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Karen Hebel
and
Huimin Yang
Discover the power of artificial intelligence on Google Cloud Platform (GCP). Learn to build machine learning models with Vertex AI, analyze language data, and unleash the creativity of generative AI.
Prerequisite details
Read more
Discover the power of artificial intelligence on Google Cloud Platform (GCP). Learn to build machine learning models with Vertex AI, analyze language data, and unleash the creativity of generative AI.
Prerequisite details
Read more
Discover the power of artificial intelligence on Google Cloud Platform (GCP). Learn to build machine learning models with Vertex AI, analyze language data, and unleash the creativity of generative AI.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Google cloud fundamentals
- Basic Python
- Google cloud platform proficiency
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/3i9f3g/google
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What's inside
Syllabus
This lesson covers the essential features of Google Cloud's suite of AI and Machine Learning services including hands-on practice with Vertex AI and related APIs.
In this lesson, you will learn different tasks in natural language processing and perform them using Google Cloud services.
This lesson provides hands-on instruction and practice with prompt engineering, prompt design, and fine-tuning using Google Cloud's Generative AI Studio.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Delves into core elements of Google Cloud's AI suite
Covers natural language processing with practical Google Cloud service applications
Provides comprehensive and hands-on experience with Google Cloud's Generative AI Studio
Assumes some familiarity with Google Cloud fundamentals, basic Python, and Google Cloud Platform proficiency
Requires fluency in written and spoken English
Save this course
Save Google Cloud: AI Fundamentals to your list so you can find it easily later:
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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 Google Cloud: AI Fundamentals with these
activities:
Review 'Hands-On Machine Learning with Google Cloud Platform'
Show steps
This book provides a comprehensive overview of machine learning concepts and techniques, and it will help you to understand the fundamentals of machine learning and how to apply them using Google Cloud Platform.
View
Hands-On Machine Learning with Scikit-Learn,...
on Amazon
Show steps
-
Read chapters 1-3
-
Complete the exercises in chapters 1-3
-
Create a simple machine learning model using Google Cloud Platform
Review Python basics
Show steps
Reinforce your understanding of Python syntax and data structures to prepare for the course's coding assignments.
Browse courses on
Python
Show steps
-
Revisit a Python tutorial or online course.
-
Practice writing simple Python scripts to manipulate data and perform basic operations.
Review Cloud fundamentals
Show steps
Refresh your knowledge of cloud computing principles and services to enhance your understanding of GCP.
Browse courses on
Google Cloud Fundamentals
Show steps
-
Review official Google Cloud documentation or online resources on cloud computing.
-
Attend a webinar or workshop on Google Cloud Platform.
-
Create a free Google Cloud account and explore the console interface.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Volunteer at a machine learning organization
Show steps
Volunteering at a machine learning organization will give you the opportunity to apply your skills to real-world problems and to make a difference in the community.
Browse courses on
Machine Learning
Show steps
-
Find a machine learning organization
-
Contact the organization and inquire about volunteer opportunities
-
Volunteer at the organization
Join a study group
Show steps
Joining a study group will give you the opportunity to discuss the course material with other students and to get help with difficult concepts.
Browse courses on
Machine Learning
Show steps
-
Find a study group
-
Attend study group meetings
-
Participate in discussions
Complete hands-on Vertex AI exercises
Show steps
Gain practical experience with Vertex AI by working through guided exercises and tutorials.
Browse courses on
Vertex AI
Show steps
-
Access the Vertex AI Quickstart guide or sample notebooks.
-
Follow the instructions to train and deploy a machine learning model using Vertex AI.
-
Experiment with different model parameters and configurations.
Review Machine Learning Concepts
Show steps
Refresh your understanding of basic machine learning concepts to strengthen your foundation for the course.
Browse courses on
Machine Learning Fundamentals
Show steps
-
Review key terms and algorithms
-
Practice solving machine learning problems
Explore natural language processing with NLP APIs
Show steps
Develop proficiency in using Google Cloud's NLP APIs for tasks like text analysis and sentiment analysis.
Browse courses on
Natural Language Processing
Show steps
-
Identify the relevant NLP API for your specific use case.
-
Use the API documentation and code samples to integrate the API into your project.
-
Test the API with real-world data and analyze the results.
Follow the Google Cloud AI Platform tutorials
Show steps
These tutorials will provide you with hands-on experience with Google Cloud AI Platform services, and they will help you to learn how to build and deploy machine learning models.
Browse courses on
Google Cloud AI Platform
Show steps
-
Complete the 'Machine Learning Crash Course' tutorial
-
Complete the 'Natural Language Processing with Python' tutorial
-
Complete the 'Generative AI with Google Cloud' tutorial
Solve machine learning coding problems
Show steps
Solving coding problems will help you to develop your problem-solving skills and to improve your understanding of machine learning algorithms.
