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Multimodal Retrieval Augmented Generation (RAG) using the Vertex AI Gemini API
Google Cloud Training
Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you learn how to perform multimodal retrieval augmented generation (RAG) using Vertex AI Gemini API.
Register for this course and see more details by visiting:
OpenCourser.com/course/e89w8z/multimodal
What's inside
Syllabus
Multimodal Retrieval Augmented Generation (RAG) using the Vertex AI Gemini API
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces students to multimodal retrieval augmented generation (RAG), which is becoming more common in industry
Is taught by Google Cloud Training, who are recognized for their work in AI and machine learning
Is self-paced and takes place in the Google Cloud console, providing hands-on experience
Requires students to have some prior knowledge of AI and machine learning, which may be a barrier for some learners
Covers a specific aspect of AI and machine learning, which may not be of interest to all learners
Save this course
Save Multimodal Retrieval Augmented Generation (RAG) using the Vertex AI Gemini API 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 Multimodal Retrieval Augmented Generation (RAG) using the Vertex AI Gemini API with these
activities:
Review previous coursework or study materials on natural language processing
Show steps
Refresh your memory and reacquaint yourself with the basics of natural language processing before embarking on this course.
Browse courses on
Natural Language Processing
Show steps
-
Gather relevant materials
-
Review key concepts
Review Python programming concepts
Show steps
Review basic Python programming concepts to strengthen your foundational understanding before starting the course, ensuring a smoother learning experience.
Browse courses on
Python
Show steps
-
Revisit Python data types, variables, and operators.
-
Refresh your knowledge of Python control flow (e.g., if-else statements, loops).
-
Practice writing simple Python functions and modules.
Review foundational materials on natural language processing
Show steps
Enhance your understanding by reviewing a foundational book on natural language processing to strengthen your grasp of core concepts before delving into the course material.
View
Natural Language Processing with Python:...
on Amazon
Show steps
-
Obtain the book
-
Read and comprehend key chapters
Six other activities
Expand to see all activities and additional details
Show all nine activities
Test your understanding of Multimodal Retrieval Augmented Generation (RAG)
Show steps
Reinforce your understanding of RAG by solving practice problems and testing your skills.
Browse courses on
RAG
Show steps
-
Review the course materials on RAG.
-
Complete the practice exercises provided in the course.
-
Seek out additional practice problems online or in textbooks.
Follow tutorials on Vertex AI Gemini API
Show steps
Enhance your understanding of the Vertex AI Gemini API through guided tutorials, deepening your knowledge of multimodal retrieval augmented generation.
Browse courses on
AI
Show steps
-
Locate and enroll in relevant tutorials on the official Vertex AI documentation website.
-
Follow the tutorials step-by-step, implementing the code and experimenting with the API.
-
Explore additional resources and documentation to expand your knowledge.
Build a small-scale RAG application
Show steps
Solidify your understanding by applying your knowledge to a practical project, building a small-scale RAG application that demonstrates your comprehension of the concepts.
Show steps
-
Design the application, including the user interface and data flow.
-
Implement the RAG functionality using the Vertex AI Gemini API.
-
Test and refine your application to ensure it meets the desired requirements.
-
Optionally, deploy your application to a platform or share it with others.
Explore advanced RAG techniques with guided tutorials
Show steps
Expand your knowledge of RAG by following guided tutorials that cover advanced concepts and techniques.
Browse courses on
RAG
Show steps
-
Identify specific areas of RAG you want to improve.
-
Search for high-quality tutorials that align with your learning goals.
-
Follow the tutorials step-by-step, taking notes and experimenting with the code.
-
Apply what you've learned to practical examples or projects.
Contribute to open-source projects related to multimodal retrieval augmented generation (RAG)
Show steps
Deepen your understanding and support the community by contributing to open-source projects that focus on multimodal retrieval augmented generation (RAG).
Browse courses on
Open Source
Show steps
-
Identify suitable open-source projects
-
Review project documentation
-
Make meaningful contributions
Build a RAG-based application to solve a real-world problem
Show steps
Solidify your understanding of RAG by applying it to a practical problem and creating a tangible deliverable.
