The document outlines the agenda for a 'Build with AI' workshop focused on the introduction of a new syllabus for generative AI, covering topics like Google Cloud tools, Vertex AI, and AI model training. Key components include practical applications for AI agents, building AI-powered assistants, and leveraging large language models. The workshop aims to enhance participants' skills through a 15-day scheme and educate them on the fundamentals of AI and cloud technologies.

1. Gen AI Cloud StudyJam
Workshop “Build with
AI”

2. Gen AI Study Jam
Resume from 2nd
November

3. Introduction of New
Syllabus of Gen AI

4. Syllabus of Gen AI
• Get started with Pub/sub
• Cloud Functions: 3 Ways
• Cloud Speech API: 3 Ways
• Get Started with Cloud Storage
• Get Started with Looker
• Get Started with Dataplex
• Get Started with API Gateway
• Monitoring in Google Cloud

5. Syllabus of Gen AI
• The Basics of Google Cloud Compute
• Get Started with Google Workspace Tools
• Prompt Design in Vertex AI
• Develop GenAI Apps with Gemini and Streamlit
• Analyze images with the Cloud vision API
• Networking Fundamentals on Google Cloud
• App Engine: 3 Ways

6. Introducing the 15
days 15 skill badges
scheme

7. Arcade game will be
accounced soon…

8. What is Vertex AI ?
A unified machine learning platform designed to simplify the
process of building and deploying AI models. Used by Data
scientists and developers for building custom models AI
Agent: It utilizes artificial intelligence techniques to perform
tasks autonomously or semi-autonomously.

9. Components of Vertex AI
• Pipelines
• Workbench
• Training
• Auto ML
• Model Registry

10. Open Source Models
Publicly available for use and modification,
fostering collaboration and innovation.TensorFlow
and PyTorch have large communities and
extensive documentation.

11. Pretrained Models
Models that have been previously trained on large datasets
and can be fine-tuned for specific tasks. They significantly
reduce the time and resources needed for model training.
Eg: Vision AI, Natural Language Processing models for text
analysis.

12. Large Language Models(LLMs)
LLMs are advanced AI models capable of understanding and
generating human-like text. They have numerous applications,
including chatbots, content generation, translation services,
and summarization tools.
Eg: BERT (Bidirectional Encoder Representations from
Transformers) and T5 (Text-to-Text Transfer Transformer).

13. Introduction to
“Build with AI”

14. Sundar Pichai on AI-
Generated Code at
Google
FirstName LastName
Title, Company

15. Building AI-Powered Assistants with
Gamma Model-
Similar to GitHub’s Copilot for VS Code.
.

16. Sundar Pichai on AI-
Generated Code at
Google
Editable Location
FirstName LastName
Title, Company

17. AI Content Search (RAG) With Docs
Agent
- User Question
- AI Conversion
- Data Retrieval
- User-Friendly Response

18. Building AI-Powered Assistants with
Gamma Model-
Similar to GitHub’s Copilot for VS Code.
.

19. Building AI-Powered Assistants with
Gamma Model-
Similar to GitHub’s Copilot for VS Code.
.

20. Introduction to AI Data Agent
and Function-Calling Feature
“Talk to SQL” system.

22. Practical Applications of AI-Powered SQL
Querying AI agent
1. User Question
2. AI Conversion
3. Data Retrieval
4. User-Friendly Response

23. Google AI Studio

24. Slide Formats

25. Thank you
.