Browse courses on
Machine Learning
Show steps
-
Find a set of machine learning coding problems
-
Solve the problems
-
Review your solutions
Build a chatbot using Generative AI
Show steps
Enhance your understanding of generative AI by creating a practical application.
Browse courses on
Generative AI
Show steps
-
Choose a specific domain or topic for your chatbot.
-
Use Generative AI Studio to train a chatbot model.
-
Deploy your chatbot and evaluate its performance.
Build a machine learning model to predict housing prices
Show steps
This project will give you the opportunity to apply the machine learning concepts and techniques that you have learned in this course to a real-world problem.
Browse courses on
Machine Learning
Show steps
-
Gather data on housing prices
-
Clean and prepare the data
-
Build a machine learning model to predict housing prices
-
Evaluate the performance of the model
-
Deploy the model
Contribute to a machine learning open-source project
Show steps
Deepen your understanding of machine learning and contribute to the community by working on open-source projects.
Browse courses on
Machine Learning
Show steps
-
Identify an open-source machine learning project that aligns with your interests.
-
Contribute to the project by submitting bug reports, code changes, or documentation.
-
Engage with the project community through discussions and online forums.
Write a report on your machine learning project
Show steps
This report will help you to consolidate your learning and to demonstrate your understanding of the machine learning concepts and techniques that you have learned in this course.
Browse courses on
Machine Learning
Show steps
-
Describe the problem that you are trying to solve
-
Describe the data that you used
-
Describe the machine learning model that you built
-
Evaluate the performance of the model
-
Discuss the implications of your findings
Create a blog post or video tutorial on a machine learning topic
Show steps
Creating a blog post or video tutorial will help you to consolidate your learning and to share your knowledge with others.
Browse courses on
Machine Learning
Show steps
-
Choose a machine learning topic
-
Research the topic
-
Write a blog post or create a video tutorial
-
Publish your blog post or video tutorial
Review 'Hands-On Machine Learning with Google Cloud Platform'
Show steps
This book provides a comprehensive overview of machine learning concepts and techniques, and it will help you to understand the fundamentals of machine learning and how to apply them using Google Cloud Platform.
View
Hands-On Machine Learning with Scikit-Learn,...
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3
- Complete the exercises in chapters 1-3
- Create a simple machine learning model using Google Cloud Platform
Review Python basics
Show steps
Reinforce your understanding of Python syntax and data structures to prepare for the course's coding assignments.
Browse courses on
Python
Show steps
Show steps
Show steps
- Revisit a Python tutorial or online course.
- Practice writing simple Python scripts to manipulate data and perform basic operations.
Review Cloud fundamentals
Show steps
Refresh your knowledge of cloud computing principles and services to enhance your understanding of GCP.
Browse courses on
Google Cloud Fundamentals
Show steps
Show steps
Show steps
- Review official Google Cloud documentation or online resources on cloud computing.
- Attend a webinar or workshop on Google Cloud Platform.
- Create a free Google Cloud account and explore the console interface.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Volunteer at a machine learning organization
Show steps
Volunteering at a machine learning organization will give you the opportunity to apply your skills to real-world problems and to make a difference in the community.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find a machine learning organization
- Contact the organization and inquire about volunteer opportunities
- Volunteer at the organization
Join a study group
Show steps
Joining a study group will give you the opportunity to discuss the course material with other students and to get help with difficult concepts.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find a study group
- Attend study group meetings
- Participate in discussions
Complete hands-on Vertex AI exercises
Show steps
Gain practical experience with Vertex AI by working through guided exercises and tutorials.
Browse courses on
Vertex AI
Show steps
Show steps
Show steps
- Access the Vertex AI Quickstart guide or sample notebooks.
- Follow the instructions to train and deploy a machine learning model using Vertex AI.
- Experiment with different model parameters and configurations.
Review Machine Learning Concepts
Show steps
Refresh your understanding of basic machine learning concepts to strengthen your foundation for the course.
Browse courses on
Machine Learning Fundamentals
Show steps
Show steps
Show steps
- Review key terms and algorithms
- Practice solving machine learning problems
Explore natural language processing with NLP APIs
Show steps
Develop proficiency in using Google Cloud's NLP APIs for tasks like text analysis and sentiment analysis.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Identify the relevant NLP API for your specific use case.
- Use the API documentation and code samples to integrate the API into your project.
- Test the API with real-world data and analyze the results.
Follow the Google Cloud AI Platform tutorials
Show steps
These tutorials will provide you with hands-on experience with Google Cloud AI Platform services, and they will help you to learn how to build and deploy machine learning models.
