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Google Cloud
Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
Read more
Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
Read more
Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
Register for this course and see more details by visiting:
OpenCourser.com/course/hkph43/innovating
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What's inside
Syllabus
Course Introduction
AI and ML Fundamentals
Google Cloud’s AI and ML Solutions
Course Summary
Read more
Syllabus
Course Introduction
AI and ML Fundamentals
Google Cloud’s AI and ML Solutions
Course Summary
Read more
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops core skills in AI and ML, which are key to various industries
Taught by Google Cloud, recognized for their expertise in AI and ML
Explores AI and ML applications, which are highly relevant to business transformation
Part of Cloud Digital Leader learning path, which aligns with industry standards
Requires no previous knowledge or experience, making it accessible to various learners
Might require additional resources or tools, not readily available in all households or libraries
Save this course
Save Innovating with Google Cloud Artificial Intelligence 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 Innovating with Google Cloud Artificial Intelligence with these
activities:
Review 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow'
Show steps
Strengthen your foundational knowledge and understanding of machine learning algorithms and techniques.
View
Hands-On Machine Learning with Scikit-Learn,...
on Amazon
Show steps
-
Read and understand the key concepts presented in the book
-
Follow the hands-on exercises and implement the code
-
Review your understanding by answering the chapter questions
Volunteer as a mentor or tutor for AI or ML enthusiasts
Show steps
Share your knowledge, support others in their learning journey, and give back to the community.
Browse courses on
AI
Show steps
-
Identify a platform or organization where you can volunteer
-
Create a profile and offer your skills as a mentor or tutor
-
Connect with learners and provide guidance, support, and feedback
-
Reflect on your experiences and identify areas for self-improvement
Create a collection of AI and ML resources
Show steps
Contribute to the community by curating valuable resources and sharing them with others.
Show steps
-
Identify and gather relevant AI and ML resources
-
Organize the resources into categories or topics
-
Create a platform or repository to share the collection
-
Promote the collection to the AI and ML community
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice Python exercises on Leetcode
Show steps
Encode the AI and ML concepts learned in class into practice to improve fluidity and retention.
Show steps
-
Create a Leetcode account
-
Choose a problem set aligned with the module
-
Solve the problems in the problem set
-
Review your solutions and identify areas for improvement
Follow Google Cloud AI tutorials
Show steps
Reinforce your understanding of the course topics with hands-on examples and guided instructions.
Show steps
-
Identify a tutorial on the Google Cloud AI platform
-
Set up the tutorial environment
-
Follow the tutorial steps and complete the exercises
-
Review your results and compare them to the expected outcomes
Build a machine learning model
Show steps
Apply the AI and ML concepts learned in class to a real-world problem and build a tangible artifact.
Browse courses on
Machine Learning
Show steps
-
Define the problem and gather data
-
Select and train a machine learning model
-
Evaluate the model's performance
-
Deploy the model to a production environment
Write a blog post on an AI or ML topic
Show steps
Develop your understanding and communication skills by presenting AI and ML concepts in your own words.
Browse courses on
AI
Show steps
-
Choose an AI or ML topic to write about
-
Research the topic and gather information
-
Organize your thoughts and create an outline
-
Write the blog post
-
Proofread and publish the blog post
Review 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow'
Show steps
Strengthen your foundational knowledge and understanding of machine learning algorithms and techniques.
View
Hands-On Machine Learning with Scikit-Learn,...
on Amazon
Show steps
Show steps
Show steps
- Read and understand the key concepts presented in the book
- Follow the hands-on exercises and implement the code
- Review your understanding by answering the chapter questions
Volunteer as a mentor or tutor for AI or ML enthusiasts
Show steps
Share your knowledge, support others in their learning journey, and give back to the community.
Browse courses on
AI
Show steps
Show steps
Show steps
- Identify a platform or organization where you can volunteer
- Create a profile and offer your skills as a mentor or tutor
- Connect with learners and provide guidance, support, and feedback
- Reflect on your experiences and identify areas for self-improvement
Create a collection of AI and ML resources
Show steps
Contribute to the community by curating valuable resources and sharing them with others.
Show steps
Show steps
Show steps
- Identify and gather relevant AI and ML resources
- Organize the resources into categories or topics
- Create a platform or repository to share the collection
- Promote the collection to the AI and ML community
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice Python exercises on Leetcode
Show steps
Encode the AI and ML concepts learned in class into practice to improve fluidity and retention.
