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Google Cloud Training
本课程介绍 Google Cloud 中的人工智能 (AI) 和机器学习 (ML) 服务，这些服务支持数据到 AI 的生命周期（从 AI 基础、AI 开发到 AI 解决方案）。我们将探索一系列技术、产品和工具；利用这些工具，可基于不同用户（包括数据科学家、AI 开发者和机器学习工程师）的目标构建机器学习模型、机器学习流水线和生成式 AI 项目。
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OpenCourser.com/course/08n813/introduction
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What's inside
Syllabus
简介
本单元介绍课程目标：帮助学员浏览 Google Cloud 中的各项 AI 开发工具。还简要介绍了基于 Google Cloud 上的三层 AI 框架的课程结构。
AI 基础
本单元着重介绍 AI 基础，包括计算和存储等云基础架构。还介绍了 Google Cloud 上的主要数据和 AI 开发产品。最后，展示了如何使用 BigQuery ML 来构建机器学习模块，这有助于将数据转换为 AI。
Read more
Syllabus
简介
本单元介绍课程目标：帮助学员浏览 Google Cloud 中的各项 AI 开发工具。还简要介绍了基于 Google Cloud 上的三层 AI 框架的课程结构。
AI 基础
本单元着重介绍 AI 基础，包括计算和存储等云基础架构。还介绍了 Google Cloud 上的主要数据和 AI 开发产品。最后，展示了如何使用 BigQuery ML 来构建机器学习模块，这有助于将数据转换为 AI。
Read more
AI 开发选项
本单元探索在 Google Cloud 上开发机器学习项目的各种选项，包括预先训练的 API 等现成解决方案、AutoML 等无代码和低代码解决方案，以及自定义训练等基于代码的解决方案。我们会比较各选项的优缺点，帮助确定适当的开发工具。
AI 开发工作流
本单元介绍机器学习工作流，内容涵盖数据准备、数据开发，和通过 Vertex AI 提供模型。还阐明了如何使用 Vertex AI Pipelines 将工作流转化为自动化流水线。
生成式 AI
本单元介绍 AI 领域的最新进展“生成式 AI”，及其背后的技术：大语言模型 (LLM)。我们还将探索 Google Cloud 上的各种生成式 AI 开发工具，例如 Generative AI Studio 和 Model Garden。最后，我们还将探讨 AI 解决方案和嵌入的生成式 AI 功能。
摘要
本单元通过介绍最重要的概念、工具、技术和产品，对整个课程进行总结。
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
适合数据科学家、AI 开发者和机器学习工程师。
介绍了 Google Cloud 中用于 AI 和机器学习的各种服务和技术。
涵盖了从 AI 基础到 AI 开发工作流的广泛主题。
由 Google Cloud Training 提供，说明其在 AI 领域拥有丰富的经验和专业知识。
提供基于代码的解决方案、预训练的 API 和无代码/低代码解决方案，以迎合不同技能水平的开发人员。
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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 Introduction to AI and Machine Learning on GC - 简体中文 with these
activities:
阅读《深度学习》
Show steps
阅读《深度学习》可以深入了解深度学习的基础原理和技术。
View
深度學習
on Amazon
Show steps
-
阅读本书的每一章
-
总结关键概念和算法
-
尝试解决本书中的练习题
复习基础计算机科学概念
Show steps
复习计算机科学基础知识，例如数据结构和算法，可以帮助加强你在 AI 和 ML 领域的理解。
Show steps
-
回顾数据结构的类型和操作
-
练习使用常见算法来解决问题
-
阅读有关计算机科学原理的文章或书籍
探索 Google Cloud AI 开发工具教程
Show steps
通过探索 Google Cloud AI 开发人员文档和教程，熟悉 AI 开发工具。
Show steps
-
查找预训练的 API 和无代码/低代码解决方案的教程
-
探索机器学习工作流和生成式 AI 的教程
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Follow tutorials on Google Cloud AutoML
Show steps
Familiarize yourself with a real-time used in AI development that can make your learning more efficient and productive.
Browse courses on
AutoML
Show steps
-
Choose a tutorial on Google Cloud AutoML
-
Follow the steps in the tutorial
-
Experiment with the different features of AutoML
Build a machine learning model using BigQuery ML
Show steps
Practice building machine learning models using a popular tool to reinforce your understanding of the model building process.
