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Google Cloud
This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
Register for this course and see more details by visiting:
OpenCourser.com/course/7bggjm/introduction
What's inside
Syllabus
Introduction to Generative AI
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces Generative AI, a trending and emerging field
Emphasizes practical application of Generative AI, bridging theory and practice
Led by Google Cloud experts, ensuring industry-relevant and up-to-date content
Focuses on microlearning, allowing for flexible and efficient learning
Provides essential knowledge for those seeking to develop Generative AI applications
Save this course
Save Introduction to Generative AI 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 Generative AI with these
activities:
Review Introduction to Machine Learning
Show steps
Refresh your knowledge on basic ML concepts, ensuring a stronger foundation for the generative AI concepts covered in this course.
Show steps
-
Revisit supervised and unsupervised learning concepts
-
Review common ML algorithms such as linear regression, logistic regression, and decision trees
-
Practice implementing simple ML models using a programming language
Follow tutorials on Generative Adversarial Networks (GANs)
Show steps
Explore in-depth tutorials that provide hands-on experience with GANs, a foundational Generative AI technique.
Browse courses on
Generative Adversarial Networks
Show steps
-
Find a comprehensive GAN tutorial from a reputable source
-
Set up the necessary development environment
-
Follow the tutorial steps to implement a basic GAN
-
Experiment with different GAN architectures and parameters
Build a Generative AI App using Google Cloud Tools
Show steps
Apply your understanding of Generative AI by building a practical application using the tools provided by Google Cloud.
Show steps
-
Identify a suitable Generative AI use case
-
Choose appropriate Google Cloud AI services and tools
-
Design and implement the application
-
Deploy and test the application
-
Refine and iterate based on results
Show all three activities
Review Introduction to Machine Learning
Show steps
Refresh your knowledge on basic ML concepts, ensuring a stronger foundation for the generative AI concepts covered in this course.
Show steps
Show steps
Show steps
- Revisit supervised and unsupervised learning concepts
- Review common ML algorithms such as linear regression, logistic regression, and decision trees
- Practice implementing simple ML models using a programming language
Follow tutorials on Generative Adversarial Networks (GANs)
Show steps
Explore in-depth tutorials that provide hands-on experience with GANs, a foundational Generative AI technique.
Browse courses on
Generative Adversarial Networks
Show steps
Show steps
Show steps
- Find a comprehensive GAN tutorial from a reputable source
- Set up the necessary development environment
- Follow the tutorial steps to implement a basic GAN
- Experiment with different GAN architectures and parameters
Build a Generative AI App using Google Cloud Tools
Show steps
Apply your understanding of Generative AI by building a practical application using the tools provided by Google Cloud.
Show steps
Show steps
Show steps
- Identify a suitable Generative AI use case
- Choose appropriate Google Cloud AI services and tools
- Design and implement the application
- Deploy and test the application
- Refine and iterate based on results
Show all three activities
Career center
Learners who complete Introduction to Generative AI will develop knowledge and skills
that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers build systems that can understand and process human language. This course provides a foundation in the underlying concepts of Generative AI and how it can be used to create powerful language-processing applications. With this knowledge, you can develop innovative solutions for tasks such as text classification, machine translation, and speech recognition.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and build machine learning systems to solve complex problems. This course provides a strong foundation in the fundamentals of Generative AI, enabling you to develop and deploy AI models that can generate novel data and solve real-world problems effectively.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course provides a valuable overview of Generative AI and its applications, equipping you with the knowledge to integrate AI capabilities into your software solutions. By understanding the potential of Generative AI, you can create more innovative and efficient software.
Data Scientist
Data Scientist
Data Scientists analyze and interpret data to extract meaningful insights. This course provides a solid understanding of Generative AI and its role in data science. With this knowledge, you can develop new techniques for data generation, data augmentation, and anomaly detection, enhancing the accuracy and efficiency of your data analysis.
AI Researcher
AI Researcher
AI Researchers push the boundaries of Artificial Intelligence. This course provides an introduction to Generative AI, a rapidly evolving field. By gaining a comprehensive understanding of its principles and applications, you can contribute to the development of novel AI algorithms and technologies.
