We may earn an affiliate commission when you visit our partners.
Google Cloud Training
Any business professional or team in an organization interested in learning about artificial intelligence, machine learning, and Google Cloud technology.
Register for this course and see more details by visiting:
OpenCourser.com/course/03h37p/innovating
What's inside
Syllabus
Course Introduction
In this introduction, you'll explore the course goals and preview each section.
AI and ML Fundamentals
Artificial intelligence and machine learning can provide many benefits to a business, but it’s important to understand the fundamentals before starting any AI or ML initiative. In this section of the course, you'll explore many of those fundamental concepts.
Read more
Syllabus
Course Introduction
In this introduction, you'll explore the course goals and preview each section.
AI and ML Fundamentals
Artificial intelligence and machine learning can provide many benefits to a business, but it’s important to understand the fundamentals before starting any AI or ML initiative. In this section of the course, you'll explore many of those fundamental concepts.
Read more
Module 3: Google Cloud’s AI and ML Solutions
In this section of the course, you'll explore four options to build ML models with Google Cloud: BigQuery ML, pre-trained APIs, AutoML, and custom training.
Course Summary
The course closes with a summary of the key points covered in each section and next steps to continue learning.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores core concepts of AI and ML, applicable in business
Covers options for building ML models with Google Cloud, suitable for various needs
Taught by Google Cloud Training, known for expertise in the field
Provides foundational knowledge for beginners but may need supplementation for advanced learners
Focuses on Google Cloud technology, limiting its applicability beyond that ecosystem
May require additional resources for more comprehensive understanding of AI and ML principles
Save this course
Save Innovating with Google Cloud Artificial Intelligence to your list so you can find it easily later:
Save
Save
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 Fundamentals of Computer Science
Show steps
Reviewing the fundamentals of computer science will help you to better understand concepts such as data structures, algorithms and complexity analysis, all of which are important for understanding artificial intelligence and machine learning.
Browse courses on
Artificial Intelligence
Show steps
-
Review your notes or textbooks.
-
Take practice tests or quizzes to reinforce your knowledge.
Read 'Introduction to Artificial Intelligence' by Russell and Norvig
Show steps
Reading this book will provide you with a strong foundation in the fundamental concepts of artificial intelligence. It will cover topics such as search, planning, uncertain knowledge, and learning, which will be essential for your success in this course.
View
Artificial Intelligence: A Modern Approach,...
on Amazon
Show steps
-
Read each chapter carefully and take notes.
-
Complete the exercises at the end of each chapter.
-
Discuss the concepts with your classmates or colleagues.
Solve practice problems and coding challenges
Show steps
Solving practice problems and coding challenges will help you to develop the problem-solving and coding skills that are essential for success in this course.
Browse courses on
Coding
Show steps
-
Find practice problems and coding challenges online.
-
Attempt to solve the problems and challenges on your own.
-
Compare your solutions to those provided by others.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Watch video tutorials and take online courses
Show steps
Watching video tutorials and taking online courses can be a great way to learn about new AI and ML concepts and techniques.
Show steps
-
Find video tutorials and online courses that cover topics that you are interested in.
-
Watch or take the courses at your own pace.
-
Take notes and practice the concepts that you learn.
Build a portfolio of AI and ML projects
Show steps
Building a portfolio of AI and ML projects will allow you to showcase your skills and knowledge to potential employers. It will also help you to learn from your experience and to further develop your skills.
Browse courses on
Portfolio
Show steps
-
Choose a few projects to work on.
-
Gather the necessary resources.
-
Build and test your projects.
-
Document your projects and share them online.
Attend industry events and meetups
Show steps
Attending industry events and meetups is a great way to network with other professionals in the field and to learn about the latest trends and developments in AI and ML.
Browse courses on
Networking
Show steps
-
Find industry events and meetups in your area.
-
Attend the events and meet new people.
-
Share your knowledge and experience with others.
Find a mentor who can provide guidance and support
Show steps
Finding a mentor who can provide guidance and support can be a great way to accelerate your learning and development in AI and ML.
Browse courses on
Support
Show steps
-
Identify potential mentors in your field.
-
Reach out to your potential mentors and introduce yourself.
-
Ask your mentors for guidance and support.
Create a collection of resources and tools for AI and ML
Show steps
Creating a collection of resources and tools for AI and ML can be a great way to organize your learning and to help you stay up-to-date on the latest trends and developments in the field.
Browse courses on
Collection
Show steps
-
Find and collect resources and tools related to AI and ML.
