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This course introduces the artificial intelligence (AI) and machine learning (ML) offerings on Google Cloud that support the data-to-AI lifecycle through AI foundations, AI development, and AI solutions.
Read more
This course introduces the artificial intelligence (AI) and machine learning (ML) offerings on Google Cloud that support the data-to-AI lifecycle through AI foundations, AI development, and AI solutions.
Read more
This course introduces the artificial intelligence (AI) and machine learning (ML) offerings on Google Cloud that support the data-to-AI lifecycle through AI foundations, AI development, and AI solutions.
This course introduces the artificial intelligence (AI) and machine learning (ML) offerings on Google Cloud that support the data-to-AI lifecycle through AI foundations, AI development, and AI solutions. It explores the technologies, products, and tools available to build an ML model, an ML pipeline, and a generative AI project based on the different goals of users, including data scientists, AI developers, and ML engineers.
Register for this course and see more details by visiting:
OpenCourser.com/course/7yp20g/introduction
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What's inside
Syllabus
Introduction
AI Foundations
AI Development Options
AI Development Workflow
Read more
Syllabus
Introduction
AI Foundations
AI Development Options
AI Development Workflow
Read more
Generative AI
Summary
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches data-to-AI lifecycle, which is the logical progression of AI application development
Covers in-demand AI technologies, including its foundations, model development, and AI solutions
Provides hands-on practice through AI tools and technologies from Google Cloud, a leader in the AI industry
Suitable for learners aiming to build a career in AI, including data scientists, AI developers, and ML engineers
Taught by experts from Google Cloud, ensuring the delivery of up-to-date and industry-relevant knowledge
Requires a foundational understanding of AI and ML concepts, making it suitable for learners with some prior knowledge
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Save Introduction to AI and Machine Learning on Google Cloud 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 Introduction to AI and Machine Learning on Google Cloud with these
activities:
Connect with an experienced AI professional
Show steps
Gain valuable insights from an expert in the field of AI.
Show steps
-
Reach out to AI professionals on LinkedIn or attend industry events
-
Request informational interviews or mentorship opportunities
Understanding AI and Machine Learning Concepts
Show steps
Provide background knowledge on the foundational concepts of AI and ML.
View
Hands-On Machine Learning with Scikit-Learn,...
on Amazon
Show steps
-
Read the book's introduction and chapter 1
Learn about AI development
Show steps
Reinforce concepts related to AI development options.
Show steps
-
Explore Google Cloud documentation on AI development options
-
Follow tutorials on building an ML model or pipeline
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete ML exercises
Show steps
Improve your practical skills in ML.
Show steps
-
Solve ML coding exercises on platforms like HackerRank or LeetCode
-
Participate in Kaggle competitions
Attend an ML workshop
Show steps
Gain hands-on experience with ML technologies.
Show steps
-
Find and register for an ML workshop that aligns with your interests
-
Attend the workshop and actively participate in exercises
Develop an AI solution for a real-world problem
Show steps
Apply your knowledge of AI development to a practical problem.
Show steps
-
Identify a problem that can be solved using AI
-
Design and implement an AI solution
-
Deploy and evaluate your solution
Participate in an AI hackathon
Show steps
Challenge yourself and push your AI development skills.
Show steps
-
Form a team or join an existing one
-
Develop an innovative AI solution during the hackathon
Connect with an experienced AI professional
Show steps
Gain valuable insights from an expert in the field of AI.
Show steps
Show steps
Show steps
- Reach out to AI professionals on LinkedIn or attend industry events
- Request informational interviews or mentorship opportunities
Understanding AI and Machine Learning Concepts
Show steps
Provide background knowledge on the foundational concepts of AI and ML.
View
Hands-On Machine Learning with Scikit-Learn,...
on Amazon
Show steps
Show steps
Show steps
- Read the book's introduction and chapter 1
Learn about AI development
Show steps
Reinforce concepts related to AI development options.
Show steps
Show steps
Show steps
- Explore Google Cloud documentation on AI development options
- Follow tutorials on building an ML model or pipeline
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete ML exercises
Show steps
Improve your practical skills in ML.
Show steps
Show steps
Show steps
- Solve ML coding exercises on platforms like HackerRank or LeetCode
- Participate in Kaggle competitions
Attend an ML workshop
Show steps
Gain hands-on experience with ML technologies.
Show steps
Show steps
Show steps
- Find and register for an ML workshop that aligns with your interests
- Attend the workshop and actively participate in exercises
Develop an AI solution for a real-world problem
Show steps
Apply your knowledge of AI development to a practical problem.
Show steps
Show steps
Show steps
- Identify a problem that can be solved using AI
- Design and implement an AI solution
- Deploy and evaluate your solution
Participate in an AI hackathon
Show steps
Challenge yourself and push your AI development skills.
Show steps
Show steps
Show steps
- Form a team or join an existing one
- Develop an innovative AI solution during the hackathon
Career center
Learners who complete Introduction to AI and Machine Learning on Google Cloud will develop knowledge and skills
that may be useful to these careers:
AI Researcher
AI Researcher
AI Researchers work on the development of new AI algorithms and techniques. An Introduction to AI and Machine Learning on Google Cloud provides a foundation in AI and ML that is essential for this role. This course can help AI Researchers to stay up-to-date on the latest developments in AI and ML, and to develop the skills they need to conduct AI research.
AI Product Manager
AI Product Manager
AI Product Managers are responsible for the development and management of AI products. An Introduction to AI and Machine Learning on Google Cloud provides the foundation in AI and ML that is essential for this role. This course can help AI Product Managers to stay up-to-date on the latest developments in AI and ML, and to develop the skills they need to develop and manage AI products.
