[2024] Generative AI with Vertex AI: Getting Started || #qwiklabs || #GSP1150 | [With Explanation🗣️]

Quick Lab ☁️
12 Jan 202406:12

TLDRThis video walkthrough guides users through the updated Generative AI lab with Vertex AI on Qwiklabs. It instructs viewers to log in, enable APIs, and manage notebooks in the workbench. The tutorial emphasizes the importance of checking kernel status in Jupyter Notebook and replacing project ID and region as needed. Following the steps ensures a successful lab completion with a green score, even if some waiting is required for the process to finish.

Takeaways

  • 📝 Log in to the platform using your credentials.
  • 🗸 Agree to the terms and conditions by checking the box and continuing.
  • 🔍 Search for 'Vex AI' and open the relevant tab.
  • ✅ Enable all recommended APIs for the service.
  • 🖥️ Access the workbench and navigate to 'User' > 'Manage Notebook'.
  • 🚀 Open Jupyter Lab by clicking on 'Open Jupyter Lab' and wait for it to launch.
  • 📂 Locate and open the 'prompt' folder within the 'generator AI' and 'language' folders.
  • 🎯 Ensure the kernel status is 'ideal' before running any commands in Jupyter Notebook.
  • 🔄 Refresh the page if you encounter any errors when launching the Jupyter Notebook.
  • 🔧 Replace the project ID in the script with the one from the dashboard.
  • 🌐 Update the region if a different one is specified in the lab instructions; otherwise, use the default.

Q & A

  • What is the first step to begin with the lab?

    -The first step is to log in using your credentials.

  • How long does it typically take for a Jupyter Notebook to launch?

    -It takes a couple of seconds for a Jupyter Notebook to launch, but it may vary depending on the system load.

  • What should you do if you encounter an error while launching the Jupyter Notebook?

    -If an error occurs, wait for a few seconds and then refresh the page.

  • How do you ensure that the kernel status is ideal before running a command in Jupyter Notebook?

    -Check the kernel status and wait until it shows as 'ideal'. If it's 'busy', wait until it's done with the previous command.

  • What is the purpose of enabling all recommendation APIs?

    -Enabling all recommendation APIs allows you to use the full functionality of Vertex AI and access the necessary resources for the lab.

  • How do you replace the project ID in the script?

    -You need to go back to the dashboard, copy the project ID, and replace the placeholder in the script with the actual project ID.

  • What should you do if the lab instructions mention a different region?

    -If a different region is mentioned, replace the default region in the script with the one specified in the lab instructions. Otherwise, you can continue with the default region.

  • How can you run all the shells at once in Jupyter Notebook?

    -You can run each shell by hitting Shift + Enter until the end of the script.

  • What is the expected outcome after successfully completing all the tasks in the lab?

    -After successfully completing all tasks, you should see a green tick next to each task, indicating full score without any issues.

  • What should you do if you don't get a green tick for all tasks immediately?

    -If you don't get a green tick immediately, wait for a few minutes and it should appear as the system updates your progress.

  • How can you verify that there are no errors in the files after running the commands?

    -Check the files and ensure there are no error messages. If you have followed the instructions correctly, there should be no errors.

Outlines

00:00

🚀 Introduction and Setup Process

This paragraph outlines the initial steps for accessing and updating a lab on a platform. The speaker instructs viewers to log in with their credentials and follow a series of clicks to enable recommended APIs, including Vex AI. They emphasize the importance of carefully watching the video to understand each step. The process involves waiting for various actions to complete, such as launching a Jupyter notebook and opening specific folders and files. The speaker also advises on handling potential errors, like kernel status issues, and provides guidance on running commands in the Jupyter notebook environment.

05:21

📝 Completion and Scoring

The second paragraph discusses the completion of the lab and the scoring process. The speaker assures viewers that if they follow the instructions correctly, they will receive a green checkmark for each task, indicating successful completion. They advise patience if the checkmarks do not appear immediately, as the system may take a few minutes to update the scores. The speaker encourages viewers to review the lab instructions and check their scores, and offers support for any doubts or issues through the comment section. The paragraph concludes with a thank you note and well-wishes for the viewers.

