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Gemini For Developers - Google Generative Ai - For Beginners
Published 1/2026
Created by K8s Point - Training House for GCP, AI & Kubernetes
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 43 Lectures ( 3h 36m ) | Size: 2.3 GB[/center]
A Developer's Guide to working with Gemini, Google AI Studio, and Vertex AI Studio - Start you AI Development Here
What you'll learn
✓ Use Gemini models effectively as a developer, not just as a chat interface
✓ Build AI-powered applications using Gemini APIs
✓ Work with Google AI Studio for rapid prototyping and experimentation
✓ Use Vertex AI Studio along with other GCP options
✓ Understand and implement different authentication methods in GCP to access a Model
✓ Use the Generative AI SDK (Gen AI SDK) with extensive, hands-on examples
✓ Understand different Gemini Models and Model lifecycle
✓ Gemini CLI - command line agent from Gemini
✓ Gemini Code Assist - Enhance your productivity in coding
✓ Control model parameters (Temperature, safety setting, tokens) while accessing a Gemini model
✓ Cost Control while accessing a model with token restriction
✓ Create images with Nano Banana
✓ Generate video using Veo models
Requirements
● Very Basic of GCP and Python
Description
Generative AI is rapidly transforming how modern applications are built, and Gemini sits at the core of Google's AI ecosystem. Whether you are building intelligent assistants, developer tools, automation workflows, or production-ready AI applications, Gemini is the foundation every developer needs to master.
This course is designed specifically for developers who want to use Gemini to build real-world AI-powered applications, not just experiment with prompts.
What You'll Learn in This Course
• Use Gemini models effectively as a developer, not just as a chat interface
• Build AI-powered applications using Gemini APIs
• Work with Google AI Studio for rapid prototyping and experimentation
• Use Vertex AI Studio for enterprise-grade development and deployment
• Understand and implement different authentication methods in GCP, including
• API keys
• Service accounts
• Application Default Credentials (ADC)
• Use the Generative AI SDK (Gen AI SDK) with extensive, hands-on examples
• Structure prompts, system instructions, and model interactions for real applications
• Move from local development to cloud-based, scalable AI solutions
Tools & Platforms Covered
This course provides hands-on experience with
• Gemini Models
• Google AI Studio
• Vertex AI Studio
• Google Cloud Platform (GCP)
• Generative AI SDKs with multiple real-world examples
All concepts are demonstrated through practical coding examples, focusing on how developers actually build and integrate AI into applications.
Why Gemini for Developers?
Gemini is not just another large language model-it is deeply integrated into Google's cloud and developer stack. It supports
• Multimodal inputs (text, images, code)
• Tool usage and function calling
• Tight integration with Google Cloud services
• Scalable, secure deployment for production workloads
Understanding Gemini gives you a significant advantage when building next-generation AI applications on Google Cloud.
Who this course is for
■ Developers who wants to learn how to use AI
■ Wanting to use Gemini outside chatbot and program AI applications
■ Understand how Generative AI works with Gemini
Gemini For Developers - Google Generative Ai - For Beginners
Published 1/2026
Created by K8s Point - Training House for GCP, AI & Kubernetes
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 43 Lectures ( 3h 36m ) | Size: 2.3 GB[/center]
A Developer's Guide to working with Gemini, Google AI Studio, and Vertex AI Studio - Start you AI Development Here
What you'll learn
✓ Use Gemini models effectively as a developer, not just as a chat interface
✓ Build AI-powered applications using Gemini APIs
✓ Work with Google AI Studio for rapid prototyping and experimentation
✓ Use Vertex AI Studio along with other GCP options
✓ Understand and implement different authentication methods in GCP to access a Model
✓ Use the Generative AI SDK (Gen AI SDK) with extensive, hands-on examples
✓ Understand different Gemini Models and Model lifecycle
✓ Gemini CLI - command line agent from Gemini
✓ Gemini Code Assist - Enhance your productivity in coding
✓ Control model parameters (Temperature, safety setting, tokens) while accessing a Gemini model
✓ Cost Control while accessing a model with token restriction
✓ Create images with Nano Banana
✓ Generate video using Veo models
Requirements
● Very Basic of GCP and Python
Description
Generative AI is rapidly transforming how modern applications are built, and Gemini sits at the core of Google's AI ecosystem. Whether you are building intelligent assistants, developer tools, automation workflows, or production-ready AI applications, Gemini is the foundation every developer needs to master.
This course is designed specifically for developers who want to use Gemini to build real-world AI-powered applications, not just experiment with prompts.
What You'll Learn in This Course
• Use Gemini models effectively as a developer, not just as a chat interface
• Build AI-powered applications using Gemini APIs
• Work with Google AI Studio for rapid prototyping and experimentation
• Use Vertex AI Studio for enterprise-grade development and deployment
• Understand and implement different authentication methods in GCP, including
• API keys
• Service accounts
• Application Default Credentials (ADC)
• Use the Generative AI SDK (Gen AI SDK) with extensive, hands-on examples
• Structure prompts, system instructions, and model interactions for real applications
• Move from local development to cloud-based, scalable AI solutions
Tools & Platforms Covered
This course provides hands-on experience with
• Gemini Models
• Google AI Studio
• Vertex AI Studio
• Google Cloud Platform (GCP)
• Generative AI SDKs with multiple real-world examples
All concepts are demonstrated through practical coding examples, focusing on how developers actually build and integrate AI into applications.
Why Gemini for Developers?
Gemini is not just another large language model-it is deeply integrated into Google's cloud and developer stack. It supports
• Multimodal inputs (text, images, code)
• Tool usage and function calling
• Tight integration with Google Cloud services
• Scalable, secure deployment for production workloads
Understanding Gemini gives you a significant advantage when building next-generation AI applications on Google Cloud.
Who this course is for
■ Developers who wants to learn how to use AI
■ Wanting to use Gemini outside chatbot and program AI applications
■ Understand how Generative AI works with Gemini
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