Browse courses on
Google Cloud AI Platform
Show steps
Show steps
Show steps
- Complete the 'Machine Learning Crash Course' tutorial
- Complete the 'Natural Language Processing with Python' tutorial
- Complete the 'Generative AI with Google Cloud' tutorial
Solve machine learning coding problems
Show steps
Solving coding problems will help you to develop your problem-solving skills and to improve your understanding of machine learning algorithms.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find a set of machine learning coding problems
- Solve the problems
- Review your solutions
Build a chatbot using Generative AI
Show steps
Enhance your understanding of generative AI by creating a practical application.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Choose a specific domain or topic for your chatbot.
- Use Generative AI Studio to train a chatbot model.
- Deploy your chatbot and evaluate its performance.
Build a machine learning model to predict housing prices
Show steps
This project will give you the opportunity to apply the machine learning concepts and techniques that you have learned in this course to a real-world problem.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Gather data on housing prices
- Clean and prepare the data
- Build a machine learning model to predict housing prices
- Evaluate the performance of the model
- Deploy the model
Contribute to a machine learning open-source project
Show steps
Deepen your understanding of machine learning and contribute to the community by working on open-source projects.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Identify an open-source machine learning project that aligns with your interests.
- Contribute to the project by submitting bug reports, code changes, or documentation.
- Engage with the project community through discussions and online forums.
Write a report on your machine learning project
Show steps
This report will help you to consolidate your learning and to demonstrate your understanding of the machine learning concepts and techniques that you have learned in this course.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Describe the problem that you are trying to solve
- Describe the data that you used
- Describe the machine learning model that you built
- Evaluate the performance of the model
- Discuss the implications of your findings
Create a blog post or video tutorial on a machine learning topic
Show steps
Creating a blog post or video tutorial will help you to consolidate your learning and to share your knowledge with others.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Choose a machine learning topic
- Research the topic
- Write a blog post or create a video tutorial
- Publish your blog post or video tutorial
Career center
Learners who complete Google Cloud: AI Fundamentals will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst collects, transforms, and analyzes data to extract insights and inform decision-making. Google Cloud: AI Fundamentals teaches you AI and Machine Learning through its foundational concepts and practical use cases, a valuable skill set for a Data Analyst seeking to excel in their role. This course introduces you to Vertex AI and other Google Cloud services, providing a strong foundation for building machine learning models. The course also covers generative AI, an emerging field that empowers you to unlock the creativity of AI.
Data Scientist
Data Scientist
A Data Scientist applies scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. Google Cloud: AI Fundamentals provides a comprehensive introduction to AI and Machine Learning on Google Cloud. It introduces you to Vertex AI, Google Cloud's suite of AI and Machine Learning services. Throughout the course, you will gain hands-on experience with these services through practical exercises, enabling you to build and deploy machine learning models and leverage natural language processing and generative AI.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models to solve real-world problems. Google Cloud: AI Fundamentals is an excellent foundation for Machine Learning Engineers. It offers a comprehensive overview of AI and Machine Learning concepts, with a focus on practical application on Google Cloud. The course covers Vertex AI, Google Cloud's MLOps platform, enabling you to build, train, and deploy machine learning models efficiently.
Natural Language Processing Engineer
Natural Language Processing Engineer
A Natural Language Processing Engineer develops and applies techniques to analyze and generate human language data. Google Cloud: AI Fundamentals provides a solid foundation for Natural Language Processing Engineers. The course covers natural language processing tasks and how to perform them using Google Cloud services, including sentiment analysis, named entity recognition, and text classification. This knowledge is essential for building effective natural language processing applications.
Generative AI Engineer
Generative AI Engineer
A Generative AI Engineer designs and develops models that can generate new data or creative content. Google Cloud: AI Fundamentals is a valuable course for Generative AI Engineers. It provides a comprehensive overview of AI and Machine Learning concepts, with a focus on practical application on Google Cloud. The course covers generative AI, including prompt engineering and fine-tuning, empowering you to build and deploy generative AI models.
AI Architect
AI Architect
An AI Architect designs and implements AI solutions to solve complex business problems. Google Cloud: AI Fundamentals provides a strong foundation for AI Architects. The course covers the essential features of Google Cloud's AI and Machine Learning services, including Vertex AI and related APIs. This knowledge is critical for designing and implementing effective AI solutions on Google Cloud.
Computer Vision Engineer
Computer Vision Engineer
A Computer Vision Engineer designs and develops computer vision systems to interpret and understand visual data. Knowledge of AI and Machine Learning is essential for Computer Vision Engineers, and Google Cloud: AI Fundamentals provides a solid foundation in these areas. The course covers the essential features of Google Cloud's AI and Machine Learning services, including Vertex AI and related APIs, enabling Computer Vision Engineers to build and deploy computer vision models on Google Cloud.
