Eric Zhu from Microsoft. As well as Diala Ezzeddine from DeepLearning.AI. In this first lesson, you will start with building your first AutoGen agent. Program a basic two-agent conversation, and enjoy a standup comedy show. That sounds great. Let's go on to the next video and get started.
course detail
Next Lesson
AI Agentic Design Patterns with AutoGen
  • Introduction
    Video
    ใƒป
    4 mins
  • Multi-Agent Conversation and Stand-up Comedy
    Video with Code Example
    ใƒป
    12 mins
  • Sequential Chats and Customer Onboarding
    Video with Code Example
    ใƒป
    8 mins
  • Reflection and Blogpost Writing
    Video with Code Example
    ใƒป
    10 mins
  • Tool Use and Conversational Chess
    Video with Code Example
    ใƒป
    15 mins
  • Coding and Financial Analysis
    Video with Code Example
    ใƒป
    17 mins
  • Planning and Stock Report Generation
    Video with Code Example
    ใƒป
    15 mins
  • Conclusion
    Video
    ใƒป
    1 min
  • Course Feedback
  • Community