Introduction to Google Gemini AI Training in Astana, Kazakhstan

This training introduces participants to Google Gemini, Google’s advanced multimodal AI model. It covers core concepts, prompt engineering, integration through Google Cloud's Vertex AI, and practical application development. The course includes hands-on labs and emphasizes responsible AI usage.

Introduction and Core Concepts

Course Introduction

• Trainer and participant introductions
• Learning objectives and course roadmap

Overview of Google Gemini

• What is Gemini?
• Evolution of Google’s AI models
• Key capabilities and differentiators
• Real-world use cases

Gemini in Google Cloud

• Introduction to Vertex AI
• Gemini’s integration in the GCP ecosystem
• Using Vertex AI Studio to access Gemini
• Gemini API overview and key features

Prompt Engineering Basics

• What is prompt engineering?
• Zero-shot and few-shot prompting
• Prompting with text, images, and structured inputs
• Tips for optimizing Gemini responses

Advanced Applications and Responsible AI

Advanced Capabilities of Gemini

• Gemini Pro vs Gemini Flash
• Chain-of-thought and reasoning
• Long-context and memory handling
• Current model limitations and best practices

Building with Gemini API

• Making Gemini API calls with Python
• Using Gemini in web and mobile applications
• Structuring API requests and handling responses
• Building chat-like or structured tools

Pricing, Quotas, and Responsible AI

• Cost structure and quota management in Google Cloud
• Responsible AI principles
• Bias and safety considerations
• Monitoring and governance strategies

Assessment and Wrap-Up

• Final quiz and knowledge check
• Summary of key takeaways
• Feedback and course evaluation
• Certificate of completion