AI Product Manager
AI Product Manager
An AI Product Manager leads the development and launch of AI products. Google Cloud: AI Fundamentals provides AI Product Managers with a deep understanding of AI and Machine Learning concepts. The course covers the essential features of Google Cloud's AI and Machine Learning services, including Vertex AI and related APIs. This knowledge empowers AI Product Managers to make informed decisions about AI product development and effectively communicate with technical teams.
AI Researcher
AI Researcher
An AI Researcher explores and develops new AI algorithms and techniques. Google Cloud: AI Fundamentals provides a strong foundation for AI Researchers. The course covers the essential features of Google Cloud's AI and Machine Learning services, including Vertex AI and related APIs. This knowledge enables AI Researchers to leverage Google Cloud's infrastructure and services to conduct their research and develop innovative AI solutions.
AI Consultant
AI Consultant
An AI Consultant advises organizations on how to adopt and implement AI solutions. Google Cloud: AI Fundamentals provides AI Consultants with a comprehensive understanding of AI and Machine Learning on Google Cloud. The course covers the essential features of Google Cloud's AI and Machine Learning services, including Vertex AI and related APIs. This knowledge enables AI Consultants to effectively guide organizations in their AI adoption and implementation journey.
Machine Learning Developer
Machine Learning Developer
A Machine Learning Developer builds and maintains machine learning models. Google Cloud: AI Fundamentals provides Machine Learning Developers with a solid foundation in AI and Machine Learning. The course covers the essential features of Google Cloud's AI and Machine Learning services, including Vertex AI and related APIs. This knowledge enables Machine Learning Developers to build, deploy, and maintain machine learning models on Google Cloud.
Data Engineer
Data Engineer
A Data Engineer designs and builds data pipelines to support data analysis and machine learning. Knowledge of AI and Machine Learning is increasingly important for Data Engineers, and Google Cloud: AI Fundamentals provides a solid foundation in these areas. The course covers the essential features of Google Cloud's AI and Machine Learning services, including Vertex AI and related APIs, enabling Data Engineers to build data pipelines that integrate with AI and Machine Learning applications.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. Google Cloud: AI Fundamentals provides Software Engineers with a solid foundation in AI and Machine Learning on Google Cloud. The course covers the essential features of Google Cloud's AI and Machine Learning services, including Vertex AI and related APIs. This knowledge enables Software Engineers to incorporate AI and Machine Learning into their software systems and build more intelligent applications.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst collects, analyzes, and interprets data to provide insights and inform decision-making. Google Cloud: AI Fundamentals provides Business Intelligence Analysts with a solid foundation in AI and Machine Learning. The course covers the essential features of Google Cloud's AI and Machine Learning services, including Vertex AI and related APIs. This knowledge enables Business Intelligence Analysts to leverage AI and Machine Learning to extract deeper insights from data and provide more valuable recommendations.
Data Scientist (Healthcare)
Data Scientist (Healthcare)
A Data Scientist (Healthcare) applies AI and Machine Learning techniques to solve problems in the healthcare industry. Google Cloud: AI Fundamentals provides a strong foundation for Data Scientists (Healthcare). The course covers the essential features of Google Cloud's AI and Machine Learning services, including Vertex AI and related APIs. This knowledge empowers Data Scientists (Healthcare) to develop and deploy AI solutions that improve patient care, streamline healthcare operations, and drive innovation in the healthcare industry.
For more career information including salaries, visit:
OpenCourser.com/course/3i9f3g/google
Reading list
We've selected six 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
Google Cloud: AI Fundamentals.
Save
A comprehensive and advanced textbook on deep learning, covering theoretical foundations, architectures, and applications. It provides a deep understanding of the field for researchers and practitioners.
Save
A comprehensive textbook on generative AI, covering theoretical foundations, models, and applications. It provides a deep understanding of the field for researchers and practitioners.
A comprehensive guide to machine learning using Python, covering a wide range of techniques and libraries. It provides practical examples and insights for those working with ML and data analysis.
A practical guide to natural language processing, using Python. It covers a wide range of techniques and applications, making it a valuable resource for those working with language data.
A practical guide to machine learning using R, covering a wide range of techniques and libraries. It provides hands-on experience for those working with ML and data analysis.
A beginner-friendly guide to Google Cloud Platform, providing an overview of key services and use cases. It provides a good starting point for those new to cloud computing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3i9f3g/google
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Effort
15 hours
Via
Udacity
Instructors
Karen Hebel
Huimin Yang
Language
English
Good to know
Delves into core elements of Google Cloud's AI suite
Covers natural language processing with practical Google Cloud service applications
Provides comprehensive and hands-on experience with Google Cloud's Generative AI Studio
Assumes some familiarity with Google Cloud fundamentals, basic Python, and Google Cloud Platform proficiency
Requires fluency in written and spoken English
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