-
Organize your resources and tools into a central location.
-
Share your collection with other students and professionals.
Review Fundamentals of Computer Science
Show steps
Reviewing the fundamentals of computer science will help you to better understand concepts such as data structures, algorithms and complexity analysis, all of which are important for understanding artificial intelligence and machine learning.
Browse courses on
Artificial Intelligence
Show steps
Show steps
Show steps
- Review your notes or textbooks.
- Take practice tests or quizzes to reinforce your knowledge.
Read 'Introduction to Artificial Intelligence' by Russell and Norvig
Show steps
Reading this book will provide you with a strong foundation in the fundamental concepts of artificial intelligence. It will cover topics such as search, planning, uncertain knowledge, and learning, which will be essential for your success in this course.
View
Artificial Intelligence: A Modern Approach,...
on Amazon
Show steps
Show steps
Show steps
- Read each chapter carefully and take notes.
- Complete the exercises at the end of each chapter.
- Discuss the concepts with your classmates or colleagues.
Solve practice problems and coding challenges
Show steps
Solving practice problems and coding challenges will help you to develop the problem-solving and coding skills that are essential for success in this course.
Browse courses on
Coding
Show steps
Show steps
Show steps
- Find practice problems and coding challenges online.
- Attempt to solve the problems and challenges on your own.
- Compare your solutions to those provided by others.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Watch video tutorials and take online courses
Show steps
Watching video tutorials and taking online courses can be a great way to learn about new AI and ML concepts and techniques.
Show steps
Show steps
Show steps
- Find video tutorials and online courses that cover topics that you are interested in.
- Watch or take the courses at your own pace.
- Take notes and practice the concepts that you learn.
Build a portfolio of AI and ML projects
Show steps
Building a portfolio of AI and ML projects will allow you to showcase your skills and knowledge to potential employers. It will also help you to learn from your experience and to further develop your skills.
Browse courses on
Portfolio
Show steps
Show steps
Show steps
- Choose a few projects to work on.
- Gather the necessary resources.
- Build and test your projects.
- Document your projects and share them online.
Attend industry events and meetups
Show steps
Attending industry events and meetups is a great way to network with other professionals in the field and to learn about the latest trends and developments in AI and ML.
Browse courses on
Networking
Show steps
Show steps
Show steps
- Find industry events and meetups in your area.
- Attend the events and meet new people.
- Share your knowledge and experience with others.
Find a mentor who can provide guidance and support
Show steps
Finding a mentor who can provide guidance and support can be a great way to accelerate your learning and development in AI and ML.
Browse courses on
Support
Show steps
Show steps
Show steps
- Identify potential mentors in your field.
- Reach out to your potential mentors and introduce yourself.
- Ask your mentors for guidance and support.
Create a collection of resources and tools for AI and ML
Show steps
Creating a collection of resources and tools for AI and ML can be a great way to organize your learning and to help you stay up-to-date on the latest trends and developments in the field.
Browse courses on
Collection
Show steps
Show steps
Show steps
- Find and collect resources and tools related to AI and ML.
- Organize your resources and tools into a central location.
- Share your collection with other students and professionals.
Career center
Learners who complete Innovating with Google Cloud Artificial Intelligence will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
This course will help you build a foundation towards a career as a Machine Learning Engineer. This course will introduce you to AI, ML, and Google Cloud technologies and show you how to use all of these to build ML models.
Software Developer
Software Developer
This course will help you build a foundation towards a career as a Software Developer. This course will introduce you to AI, ML, and Google Cloud technologies and show you how to use all of these to build ML models.
Data Scientist
Data Scientist
This course can introduce you to key AI and ML concepts, which are the tools of the trade for Data Scientists. These are crucial for many modern solutions that help companies operate efficiently.
Project Manager
Project Manager
AI/ML projects often require a Proejct Manager to coordinate and direct activities. This course can help build a foundation towards a career as a Project Manager, and it can help build a foundation for engaging with AI/ML project stakeholders.
Business Analyst
Business Analyst
Business Analysts can learn from this course how to understand the potential and applications of AI/ML for their organization. This course will help you build a solid basis from which to become a Business Analyst.
Data Analyst
Data Analyst
Data Analysts frequently collaborate with Data Scientists. They know how to organize, analyze, and visualize data. Taking this course can help build a solid basis from which to become a Data Analyst.
Information Security Analyst
Information Security Analyst
Information Security Analysts may need to understand how AI/ML systems are used within an organization. This course can provide that understanding and can help you build a solid basis from which to become an Information Security Analyst.
