5. Overview of the Google Cloud Study Jam campaign!
Google Cloud Computing Foundations
8 courses
GenAI Arcade Game: Prompt Engineering
8 Hands-on Lab Activities
7. Session Agenda
Introdution to AI , ML , Generative AI and LLMโs
1
2 Introduction to GenAI: Prompt Engineering Pathway
3 Resources for GenAI Hands-on Labs,& challenge
4 Quiz , Q&A and Next steps
45. Session Agenda
2 Introduction to GenAI: Prompt Engineering Pathway
3 Resources for GenAI Hands-on Labs,& challenge
4 Quiz , Q&A and Next steps
Introdution to AI , ML , Generative AI and LLMโs
1
46. Introduction to GenAI: Prompt Engineering
เนOverview of the GenAI Pathway
เนGCP Services to Unlocking GenAI Potential!
เนGetting Ready for Hands-On Learning
47. Overview of the GenAI Pathway
1. Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API
2. Entity and Sentiment Analysis with the Natural Language API
3. Generative AI with Vertex AI: Prompt Design
4. Generative AI with Vertex AI: Getting Started
5. Get Started with Generative AI Studio
6. Generative AI Cricket Chatbot
7. Generative AI Food Chatbot
8. Analyze Images with the Cloud Vision API: Challenge Lab.
49. GCPโs AI Services to Unlocking GenAI Potential!
AI
Vertex AI
Natural Language
API
Vision
API
Auto ML
50. โ Google Cloud Vision API is a
powerful tool for image
recognition and analysis.
โ It uses ML models to detect
and identify objects, faces,
text, and other elements within
images and can provide
information about their
content.
โ Google Cloud Natural
Language API is a powerful
tool for analyzing and
extracting valuable insights
from text data.
โ It can perform sentiment
analysis to determine the
emotional tone of a piece of
text, which is useful for
understanding customer
sentiment in product reviews
or social media comments.
Vision API Natural Language API
GCPโs AI Services to Unlocking GenAI Potential!
51. โ It is a powerful image analysis
tool that offers a wide range of
capabilities, including object
recognition, facial detection,
text extraction, and explicit
content detection.
โ It allows businesses and
developers to extract
meaningful information from
images, making it valuable for
tasks like content moderation,
automated tagging, and image
classification.
โ Google Cloud AutoML is a
suite of machine learning
products that allows users to
create custom machine
learning models with ease,
even if they have limited
expertise in machine learning.
โ It provides a user-friendly
interface and automated
processes for tasks such as
image recognition, natural
language processing, and
structured data analysis.
Vision API Auto ML
GCPโs AI Services to Unlocking GenAI Potential!
52. GCPโs AI Services to Unlocking GenAI Potential!
โ Generative AI Studio is a
Google Cloud console tool for
rapidly prototyping and testing
generative AI models.
Generative AI Studio
54. Session Agenda
3 Resources for GenAI Hands-on Labs,& challenge
4 Quiz , Q&A and Next steps
Introdution to AI , ML , Generative AI and LLMโs
1
2 Introduction to GenAI: Prompt Engineering Pathway
55. 3 Resources for GenAI Hands-on Labs,& challenge
Lab & Quiz Resources for Google Cloud & Generative AI
63. Session Agenda
4 Quiz , Q&A and Next steps
Introdution to AI , ML , Generative AI and LLMโs
1
2 Introduction to GenAI: Prompt Engineering Pathway
3 Resources for GenAI Hands-on Labs,& challenge
66. Session Agenda
Introdution to AI , ML , Generative AI and LLMโs
1
2 Introduction to GenAI: Prompt Engineering Pathway
3 Resources for GenAI Hands-on Labs,& challenge
4 Quiz , Q&A and Next steps
With infrastructure as a service, the service provides the underlying architecture for you to run servers. The resources to run are provided, but itโs up to the user to manage the operating system and application.
Platform as a service takes it one step further. Now the entire environment will be managed for you the user, and all that is required of you is to manage your applications. The operating system layer will be managed as part of the service.
For Software as a service, the infrastructure, platform, and software is managed for you. All thatโs required is that you bring your data to the system. A few commercial examples of SaaS include SAP and Salesforce.
With infrastructure as a service, the service provides the underlying architecture for you to run servers. The resources to run are provided, but itโs up to the user to manage the operating system and application.
Platform as a service takes it one step further. Now the entire environment will be managed for you the user, and all that is required of you is to manage your applications. The operating system layer will be managed as part of the service.
For Software as a service, the infrastructure, platform, and software is managed for you. All thatโs required is that you bring your data to the system. A few commercial examples of SaaS include SAP and Salesforce.
With infrastructure as a service, the service provides the underlying architecture for you to run servers. The resources to run are provided, but itโs up to the user to manage the operating system and application.
Platform as a service takes it one step further. Now the entire environment will be managed for you the user, and all that is required of you is to manage your applications. The operating system layer will be managed as part of the service.
For Software as a service, the infrastructure, platform, and software is managed for you. All thatโs required is that you bring your data to the system. A few commercial examples of SaaS include SAP and Salesforce.