Browse courses on
Machine Learning Models
Show steps
-
Import your data into BigQuery
-
Create a machine learning model using BigQuery ML
-
Evaluate the performance of your model
学习使用 Google Cloud AI/ML 平台
Show steps
熟悉 Google Cloud 提供的 AI/ML 平台和工具可以让你更有效地应用理论知识。
Show steps
-
完成 Google Cloud AI/ML 学习路径
-
观看有关 Google Cloud AI/ML 服务的视频教程
-
使用 Google Cloud AI/ML 沙盒进行实验
寻找人工智能开发领域的导师
Show steps
接触经验丰富的 AI 开发者，获得指导和支持，以提升技能。
Show steps
-
参加 AI 社区活动或会议
-
通过 LinkedIn 或其他专业网络平台联系专业人士
Develop a machine learning workflow using Vertex AI
Show steps
Create a machine learning workflow to gain hands-on experience in the end-to-end process of building and deploying machine learning models.
Browse courses on
Machine Learning Workflow
Show steps
-
Design your machine learning workflow
-
Create a Vertex AI pipeline
-
Deploy your machine learning model
构建机器学习模型练习
Show steps
通过在 Google Cloud AI Platform 上构建几个机器学习模型，增强实际操作技能。
Show steps
-
使用 BigQuery ML 构建机器学习模型
-
使用 AutoML 构建一个图像分类模型
-
使用 Vertex AI Custom Training 构建一个时间序列预测模型
参加机器学习或人工智能竞赛
Show steps
通过参加机器学习或人工智能竞赛，在实战环境中测试技能和知识。
Show steps
-
在 Kaggle 或其他平台上寻找机器学习或人工智能竞赛
-
组建一支团队或单独参加比赛
-
使用 Google Cloud AI 开发工具解决问题
Build a Generative AI project using Generative AI Studio
Show steps
Create a Generative AI project to gain practical experience in using this new and exciting technology.
Browse courses on
Generative AI
Show steps
-
Choose a Generative AI project idea
-
Create a Generative AI Studio account
-
Build your Generative AI project
为 Google Cloud AI 开源项目做出贡献
Show steps
通过为 Google Cloud AI 开源项目做出贡献，加深对 AI 开发工具的理解。
Show steps
-
查找 Google Cloud AI 存储库中的开放问题或功能请求
-
为问题提供解决方案或创建功能请求
-
提交拉取请求并与项目维护者合作
阅读《深度学习》
Show steps
阅读《深度学习》可以深入了解深度学习的基础原理和技术。
View
深度學習
on Amazon
Show steps
Show steps
Show steps
- 阅读本书的每一章
- 总结关键概念和算法
- 尝试解决本书中的练习题
复习基础计算机科学概念
Show steps
复习计算机科学基础知识，例如数据结构和算法，可以帮助加强你在 AI 和 ML 领域的理解。
Show steps
Show steps
Show steps
- 回顾数据结构的类型和操作
- 练习使用常见算法来解决问题
- 阅读有关计算机科学原理的文章或书籍
探索 Google Cloud AI 开发工具教程
Show steps
通过探索 Google Cloud AI 开发人员文档和教程，熟悉 AI 开发工具。
Show steps
Show steps
Show steps
- 查找预训练的 API 和无代码/低代码解决方案的教程
- 探索机器学习工作流和生成式 AI 的教程
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Follow tutorials on Google Cloud AutoML
Show steps
Familiarize yourself with a real-time used in AI development that can make your learning more efficient and productive.
Browse courses on
AutoML
Show steps
Show steps
Show steps
- Choose a tutorial on Google Cloud AutoML
- Follow the steps in the tutorial
- Experiment with the different features of AutoML
Build a machine learning model using BigQuery ML
Show steps
Practice building machine learning models using a popular tool to reinforce your understanding of the model building process.
Browse courses on
Machine Learning Models
Show steps
Show steps
Show steps
- Import your data into BigQuery
- Create a machine learning model using BigQuery ML
- Evaluate the performance of your model
学习使用 Google Cloud AI/ML 平台
Show steps
熟悉 Google Cloud 提供的 AI/ML 平台和工具可以让你更有效地应用理论知识。
Show steps
Show steps
Show steps
- 完成 Google Cloud AI/ML 学习路径
- 观看有关 Google Cloud AI/ML 服务的视频教程
- 使用 Google Cloud AI/ML 沙盒进行实验
寻找人工智能开发领域的导师
Show steps
接触经验丰富的 AI 开发者，获得指导和支持，以提升技能。
Show steps
Show steps
Show steps
- 参加 AI 社区活动或会议
- 通过 LinkedIn 或其他专业网络平台联系专业人士
Develop a machine learning workflow using Vertex AI
Show steps
Create a machine learning workflow to gain hands-on experience in the end-to-end process of building and deploying machine learning models.