AI Architect
AI Architect
AI Architects design and develop AI systems. An Introduction to AI and Machine Learning on Google Cloud provides the foundation in AI and ML that is essential for this role. This course can help AI Architects to stay up-to-date on the latest developments in AI and ML, and to develop the skills they need to design and develop AI systems.
AI Business Analyst
AI Business Analyst
AI Business Analysts help organizations to understand and use AI. An Introduction to AI and Machine Learning on Google Cloud provides the foundation in AI and ML that is essential for this role. This course can help AI Business Analysts to stay up-to-date on the latest developments in AI and ML, and to develop the skills they need to help organizations to understand and use AI.
AI Teacher
AI Teacher
AI Teachers educate others about AI. An Introduction to AI and Machine Learning on Google Cloud provides the foundation in AI and ML that is essential for this role. This course can help AI Teachers to stay up-to-date on the latest developments in AI and ML, and to develop the skills they need to educate others about AI.
AI Evangelist
AI Evangelist
AI Evangelists promote the adoption of AI. An Introduction to AI and Machine Learning on Google Cloud provides the foundation in AI and ML that is essential for this role. This course can help AI Evangelists to stay up-to-date on the latest developments in AI and ML, and to develop the skills they need to promote the adoption of AI.
Data Scientist
Data Scientist
Data Scientists use AI and ML to extract insights from data. An Introduction to AI and Machine Learning on Google Cloud can help Data Scientists develop the skills they need to build and deploy ML models. This course can help Data Scientists to work more effectively with AI and ML, and to stay up-to-date on the latest developments in the field.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers work on the development and deployment of machine learning models. An Introduction to AI and Machine Learning on Google Cloud provides the fundamental knowledge and skills needed to be successful in this role. This course can also help Machine Learning Engineers to stay up-to-date on the latest developments in AI and ML.
AI Engineer
AI Engineer
The AI Engineer is responsible for building, deploying, and monitoring AI solutions. An Introduction to AI and Machine Learning on Google Cloud provides a foundation in AI and ML, as well as practical experience in building and deploying ML models. This course can be a valuable resource for anyone looking to start or advance a career in AI engineering.
Product Manager
Product Manager
Product Managers develop and manage products. An Introduction to AI and Machine Learning on Google Cloud can be useful for Product Managers who want to use AI and ML to develop and manage AI-powered products.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. An Introduction to AI and Machine Learning on Google Cloud can be useful for Project Managers who want to use AI and ML to improve project management processes.
Business Analyst
Business Analyst
Business Analysts analyze business processes to identify opportunities for improvement. An Introduction to AI and Machine Learning on Google Cloud can be useful for Business Analysts who want to use AI and ML to improve business processes.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. An Introduction to AI and Machine Learning on Google Cloud can be useful for Software Engineers who want to develop AI-powered software applications.
Data Analyst
Data Analyst
Data Analysts analyze data to extract insights. An Introduction to AI and Machine Learning on Google Cloud can be useful for Data Analysts who want to use AI and ML to analyze data.
Marketing Manager
Marketing Manager
Marketing Managers develop and execute marketing campaigns. An Introduction to AI and Machine Learning on Google Cloud can be useful for Marketing Managers who want to use AI and ML to improve marketing campaigns.
For more career information including salaries, visit:
OpenCourser.com/course/7yp20g/introduction
Reading list
We've selected ten 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 Google Cloud.
Save
Provides a comprehensive overview of deep learning. It valuable resource for anyone looking to learn more about the theory and practice of deep learning.
Provides a practical guide to building and deploying machine learning models on Google Cloud Platform. It covers a wide range of topics, from data preparation to model evaluation, and valuable resource for anyone looking to learn more about AI and ML on Google Cloud.
Provides a comprehensive overview of statistical learning. It valuable resource for anyone looking to learn more about the theoretical foundations of ML.
Provides a comprehensive overview of machine learning from a probabilistic perspective. It valuable resource for anyone looking to learn more about the theoretical foundations of ML.
Save
Provides a practical guide to using machine learning for business applications. It valuable resource for anyone looking to learn more about the potential of ML for businesses.
Provides a practical guide to building and training deep learning models using Python. It valuable resource for anyone looking to learn more about deep learning and its applications.
Provides a practical guide to building and deploying machine learning models for a variety of tasks. It valuable resource for anyone looking to learn more about the practical applications of ML.
Provides a practical guide to building and deploying machine learning models using R. It valuable resource for anyone looking to learn more about the practical applications of ML in R.
Save
Provides a thought-provoking exploration of the potential future of humanity in the age of AI. It valuable resource for anyone looking to think more deeply about the implications of AI for our society.
Provides a clear and concise overview of the basics of artificial intelligence. It valuable resource for anyone looking to learn more about the fundamentals of AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/7yp20g/introduction
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Time
165 hours
Level
Introductory
Via
Pluralsight
Instructor
Google Cloud
Language
English
Good to know
Teaches data-to-AI lifecycle, which is the logical progression of AI application development
Covers in-demand AI technologies, including its foundations, model development, and AI solutions
Provides hands-on practice through AI tools and technologies from Google Cloud, a leader in the AI industry
Suitable for learners aiming to build a career in AI, including data scientists, AI developers, and ML engineers
Taught by experts from Google Cloud, ensuring the delivery of up-to-date and industry-relevant knowledge
Requires a foundational understanding of AI and ML concepts, making it suitable for learners with some prior knowledge
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