This course introduces the essentials of Gemini AI and Vertex AI, blending architectural insights with hands-on coding, multimodal development, and intelligent agent creation. Designed to give you both theoretical foundations and practical experience, it explores how Google’s most advanced AI systems are transforming software development, data analysis, and real-world applications.

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Gemini and Vertex AI: Building Intelligent Applications
This course is part of Generative AI for Software Engineers & Developers Specialization

Instructor: Edureka
Included with
Recommended experience
What you'll learn
Explain Gemini’s multimodal architecture and use AI Studio/APIs for text, vision, and code.
Use Gemini APIs and Google AI Studio to explore code generation, document analysis, and multimodal capabilities.
Explore Vertex AI foundations, model tuning, and deployment strategies conceptually, with practical demos focused on Gemini.
Skills you'll gain
- Generative AI Agents
- Program Development
- Document Management
- Agentic systems
- Generative AI
- Cloud Platforms
- MLOps (Machine Learning Operations)
- Performance Tuning
- Artificial Intelligence
- Google Cloud Platform
- Artificial Intelligence and Machine Learning (AI/ML)
- Software Development Tools
- AI Personalization
- Application Deployment
- Natural Language Processing
- Large Language Modeling
- Application Programming Interface (API)
- Prompt Engineering
- Test Case
- Python Programming
Details to know

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August 2025
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There are 5 modules in this course
Learn Gemini’s multimodal architecture, differences between Pro and Ultra models, and how it compares with other LLMs. Explore the evolution of multimodal AI, Google AI Studio, and setting up the Gemini API for text and vision. Gain skills in structured outputs, function calling, document understanding, grounding, contextual anchoring, and fine-tuning models.
What's included
12 videos5 readings3 assignments2 discussion prompts2 plugins
Discover Gemini’s code generation capabilities with multilingual support, best practices, and AI-powered coding assistance. Learn prompt engineering in Google AI Studio for testing, optimization, and regex mastery. Explore multimodal development with OpenAI compatibility, natural language to SQL, document analysis, real-time streaming APIs, and starter apps.
What's included
17 videos3 readings4 assignments3 discussion prompts1 plugin
Set up your Vertex AI environment, explore Model Garden, and examine Google’s foundation models like Gemini, Imagen, and Veo. Develop intelligent agents using the Agent Development Kit and Agent Engine, enhance them with tools, and apply task-specific prompts. Leverage generative AI for text, code, image, and video generation, and utilize grounding, translation, and AI-powered prompt writing tools.
What's included
10 videos6 readings4 assignments3 discussion prompts1 plugin
Apply tuning techniques to optimize Gemini, Imagen, and translation models, implement LoRA and QLoRA for efficiency, and migrate seamlessly from Google AI to Vertex AI using OpenAI libraries. Conduct evaluations with the Python SDK, define metrics, analyze results, and customize judge models for improved accuracy. Deploy generative AI models with scalable strategies, optimize cost, latency, and performance, and enhance efficiency through caching, batch inference, and throughput management.
What's included
11 videos4 readings4 assignments3 discussion prompts1 plugin
This module is designed to assess an individual on the various concepts and teachings covered in this course. Evaluate your knowledge with a comprehensive graded quiz.
What's included
1 video2 assignments1 discussion prompt
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Frequently asked questions
A practical introduction to Gemini AI using Google AI Studio and GCP for multimodal AI and code generation.
Developers, data scientists, and tech professionals seeking hands-on Gemini demos and practical workflows.
No; basic Python or ML familiarity is helpful but not required.
More questions
Financial aid available,
¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.