Show steps
Show steps
Show steps
- Create a Leetcode account
- Choose a problem set aligned with the module
- Solve the problems in the problem set
- Review your solutions and identify areas for improvement
Follow Google Cloud AI tutorials
Show steps
Reinforce your understanding of the course topics with hands-on examples and guided instructions.
Show steps
Show steps
Show steps
- Identify a tutorial on the Google Cloud AI platform
- Set up the tutorial environment
- Follow the tutorial steps and complete the exercises
- Review your results and compare them to the expected outcomes
Build a machine learning model
Show steps
Apply the AI and ML concepts learned in class to a real-world problem and build a tangible artifact.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Define the problem and gather data
- Select and train a machine learning model
- Evaluate the model's performance
- Deploy the model to a production environment
Write a blog post on an AI or ML topic
Show steps
Develop your understanding and communication skills by presenting AI and ML concepts in your own words.
Browse courses on
AI
Show steps
Show steps
Show steps
- Choose an AI or ML topic to write about
- Research the topic and gather information
- Organize your thoughts and create an outline
- Write the blog post
- Proofread and publish the blog post
Career center
Learners who complete Innovating with Google Cloud Artificial Intelligence will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists conceive, design, and build solutions to business problems with the use of data. They are skilled at collecting raw data, transforming it into valuable information, and sharing insights with key stakeholders. This course on Google Cloud AI can help you understand how to use these services to build, deploy, and manage models. This can help lead to developing models that leverage diverse datasets, building pipelines to automate model training, and gaining proficiency in building a range of models on Google Cloud. Data Scientists can use this knowledge to help them on their journeys in this in-demand field.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers specialize in applying machine learning techniques to solve real-world problems. They design, construct, and deploy predictive models using machine learning algorithms, statistical techniques, and large datasets. This course on Google Cloud AI can help you understand how to use these services for common tasks like feature engineering, model training, and model evaluation. Machine Learning Engineers can use this knowledge to help them on their journeys in this in-demand field.
Data Analyst
Data Analyst
Data Analysts collect, analyze, interpret, and present data to provide insights and inform decision-making. They use analytical techniques and tools to transform raw data into meaningful information that can be utilized by businesses. This course on Google Cloud AI can help build a foundation in using AI and ML to gain insights from large and complex datasets. Data Analysts can use this knowledge to help them on their journeys in this in-demand field.
Software Engineer
Software Engineer
Software Engineers apply engineering principles to design, develop, maintain, and test software applications. They work with a variety of technologies, including programming languages, software development tools, and databases. This course on Google Cloud AI may be useful for Software Engineers, as it can help them build a foundation in using AI and ML to create more efficient and effective software solutions.
Product Manager
Product Manager
Product Managers are responsible for the overall success of a product, ensuring that it meets the needs of users and achieves business goals. They work with a variety of stakeholders including engineers, designers, and marketers. This course on Google Cloud AI can be useful for Product Managers as it can help them understand how AI and ML can be used to create innovative new products and features.
Business Analyst
Business Analyst
Business Analysts help organizations improve their performance by analyzing business processes and identifying areas for improvement. They use analytical techniques and tools to gather and interpret data, and then develop recommendations for changes that can improve efficiency and effectiveness. This course on Google Cloud AI may be useful for Business Analysts, as it can help them build a foundation in using AI and ML to gain insights from large and complex datasets.
Cloud Architect
Cloud Architect
Cloud Architects design, build, and manage cloud computing solutions. They work with a variety of tecnologías, including cloud platforms, networking, and security. This course on Google Cloud AI may be useful for Cloud Architects, as it can help them build a foundation in using AI and ML to create more efficient and effective cloud solutions.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain the infrastructure that is used to store and process data. They work with a variety of tecnologías, including databases, data warehouses, and big data platforms. This course on Google Cloud AI may be useful for Data Engineers, as it can help them build a foundation in using AI and ML to create more efficient and effective data solutions.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to provide insights and inform decision-making. They use statistical techniques and tools to transform raw data into meaningful information that can be utilized by businesses. This course on Google Cloud AI may be useful for Statisticians, as it can help them build a foundation in using AI and ML to gain insights from large and complex datasets.
