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There are 5 modules in this course
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.
Through guided lessons and demonstrations, you’ll learn to work with Gemini’s multimodal architecture, leverage APIs for text and vision, build smarter apps with AI-driven code generation, and design intelligent agents on Vertex AI. You will also explore advanced model tuning, grounding techniques, and deployment strategies to create reliable, production-ready AI solutions.
By the end of this course, you will be able to:
• Understand Gemini’s multimodal architecture, APIs, and core capabilities.
• Implement Gemini for text, vision, and code tasks, including function calling and document understanding.
• Apply prompt engineering strategies and best practices for code generation, optimization, and testing.
• Develop multimodal applications using Gemini Live API and natural language-to-database techniques.
• Explore Vertex AI foundations, model garden, and Google’s foundation models (Gemini, Imagen, Veo).
• Build and enhance intelligent agents with the Agent Development Kit and task-specific prompt guidance.
• Tune, evaluate, and optimize Gemini and Vertex AI models using LoRA, QLoRA, and evaluation metrics.
• Deploy AI systems with strategies to balance cost, latency, throughput, and performance.
This course is ideal for developers, data scientists, and AI practitioners who want to build next-generation applications powered by Google Gemini AI and Vertex AI.
A basic understanding of Python and machine learning will be helpful, but no prior experience with Gemini or Vertex AI is required.
Join us to explore the cutting edge of multimodal AI and discover how to build smarter, more reliable applications with Gemini and Vertex AI!
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.
Building Smarter Apps with Gemini AI: Code, Prompts & Multimodal Power
Module 2•3 hours to complete
Module details
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.
Demonstration: Python with Gemini on Google AI Studio•4 minutes
Demonstration: C++ with Gemini on Google AI Studio•3 minutes
Best Practices for Code Generation•2 minutes
Prompt Engineering in Google AI Studio•3 minutes
Unit Testing for Reliable Code•3 minutes
Demonstartion: Unit Testing for Reliable Code•2 minutes
Code Optimization Made Easy•4 minutes
Demonstartion: Code Optimization Made Easy•4 minutes
Mastering Regex for Developers•3 minutes
Demonstration: Mastering Regex for Developers•4 minutes
OpenAI Compatibility•3 minutes
Natural Language to SQL•2 minutes
Demonstration: Document Analysis and Code Extraction•3 minutes
Demonstration: Gemini Live API•5 minutes
Stream Realtime/ Multimodal Live API•4 minutes
Demonstration: Starter Apps•8 minutes
3 readings•Total 45 minutes
AI-Powered Code Assistance: From Autocomplete to Intelligent Pair Programming•15 minutes
Converting Natural Language to Database Queries: Challenges and Innovations•15 minutes
Module Summary: Building Smarter Apps with Gemini AI: Code, Prompts & Multimodal Power•15 minutes
4 assignments•Total 48 minutes
Practice Quiz: Code Generation with Gemini•6 minutes
Practice Quiz: Prompt Engineering with Gemini•6 minutes
Practice Quiz: Multimodal Development with Gemini•6 minutes
Knowledge Check: Building Smarter Apps with Gemini AI: Code, Prompts & Multimodal Power•30 minutes
3 discussion prompts•Total 15 minutes
Writing Code the Right Way•5 minutes
Testing for Trust•5 minutes
Talking to Databases•5 minutes
Vertex AI Foundations & Intelligent Agent Development
Module 3•4 hours to complete
Module details
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.
Build a Simple Knowledge Chat Agent with Vertex AI•15 minutes
Analyzing Data with Generative AI Models•15 minutes
Module Summary: Vertex AI Foundations & Intelligent Agent Development•15 minutes
4 assignments•Total 48 minutes
Practice Quiz: Discovering Vertex AI•6 minutes
Practice Quiz: Building Intelligent Agents on Vertex AI•6 minutes
Practice Quiz: Harnessing the Capabilities of Generative AI Models•6 minutes
Knowledge Check: Vertex AI Foundations & Intelligent Agent Development•30 minutes
3 discussion prompts•Total 15 minutes
Building the Right Setup•5 minutes
Building with ADK and Agent Engine•5 minutes
Staying Grounded and Translated•5 minutes
Advanced Model Tuning, Evaluation & Deployment on Vertex AI
Module 4•3 hours to complete
Module details
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.
Fine-Tuning Gemini Models for Optimal Performance•4 minutes
Tuning Embeddings, Imagen, and Translation Models•4 minutes
Migrating from Google AI to Vertex AI Using the OpenAI Library•5 minutes
Introduction to Model Evaluation on Vertex AI•5 minutes
Defining Evaluation Metrics and Preparing Your Dataset•4 minutes
Running and Interpreting Model Evaluation Results•4 minutes
Customizing Judge Models for Enhanced Evaluation•4 minutes
Model Deployment Strategies and Provisioned Throughput•4 minutes
Optimizing Cost, Latency, and Performance in AI Systems•6 minutes
Efficiency Boost: Caching, Batching and Throughput•3 minutes
4 readings•Total 60 minutes
Tuning Recommendations with LoRA and QLoRA•15 minutes
Fine-Tuning a Small Text Model in Vertex AI•15 minutes
Performing Evaluation with the Python SDK•15 minutes
Module Summary: Advanced Model Tuning, Evaluation & Deployment on Vertex AI•15 minutes
4 assignments•Total 48 minutes
Practice Quiz: Model Tuning and Optimization on Vertex AI•6 minutes
Practice Quiz: Evaluating and Customizing Generative AI Models•6 minutes
Practice Quiz: Deploying Generative AI Models for Production•6 minutes
Knowledge Check: Advanced Model Tuning, Evaluation & Deployment on Vertex AI•30 minutes
3 discussion prompts•Total 15 minutes
Beyond Text: Imagen and Translation•5 minutes
Metrics That Matter•5 minutes
Balancing the Trade-offs•5 minutes
Course Wrap-Up and Assessment
Module 5•2 hours to complete
Module details
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
Show info about module content
1 video•Total 4 minutes
Course Summary•4 minutes
2 assignments•Total 90 minutes
End Course Knowledge Check: Gemini and Vertex AI: Building Intelligent Applications•60 minutes
Building a Multimodal AI-Powered Healthcare Assistant with Gemini and Vertex AI•30 minutes
1 discussion prompt•Total 5 minutes
Describe Your Learning Journey•5 minutes
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themselves with industry-relevant skills in today’s cutting edge technologies.
A practical introduction to Gemini AI using Google AI Studio and GCP for multimodal AI and code generation.
Who should take this course?
Developers, data scientists, and tech professionals seeking hands-on Gemini demos and practical workflows.
Do I need prior experience?
No; basic Python or ML familiarity is helpful but not required.
Which tools and platforms are used?
Gemini APIs, Google AI Studio, and select Google Cloud Platform (GCP) services.
What programming language is used?
Primarily Python, with patterns transferable to other languages.
Does this course cover multimodal AI?
Yes, working with text, images, and code via Gemini’s multimodal capabilities.
What outcomes can I expect?
Confidence using Gemini for practical demos, cleaner prompts and structured outputs, and a clear conceptual view of Vertex AI.
What setup do I need to follow the demos?
A modern browser, a Google account, and basic Python tools are sufficient however, GCP is recommended.
Are there quizzes or checks for understanding?
Yes, short knowledge checks and guided exercises after each section.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.