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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 Building Your Own Database Agent, built in partnership with Microsoft. In this course, you'll learn how LLMs can interact with structured data like tabular data or SQL databases. This is very useful when you're building a system to answer questions using data sources with tables of data, rather than needing to find maybe an analyst to translate a question to a SQL database query, you see how a database agents can automatically input a question and generate a sequence of actions. This function calls to retrieve the relevant data. Specifically, in this course, you learn how to build your own AI agent to interact with tabular data and SQL databases. Along the way, you'll learn about some of the key building blocks for agents and will be using the LangChain agents framework. I'm delighted that our instructor for this course is Adrian Gonzalez Sanchez. He is a data AI specialist at Microsoft, teaches at the University level, and is also author of the Azure OpenAI O'Reilly book. Thanks, Andrew. I'm very excited to be here. In this course, you will learn how to deploy LLMs to build your AI agent. Implement RAG with tabular data. Develop your own database agent. Build a function calling system, integrate Azure OpenAI assistance API. You'll go through these concepts using the Azure OpenAI service and LangChain. Although we'll be using a database agent as a running example, these components are useful for building any other agents as well. So database agents are an exciting breakthrough for how we analyze data, is letting people interact with complex datasets without needing to learn query languages like SQL, so that you can have an LLM perform requests to a database for you, regardless of the database provider, data model, or type language. Using an LLM as an extraction layer on top of the database is one of the new frontiers for data democratization within many companies, and perhaps you could bring this to fruition for your company or for applications you're working on. I mean, how exciting is that? Further, I see agents as a rapidly growing category with in terms of AI, and you also learn about key components to agents and best practices for assembling these components into draw this system. Many people have worked to create this course from the Microsoft side I'd like to thank Jorge Garcia Ximenez, Agustine SantaMaria, Arancha Diez Garcia and Xiaopeng Li. From DeepLearning.AI, Diala Ezzeddine also contributed to this course. In the first lesson, you will start building your first AI agent with the Azure OpenAI service. So let's go on to the next video to get started.
course detail
Next Lesson
Building Your Own Database Agent
  • Introduction
    Video
    ใƒป
    3 mins
  • Your First AI Agent
    Video with Code Example
    ใƒป
    9 mins
  • Interacting with a CSV Data
    Video with Code Example
    ใƒป
    12 mins
  • Connecting to a SQL Database
    Video with Code Example
    ใƒป
    10 mins
  • Azure OpenAI Function Calling Feature
    Video with Code Example
    ใƒป
    13 mins
  • Leveraging Assistants API for SQL Databases
    Video with Code Example
    ใƒป
    9 mins
  • Conclusion
    Video
    ใƒป
    1 min
  • Course Feedback
  • Community