Browse courses on
Machine Learning Workflow
Show steps
Show steps
Show steps
- Design your machine learning workflow
- Create a Vertex AI pipeline
- Deploy your machine learning model
构建机器学习模型练习
Show steps
通过在 Google Cloud AI Platform 上构建几个机器学习模型，增强实际操作技能。
Show steps
Show steps
Show steps
- 使用 BigQuery ML 构建机器学习模型
- 使用 AutoML 构建一个图像分类模型
- 使用 Vertex AI Custom Training 构建一个时间序列预测模型
参加机器学习或人工智能竞赛
Show steps
通过参加机器学习或人工智能竞赛，在实战环境中测试技能和知识。
Show steps
Show steps
Show steps
- 在 Kaggle 或其他平台上寻找机器学习或人工智能竞赛
- 组建一支团队或单独参加比赛
- 使用 Google Cloud AI 开发工具解决问题
Build a Generative AI project using Generative AI Studio
Show steps
Create a Generative AI project to gain practical experience in using this new and exciting technology.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Choose a Generative AI project idea
- Create a Generative AI Studio account
- Build your Generative AI project
为 Google Cloud AI 开源项目做出贡献
Show steps
通过为 Google Cloud AI 开源项目做出贡献，加深对 AI 开发工具的理解。
Show steps
Show steps
Show steps
- 查找 Google Cloud AI 存储库中的开放问题或功能请求
- 为问题提供解决方案或创建功能请求
- 提交拉取请求并与项目维护者合作
Career center
Learners who complete Introduction to AI and Machine Learning on GC - 简体中文 will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
As a Machine Learning Engineer, your work involves the research, development, and implementation of a wide variety of tasks relating to machine learning. This includes developing models, writing code to train and evaluate models, and building systems to deploy models into production. Due to the increasing demand for this role and the high salaries associated, many individuals make career pivots into Machine Learning Engineering. Whether you are a Machine Learning Engineer eager to get started with Google Cloud or a learner who wants to try out Machine Learning Engineering for the first time, this class will help you achieve your goals.
Data Scientist
Data Scientist
Data Scientists leverage their expertise in statistics and machine learning techniques in order to help businesses understand data better. A Data Scientist is needed to make data-driven decisions that impact the future direction of a business. This course covers the skills you need to become a successful Data Scientist, including how to build models, create visualizations, and communicate insights to stakeholders.
Software Engineer
Software Engineer
In the field of Software Engineering, AI is often utilized to build features quicker, such as automating coding-based tasks. A Software Engineer can use AI to save time and effort and to enhance their productivity. This course is effective for those Software Engineers that want to apply AI to their current work.
Data Analyst
Data Analyst
Data Analysts use their skills to clean, interpret, and present data to stakeholders, and to do this, they often use AI. In this course, you will learn how to use AI to automate data analysis tasks, which will save time and allow you to focus on more complex tasks.
AI Engineer
AI Engineer
An AI Engineer uses their knowledge of AI to design, develop, and maintain AI systems. This role combines elements of Software Engineering with skills related to Machine Learning. This course is helpful for anyone who is looking to enter the field of AI Engineering by providing a solid foundation in the fundamentals of AI.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematics and statistics to analyze data in order to help make informed investment decisions. AI techniques are often used for the analysis of large datasets and for finding patterns and relationships in complex data. This course will be useful for those seeking a career in Quantitative Analysis.
Business Analyst
Business Analyst
In the field of Business Analysis, AI can be utilized to explore and analyze data. This information can help stakeholders better understand how to make informed decisions that will help the business grow. This course can help Business Analysts to develop the skills needed to stay competitive in this evolving field.
Computer Vision Engineer
Computer Vision Engineer
Someone who works as a Computer Vision Engineer may use AI to design and develop systems that can analyze images and videos to gain insights. This course may be useful for someone in this field because it covers topics such as how to build models for image and video analysis, and how to deploy these models to the cloud.