Database Administrator
Database Administrator
A Database Administrator needs to understand how data is used. This course can provide that understanding in the context of AI/ML systems. This course may be helpful for Database Administrators.
Systems Administrator
Systems Administrator
Systems Administrators need to understand how the systems they maintain are used. This course can provide that understanding in the context of AI/ML systems. This course may be helpful for Systems Administrators.
Product Manager
Product Manager
Product Managers need to be familiar with the potential value and applications of AI/ML. This course may be useful for Product Managers looking to expand their understanding of AI/ML.
Data Architect
Data Architect
This course may be helpful for Data Architects who want to understand how AI/ML systems process data. This information can make one more effective in building robust and scalable data processing pipelines.
Web Developer
Web Developer
This course may be helpful for Web Developers who want to add AI/ML powered interactivity to their web applications. The course will teach the foundational concepts and how to use Google Cloud to implement these concepts practically.
Data Engineer
Data Engineer
Data Engineers work with the infrastructure that is foundational to data analysis. A stronger understanding of how this data is used by AI/ML systems can make one more effective in this role.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts can use their knowledge of AI/ML systems to improve testing and quality assurance processes. This course may be helpful for Quality Assurance Analysts wanting to expand their understanding of AI/ML.
DevOps Engineer
DevOps Engineer
DevOps Engineers may need to understand how to interpret predictions made by AI/ML systems. Knowledge of how AI/ML systems are trained can help one be more effective in this role.
For more career information including salaries, visit:
OpenCourser.com/course/03h37p/innovating
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
Innovating with Google Cloud Artificial Intelligence.
Save
This classic textbook on deep learning, providing deep coverage of topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a probabilistic perspective on machine learning, covering topics such as Bayesian inference, graphical models, and reinforcement learning.
Provides an introduction to reinforcement learning, covering topics such as Markov decision processes, dynamic programming, and Monte Carlo methods.
Provides a comprehensive overview of data science, including topics such as data mining, machine learning, and statistical modeling.
Provides a hands-on introduction to machine learning using popular libraries such as scikit-learn, keras, and TensorFlow.
Teaches the fundamentals of data science, including data cleaning, data analysis, and data visualization.
Explores the economic impact of AI.
Explores the ethical and societal implications of AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/03h37p/innovating
Share
Similar courses
Here are nine courses similar to
Innovating with Google Cloud Artificial Intelligence.
Applications of Machine Learning in Plant Science
OpenCourser.com/course/6k85i0/applications
Applications of Machine Learning in Plant Science
Less relevant
Leading Change: Go Beyond Gamification with Gameful Learning
OpenCourser.com/course/6ookd9/leading
Leading Change: Go Beyond Gamification with Gameful...
Less relevant
Deep Learning and Reinforcement Learning
OpenCourser.com/course/ppm31d/deep
Deep Learning and Reinforcement Learning
Less relevant
Getting Started with Azure Machine Learning Studio
OpenCourser.com/course/go1rmi/getting
Getting Started with Azure Machine Learning Studio
Less relevant
Play by Play: Machine Learning Exposed
OpenCourser.com/course/2hitrz/play
Play by Play: Machine Learning Exposed
Less relevant
Deep Learning Application for Healthcare
OpenCourser.com/course/yy9w6z/deep
Deep Learning Application for Healthcare
Less relevant
Blended Learning Essentials: Getting Started
OpenCourser.com/course/t7dazf/blended
Blended Learning Essentials: Getting Started
Less relevant
Design, Build, & Implement
OpenCourser.com/course/fd3mrr/design
Design, Build, & Implement
Less relevant
Big Data Machine Learning | 大数据机器学习
OpenCourser.com/course/5kg2s5/big
Big Data Machine Learning | 大数据机器学习
Less relevant
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
This course belongs to a
collection
called
Google Cloud Digital Leader Training. It's comprised of four courses:
- Modernize Infrastructure and Applications with Google Cloud
- Trust and Security with Google Cloud
- Innovating with Google Cloud Artificial Intelligence (viewing)
- Scaling with Google Cloud Operations
Good to know
Explores core concepts of AI and ML, applicable in business
Covers options for building ML models with Google Cloud, suitable for various needs
Taught by Google Cloud Training, known for expertise in the field
Provides foundational knowledge for beginners but may need supplementation for advanced learners
Focuses on Google Cloud technology, limiting its applicability beyond that ecosystem
May require additional resources for more comprehensive understanding of AI and ML principles
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser