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Working with Notebooks in Vertex AI

Google Cloud Training

This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.

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What's inside

Syllabus

Introduction
This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches skills that may be useful for personal growth and development
Develops skills that are highly relevant to industry
Develops skills that are highly relevant to an academic setting
Builds a strong foundation for beginners
Multi-modal with video, readings, and discussions
Taught by established organization, Google Cloud Training

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Working with Notebooks in Vertex AI with these activities:
Review Machine Learning Fundamentals
Review the basics of machine learning, including supervised and unsupervised learning, to strengthen your foundation for Vertex AI Notebooks.
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  • Revisit key concepts of supervised learning, such as linear regression and classification.
  • Explore unsupervised learning methods, such as clustering and dimensionality reduction.
Compile a list of resources on Vertex AI Notebooks
Enhance your understanding of Vertex AI Notebooks by compiling a comprehensive list of relevant resources.
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  • Search for articles, blog posts, tutorials, and other materials on Vertex AI Notebooks
  • Organize the resources into a structured list or database
  • Include a brief description or annotation for each resource
  • Share the compiled list with other students or the community
Complete Vertex AI Notebooks Tutorials
Work through official Vertex AI Notebooks tutorials to gain hands-on experience with the platform and its features.
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  • Follow the quickstart tutorial to create and launch a Vertex AI Notebook.
  • Explore tutorials on data preparation, model training, and model evaluation using Vertex AI Notebooks.
Eight other activities
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Practice creating and managing Vertex AI Notebooks
Reinforce your understanding of creating and managing Vertex AI Notebooks by working through practice exercises.
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  • Create a new Vertex AI Notebook instance
  • Upload and attach a dataset to the notebook
  • Run a sample notebook to perform data exploration and model training
  • Save and publish the notebook
  • Manage notebook permissions and access control
Practice Creating and Managing Notebooks
Create multiple Vertex AI Notebooks with different configurations and manage them effectively to reinforce your understanding.
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  • Create a notebook with a custom runtime and pre-installed libraries.
  • Manage notebook access by adding collaborators and setting permissions.
Follow a tutorial on deploying a model with Vertex AI Notebooks
Expand your knowledge of deploying models by following a guided tutorial that uses Vertex AI Notebooks.
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  • Find a tutorial that covers model deployment with Vertex AI Notebooks
  • Follow the steps outlined in the tutorial
  • Deploy your own model using the techniques you learned
  • Monitor and evaluate the performance of your deployed model
Attend a meetup or conference on Vertex AI Notebooks
Connect with other professionals and learn about the latest trends in Vertex AI Notebooks by attending a meetup or conference.
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  • Find a meetup or conference that focuses on Vertex AI Notebooks
  • Register and attend the event
  • Network with other attendees and speakers
  • Learn about new use cases and best practices for Vertex AI Notebooks
Create a blog post on Vertex AI Notebooks
Deepen your understanding of Vertex AI Notebooks by creating a blog post that explains its key features and benefits.
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  • Choose a specific aspect of Vertex AI Notebooks to focus on
  • Research and gather information on the topic
  • Write a clear and concise blog post that explains the topic and its relevance
  • Include code examples and screenshots to illustrate your points
  • Publish the blog post on a relevant platform
Attend a workshop on advanced topics in Vertex AI Notebooks
Deepen your technical expertise by attending a workshop that covers advanced topics in Vertex AI Notebooks.
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  • Identify a workshop that aligns with your learning goals
  • Register and attend the workshop
  • Actively participate in discussions and hands-on exercises
  • Network with experts and other attendees
  • Apply the knowledge and skills gained in your own projects
Contribute to an Open Source Project Using Vertex AI Notebooks
Engage with the wider machine learning community by contributing to an open source project using Vertex AI Notebooks.
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  • Identify an open source project related to machine learning that aligns with your interests.
  • Set up a development environment and clone the project repository.
  • Create a Vertex AI Notebook and connect it to the project repository.
  • Make contributions to the project, such as adding features, fixing bugs, or improving documentation.
Participate in a Vertex AI Notebooks hackathon
Challenge yourself and apply your skills in a hands-on environment by participating in a Vertex AI Notebooks hackathon.
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  • Find a hackathon that aligns with your interests and skills
  • Form a team or work individually
  • Develop a project idea that utilizes Vertex AI Notebooks
  • Implement your project within the hackathon timeframe
  • Present your project and compete for prizes or recognition

Career center

Learners who complete Working with Notebooks in Vertex AI will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use machine learning and other techniques to extract insights from data. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Data Scientist by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Machine Learning Engineer
Machine Learning Engineers are responsible for the development and maintenance of machine learning models. They may also be involved in the design and implementation of machine learning systems. This course can help build a foundation for a career as a Machine Learning Engineer by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Data Analyst
Data Analysts use data to make informed decisions. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Data Analyst by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Software Engineer
Software Engineers design, develop, and maintain software systems. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Software Engineer by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as an Operations Research Analyst by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to make investment decisions. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Quantitative Analyst by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Product Manager
Product Managers are responsible for the development and launch of new products. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Product Manager by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Business Analyst
Business Analysts use data to solve business problems. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Business Analyst by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Market Researcher
Market Researchers collect and analyze data about markets and consumers. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Market Researcher by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Statistician
Statisticians collect and analyze data. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Statistician by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Financial Analyst
Financial Analysts use financial data to make investment decisions. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Financial Analyst by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Management Consultant
Management Consultants help organizations improve their performance. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Management Consultant by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Actuary
Actuaries use mathematical and statistical models to assess risk. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as an Actuary by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Economist
Economists study the economy. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as an Economist by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.
Data Engineer
Data Engineers design and build data systems. They may also be involved in the development and maintenance of machine learning models. This course can help build a foundation for a career as a Data Engineer by providing an introduction to the Jupyter notebook-based environments used in the field, as well as the different types of Vertex AI Notebooks and their features.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Working with Notebooks in Vertex AI.
Comprehensive guide to machine learning with TensorFlow 2.0, covering the latest techniques and best practices. It valuable resource for anyone looking to learn more about machine learning and how to use it in practice.
Widely-used textbook for deep learning, providing a comprehensive overview of the field. It is written in a clear and concise style, making it a great choice for beginners and experienced learners alike.
Comprehensive guide to machine learning with Java, covering a wide range of topics from data preprocessing to model evaluation.
Comprehensive guide to artificial intelligence with Python, covering a wide range of topics from machine learning to natural language processing.
Comprehensive guide to machine learning with Python, covering a wide range of topics from data preprocessing to model evaluation.
Concise and accessible introduction to machine learning, making it a great choice for beginners who want to get started with the field.

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