Gemini 3 Training in Astana, Kazakhstan

The Gemini 3 Training is a hands-on, professional program designed to help participants use Google’s Gemini 3 models to build high-impact AI-powered workflows and applications.
The course focuses on multimodal AI, advanced prompting, workflow optimization, integration, and enterprise use cases, enabling teams to apply Gemini 3 for productivity, automation, analytics, and decision support.

This training is suitable for business users, developers, analysts, and innovation teams looking to maximize value from Gemini 3.

Introduction to Gemini 3

• Overview of Gemini 3 models and capabilities

• How Gemini 3 differs from earlier versions

• Multimodal AI: text, image, and data understanding

Gemini 3 Platform & Tooling

• Gemini web, API, and AI Studio overview

• Model selection and configuration

• Safety, temperature, and token controls

• Understanding cost and performance trade-offs

Prompt Engineering for Gemini 3

• Prompt structure and best practices

• System vs user instructions

• Controlling tone, format, and reasoning

• Few-shot and template-based prompting

Multimodal Workflows

• Working with images and documents

• Extracting insights from PDFs and visuals

• Image + text reasoning use cases

• Multimodal productivity scenarios

Structured Outputs & Automation

• JSON and schema-based outputs

• Using Gemini for classification and extraction

• Automation-friendly prompting

• Validation and error handling

Gemini 3 for Productivity

• Writing, summarization, and content generation

• Meeting notes, reports, and documentation

• Research and information synthesis

• Presentation and communication support

Gemini 3 for Analytics & Decision Support

• Explaining data and KPIs

• Scenario analysis and comparisons

• Risk and impact assessments

• AI-assisted recommendations

Building Multi-Step AI Workflows

• Chained prompts and task decomposition

• Human-in-the-loop workflows

• AI agents and task orchestration (concepts)

• Improving reliability with step-by-step designs

Integration & Application Patterns

• Using Gemini 3 via APIs

• Integrating with business tools and systems

• Embedding Gemini into internal apps

• Workflow automation patterns

Performance, Cost & Optimization

• Reducing token usage

• Latency optimization strategies

• Caching and reuse

• Scaling Gemini-powered workflows

Security, Governance & Responsible AI

• Data privacy and access control

• Preventing data leakage

• Bias and reliability considerations

• Enterprise AI governance best practices

Hands-on Exercises

Summary and Conclusion