Market Researcher
Market Researcher
Market Researchers conduct research to gather information about markets and customers. They use research methods such as surveys, interviews, and focus groups to collect data that can be used to develop marketing strategies and make informed business decisions. This course on Google Cloud AI may be useful for Market Researchers as it can help them build a foundation in using AI and ML to gain insights from large and complex datasets.
Financial Analyst
Financial Analyst
Financial Analysts use financial data to evaluate investments and make recommendations to clients. They use analytical techniques and tools to analyze financial statements, market trends, and economic data. This course on Google Cloud AI may be useful for Financial Analysts as it can help them build a foundation in using AI and ML to gain insights from large and complex datasets.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. They work with a variety of industries to improve efficiency and effectiveness. This course on Google Cloud AI may be useful for Operations Research Analysts as it can help them build a foundation in using AI and ML to gain insights from large and complex datasets.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze data and make predictions. They work in a variety of industries, including finance, insurance, and healthcare. This course on Google Cloud AI may be useful for Quantitative Analysts as it can help them build a foundation in using AI and ML to gain insights from large and complex datasets.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and mitigate risks to an organization. They work with a variety of stakeholders to develop and implement risk management strategies. This course on Google Cloud AI may be useful for Risk Analysts as it can help them build a foundation in using AI and ML to gain insights from large and complex datasets.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty. They work in a variety of industries, including insurance, finance, and healthcare. This course on Google Cloud AI may be useful for Actuaries as it can help them build a foundation in using AI and ML to gain insights from large and complex datasets.
For more career information including salaries, visit:
OpenCourser.com/course/hkph43/innovating
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
Innovating with Google Cloud Artificial Intelligence.
Save
Comprehensive guide to generative adversarial networks (GANs). It covers topics such as the theory of GANs, different GAN architectures, and applications of GANs. It valuable resource for anyone interested in learning more about GANs.
Classic textbook on reinforcement learning. It provides a comprehensive overview of the field, covering topics such as Markov decision processes, value functions, and policy gradient methods. It valuable resource for anyone interested in learning more about reinforcement learning.
Practical guide to deep learning with Python. It covers topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for anyone interested in learning how to apply deep learning to real-world problems using Python.
Save
Comprehensive guide to deep learning, a subfield of machine learning that has revolutionized many industries in recent years. It covers topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for anyone interested in learning more about deep learning.
Comprehensive guide to natural language processing with Python. It covers topics such as text preprocessing, machine learning for NLP, and deep learning for NLP. It valuable resource for anyone interested in learning how to apply NLP to real-world problems using Python.
Practical guide to machine learning with Python. It covers topics such as data preprocessing, model selection, and model evaluation. It valuable resource for anyone interested in learning how to apply machine learning to real-world problems using popular Python libraries.
Comprehensive guide to machine learning with Python. It covers topics such as data preprocessing, model selection, and model evaluation. It valuable resource for anyone interested in learning how to apply machine learning to real-world problems using Python.
Save
Explores the potential future of humanity in light of the rapid development of AI and other technologies. It discusses topics such as the singularity, the future of work, and the ethical implications of AI. It valuable resource for anyone interested in thinking about the long-term future of our species.
Gentle introduction to deep learning. It uses clear and simple language to explain complex concepts. It valuable resource for anyone who wants to learn more about deep learning without getting bogged down in technical details.
Practical guide to data science. It covers topics such as data cleaning, data analysis, and machine learning. It valuable resource for anyone interested in learning how to apply data science to real-world problems.
Practical guide to machine learning. It covers topics such as data preprocessing, model selection, and model evaluation. It valuable resource for anyone interested in learning how to apply machine learning to real-world problems.
Beginner-friendly introduction to machine learning. It covers topics such as data preprocessing, model selection, and model evaluation. It valuable resource for anyone who wants to learn more about machine learning without any prior knowledge.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/hkph43/innovating
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Time
2220 hours
Level
Introductory
Via
Pluralsight
Instructor
Google Cloud
Language
English
Good to know
Develops core skills in AI and ML, which are key to various industries
Taught by Google Cloud, recognized for their expertise in AI and ML
Explores AI and ML applications, which are highly relevant to business transformation
Part of Cloud Digital Leader learning path, which aligns with industry standards
Requires no previous knowledge or experience, making it accessible to various learners
Might require additional resources or tools, not readily available in all households or libraries
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