Mindmap

Keywords

💡Generative AI

Generative AI refers to the branch of artificial intelligence that focuses on creating or generating new content, such as images, text, or music, based on learned patterns and data. In the context of the video, it is the primary technology being explored, where the user is guided through the process of setting up and using Vertex AI for generative tasks.

💡Vertex AI

Vertex AI is a suite of tools and services offered by Google Cloud that enables developers and data scientists to build, deploy, and manage machine learning models with ease. It provides a range of features, including automated ML, custom model training, and AI platform integration. In the video, the user is guided on how to access and use Vertex AI to work with Generative AI.

💡API

API, or Application Programming Interface, is a set of protocols and tools that allows different software applications to communicate with each other. In the context of the video, enabling the recommendation API is a step in configuring the environment for Generative AI, which will enable the AI to access and utilize the recommendation service.

💡Jupyter Notebook

Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It is widely used in data science and machine learning for prototyping,数据分析, and展示模型结果. In the video, launching a Jupyter Notebook is part of the process to start working with Generative AI within Vertex AI.

💡Kernel

In the context of Jupyter Notebook, the kernel is the backend service that executes the code inputted in the notebook. It is responsible for the computation, and its status (such as 'busy' or 'idle') indicates whether it is currently running commands or not. The video emphasizes the importance of ensuring the kernel status is 'ideal' before running new commands.

💡Project ID

A Project ID is a unique identifier for a specific project within a cloud service, such as Google Cloud's Vertex AI. It is used to manage resources, permissions, and services associated with that project. In the video, the user is required to replace a placeholder with their actual Project ID to link their work to the correct resources.

💡Region

In cloud computing, a region refers to a geographical area that contains multiple data centers or zones. It is important for latency, data sovereignty, and redundancy purposes. In the context of the video, the user may need to select or change the region for their Generative AI project based on the lab instructions or their specific requirements.

💡Command

A command is a directive given to a computer system to perform a specific task or operation. In the context of the video, commands are lines of code or instructions entered in the Jupyter Notebook that tell the kernel what actions to execute. The video emphasizes the importance of running these commands in sequence to progress through the Generative AI setup and execution.

💡Lab Instructions

Lab instructions are detailed guidelines provided to users for completing a specific task or experiment within a learning environment or project. In the video, the lab instructions serve as the step-by-step guide for the user to follow in order to successfully set up and use Generative AI with Vertex AI.

💡Green Torch

In the context of the video, a green torch likely represents a visual indicator of successful completion or achievement of a task or milestone within the lab environment. It signifies that the user has correctly followed the instructions and met the requirements for each task.

Highlights

Log in with your credentials to start the Generative AI lab.

Ensure you watch the video for a detailed explanation of each step.

Search for 'Vex AI' and open the relevant tab for further instructions.

Enable all recommendation APIs for the necessary permissions.

Access the workbench and navigate to 'User' and 'Manage Notebook'.

Wait for Jupyter Lab to launch, and refresh the page if any errors occur.

Open the 'generator AI' and 'language' folders to locate the 'prompt' folder.

Run the shell commands in Jupyter Lab by clicking the play button or pressing Shift+Enter.

Ensure the kernel status is 'ideal' before running new commands.

Replace the project ID in the script with the one from the dashboard.

If a different 'region' is specified in the lab instructions, replace the default region with it.

Run all shells in sequence by hitting Shift+Enter until completion.

Track your progress and wait for the 'col' status to show as 'ideal'.

You should see no errors if you follow the instructions correctly.

Each task completion should be indicated by a green tick in the lab instructions.

A full score on the lab can be achieved by waiting and following the video guidance.

Doubts or questions can be addressed in the comment section of the video.

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