Natural Language Processing Engineer
Natural Language Processing Engineer
A Natural Language Processing Engineer designs and develops systems for the processing of text and speech data. AI is used to develop applications such as chatbots, language translation, and text summarization. This course is relevant for the role of Natural Language Processing Engineer because it focuses on how to use AI to build models for natural language processing tasks.
Cybersecurity Analyst
Cybersecurity Analyst
AI is often utilized in cybersecurity to detect and respond to threats and protect data from unauthorized access. This course covers topics like how to use AI to build models to detect fraud and identify malicious activity. Anyone working in Cybersecurity will find this course to be helpful in building the necessary skills to be successful.
Cloud Architect
Cloud Architect
A Cloud Architect plans, designs, and manages cloud computing systems. AI can be used to optimize cloud infrastructure and to automate tasks. This course will be helpful for those who want to become a Cloud Architect with a focus on AI.
Database Administrator
Database Administrator
A Database Administrator is responsible for the planning, implementation, and maintenance of a database system. AI can be used for tasks such as data backup and recovery, performance tuning, and database security. This course can help Database Administrators to develop the skills needed to manage AI-powered database systems.
Product Manager
Product Manager
Product Managers utilize their business knowledge and technical expertise to bring new products to market. AI can be used to improve product development and marketing strategies. This course can help Product Managers to learn how to use AI to better understand customer needs, develop more innovative products, and improve product adoption.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to solve real-world problems in various industries. AI techniques are often used to develop optimization models and to assist in decision-making. This course will be helpful for those seeking a career in Operations Research Analysis, as it provides a foundation in AI techniques.
Financial Analyst
Financial Analyst
Financial Analysts provide financial advice to clients and help them make sound investment decisions. AI can be used to analyze financial data, identify trends, and make predictions. This course is useful for Financial Analysts who want to use AI to improve their analysis and forecasting capabilities.
For more career information including salaries, visit:
OpenCourser.com/course/08n813/introduction
Reading list
We've selected 12 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
Introduction to AI and Machine Learning on GC - 简体中文.
Save
本书提供了一本全面的自然语言处理指南。涵盖了自然语言处理的各种任务和技术。
本书提供了一本综合指南，介绍机器学习背后的原理和技术。机器学习的基础知识、算法和应用程序都得到了详细的解释。
Provides a practical guide to machine learning, with a focus on using popular libraries such as Scikit-Learn, Keras, and TensorFlow. It covers a wide range of topics, from data preprocessing to model evaluation.
Provides a comprehensive overview of artificial intelligence, with a focus on cognitive science. It covers a wide range of topics, from logic and reasoning to machine learning.
Provides a comprehensive overview of natural language processing, with a focus on using Python. It covers a wide range of topics, from text preprocessing to machine learning.
Save
Provides a comprehensive overview of computer vision, with a focus on algorithms and applications. It covers a wide range of topics, from image processing to object recognition.
Provides a comprehensive overview of reinforcement learning, with a focus on the mathematical foundations. It valuable resource for researchers and practitioners in the field.
Provides a comprehensive overview of probabilistic graphical models, with a focus on the mathematical foundations. It valuable resource for researchers and practitioners in the field.
Provides a comprehensive overview of Bayesian reasoning and machine learning, with a focus on the mathematical foundations. It valuable resource for researchers and practitioners in the field.
Provides a comprehensive overview of machine learning, with a focus on the probabilistic perspective. It valuable resource for researchers and practitioners in the field.
Save
Provides a comprehensive and in-depth overview of deep learning, covering the latest techniques and algorithms. It valuable resource for researchers and practitioners in the field.
Save
Provides a practical guide to data mining, with a focus on machine learning techniques. It covers a wide range of topics, from data preprocessing to model evaluation.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/08n813/introduction
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Level
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Via
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Institution
Google Cloud
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Google Cloud Training
Language
中文
Transcript
English
Good to know
适合数据科学家、AI 开发者和机器学习工程师。
介绍了 Google Cloud 中用于 AI 和机器学习的各种服务和技术。
涵盖了从 AI 基础到 AI 开发工作流的广泛主题。
由 Google Cloud Training 提供，说明其在 AI 领域拥有丰富的经验和专业知识。
提供基于代码的解决方案、预训练的 API 和无代码/低代码解决方案，以迎合不同技能水平的开发人员。
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