Browse courses on
RAG
Show steps
-
Define a problem that can be addressed with RAG.
-
Design and develop a RAG-based solution.
-
Implement and test your solution.
-
Present your application and its results.
Review previous coursework or study materials on natural language processing
Show steps
Refresh your memory and reacquaint yourself with the basics of natural language processing before embarking on this course.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Gather relevant materials
- Review key concepts
Review Python programming concepts
Show steps
Review basic Python programming concepts to strengthen your foundational understanding before starting the course, ensuring a smoother learning experience.
Browse courses on
Python
Show steps
Show steps
Show steps
- Revisit Python data types, variables, and operators.
- Refresh your knowledge of Python control flow (e.g., if-else statements, loops).
- Practice writing simple Python functions and modules.
Review foundational materials on natural language processing
Show steps
Enhance your understanding by reviewing a foundational book on natural language processing to strengthen your grasp of core concepts before delving into the course material.
View
Natural Language Processing with Python:...
on Amazon
Show steps
Show steps
Show steps
- Obtain the book
- Read and comprehend key chapters
Six other activities
Expand to see all activities and additional details
Show all nine activities
Test your understanding of Multimodal Retrieval Augmented Generation (RAG)
Show steps
Reinforce your understanding of RAG by solving practice problems and testing your skills.
Browse courses on
RAG
Show steps
Show steps
Show steps
- Review the course materials on RAG.
- Complete the practice exercises provided in the course.
- Seek out additional practice problems online or in textbooks.
Follow tutorials on Vertex AI Gemini API
Show steps
Enhance your understanding of the Vertex AI Gemini API through guided tutorials, deepening your knowledge of multimodal retrieval augmented generation.
Browse courses on
AI
Show steps
Show steps
Show steps
- Locate and enroll in relevant tutorials on the official Vertex AI documentation website.
- Follow the tutorials step-by-step, implementing the code and experimenting with the API.
- Explore additional resources and documentation to expand your knowledge.
Build a small-scale RAG application
Show steps
Solidify your understanding by applying your knowledge to a practical project, building a small-scale RAG application that demonstrates your comprehension of the concepts.
Show steps
Show steps
Show steps
- Design the application, including the user interface and data flow.
- Implement the RAG functionality using the Vertex AI Gemini API.
- Test and refine your application to ensure it meets the desired requirements.
- Optionally, deploy your application to a platform or share it with others.
Explore advanced RAG techniques with guided tutorials
Show steps
Expand your knowledge of RAG by following guided tutorials that cover advanced concepts and techniques.
Browse courses on
RAG
Show steps
Show steps
Show steps
- Identify specific areas of RAG you want to improve.
- Search for high-quality tutorials that align with your learning goals.
- Follow the tutorials step-by-step, taking notes and experimenting with the code.
- Apply what you've learned to practical examples or projects.
Contribute to open-source projects related to multimodal retrieval augmented generation (RAG)
Show steps
Deepen your understanding and support the community by contributing to open-source projects that focus on multimodal retrieval augmented generation (RAG).
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Identify suitable open-source projects
- Review project documentation
- Make meaningful contributions
Build a RAG-based application to solve a real-world problem
Show steps
Solidify your understanding of RAG by applying it to a practical problem and creating a tangible deliverable.
Browse courses on
RAG
Show steps
Show steps
Show steps
- Define a problem that can be addressed with RAG.
- Design and develop a RAG-based solution.
- Implement and test your solution.
- Present your application and its results.
Career center
Learners who complete Multimodal Retrieval Augmented Generation (RAG) using the Vertex AI Gemini API will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/e89w8z/multimodal
Reading list
We haven't picked any books for this reading list yet.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/e89w8z/multimodal
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Effort
60 minutes
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Session
August 12, 2024
- August 26, 2024
Language
English
Good to know
Introduces students to multimodal retrieval augmented generation (RAG), which is becoming more common in industry
Is taught by Google Cloud Training, who are recognized for their work in AI and machine learning
Is self-paced and takes place in the Google Cloud console, providing hands-on experience
Requires students to have some prior knowledge of AI and machine learning, which may be a barrier for some learners
Covers a specific aspect of AI and machine learning, which may not be of interest to all learners
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