Product Manager
Product Manager
Product Managers oversee the development and launch of products. This course provides a valuable understanding of Generative AI and its potential to transform products and services. By leveraging AI, you can create more personalized and engaging user experiences, driving innovation and growth.
UX Designer
UX Designer
UX Designers focus on creating user-centered experiences. This course provides insights into the role of Generative AI in UX design. By understanding how AI can generate personalized content and enhance user interactions, you can design more intuitive and engaging digital products.
Technical Writer
Technical Writer
Technical Writers create and maintain technical documentation. This course provides a foundation in Generative AI and its applications in natural language processing. By understanding how AI can generate text and translate languages, you can improve the quality and efficiency of your technical writing.
Content Creator
Content Creator
Content Creators develop and distribute content for various platforms. This course offers insights into Generative AI and its potential to transform content creation. By leveraging AI, you can generate unique and engaging content, streamline your workflow, and reach a wider audience.
Marketing Manager
Marketing Manager
Marketing Managers plan and execute marketing campaigns. This course provides an overview of Generative AI and its applications in marketing. By understanding how AI can generate personalized content and automate tasks, you can improve the effectiveness of your marketing campaigns.
Business Analyst
Business Analyst
Business Analysts analyze business processes and develop solutions to improve efficiency. This course provides a foundation in Generative AI and its potential to automate tasks and optimize processes. By understanding how AI can generate data and provide insights, you can enhance your problem-solving skills and drive business growth.
Financial Analyst
Financial Analyst
Financial Analysts provide insights and recommendations on financial matters. This course offers an introduction to Generative AI and its applications in finance. By understanding how AI can generate financial data and predict trends, you can make more informed decisions and improve your financial analysis.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. This course provides an overview of Generative AI and its potential to optimize project management. By understanding how AI can generate project plans and automate tasks, you can improve your project management skills and deliver successful projects.
Sales Manager
Sales Manager
Sales Managers lead and motivate sales teams. This course offers insights into Generative AI and its applications in sales. By understanding how AI can generate leads and automate tasks, you can improve your sales strategies and increase revenue.
Customer Success Manager
Customer Success Manager
Customer Success Managers ensure customer satisfaction and retention. This course provides an introduction to Generative AI and its potential to enhance customer interactions. By understanding how AI can generate personalized content and resolve issues, you can improve customer experiences and build stronger relationships.
For more career information including salaries, visit:
OpenCourser.com/course/7bggjm/introduction
Reading list
We've selected seven 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 Generative AI.
Provides a comprehensive overview of machine learning with Python. It covers the theory, algorithms, and applications of machine learning with Python, and it valuable resource for anyone who wants to learn more about this important field.
Provides a comprehensive overview of deep learning for natural language processing. It covers the theory, algorithms, and applications of deep learning for natural language processing, and it valuable resource for anyone who wants to learn more about this important field.
Provides a comprehensive overview of PyTorch for deep learning. It covers the theory, algorithms, and applications of PyTorch for deep learning, and it valuable resource for anyone who wants to learn more about this important tool.
Classic textbook on deep reinforcement learning. It covers the essential concepts and techniques of deep reinforcement learning, and it valuable resource for anyone who wants to learn more about this field.
Provides a practical introduction to deep learning using Python. It covers the essential concepts and techniques of deep learning, and it includes numerous code examples.
Save
Provides a comprehensive overview of generative adversarial networks (GANs), covering the theory, algorithms, and applications. It is written by leading researchers in the field and provides a solid foundation for understanding GANs.
Provides a comprehensive overview of variational autoencoders (VAEs), covering the theory, algorithms, and applications. It is written by leading researchers in the field and provides a solid foundation for understanding VAEs.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/7bggjm/introduction
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Time
22 hours
Level
Introductory
Via
Pluralsight
Instructor
Google Cloud
Language
English
Good to know
Introduces Generative AI, a trending and emerging field
Emphasizes practical application of Generative AI, bridging theory and practice
Led by Google Cloud experts, ensuring industry-relevant and up-to-date content
Focuses on microlearning, allowing for flexible and efficient learning
Provides essential knowledge for those seeking to develop Generative AI applications
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