The Complete Guide To Google Gemini (With Gemini Ultra!) Course Syllabus

Full curriculum breakdown — modules, lessons, estimated time, and outcomes.

Overview (80-120 words) describing structure and time commitment.

Module 1: Introduction to Generative AI

Estimated time: 0.5 hours

  • What is generative AI and how does it work?
  • Key use cases across industries
  • Overview of Google’s AI capabilities

Module 2: Overview of Google Generative AI Studio

Estimated time: 0.75 hours

  • Navigating the AI Studio platform
  • Understanding available tools and APIs
  • Exploring model types in Google Cloud

Module 3: Prompt Engineering Basics

Estimated time: 1 hour

  • Writing effective prompts for AI tasks
  • Understanding temperature and token settings
  • Tuning parameters for better outputs

Module 4: Creating Text & Image Models

Estimated time: 1 hour

  • Building and testing text generation models
  • Generating visual content using Imagen
  • Hands-on practice with multimodal outputs

Module 5: Real-World Applications

Estimated time: 0.75 hours

  • Automating content creation and summarization
  • Code generation use cases
  • Case studies in marketing, education, and enterprise

Module 6: Ethical Use & AI Governance

Estimated time: 0.5 hours

  • Understanding bias in AI models
  • Ensuring transparency and accountability
  • Google’s principles for responsible AI

Module 7: Deploying & Scaling AI Projects

Estimated time: 0.75 hours

  • Integrating AI into apps and workflows
  • Managing models and APIs on Google Cloud
  • Strategies for scaling AI solutions

Module 8: Final Project

Estimated time: 1 hour

  • Design a text generation pipeline using Gemini
  • Create AI-generated images for a use case
  • Submit a responsible AI deployment plan

Prerequisites

  • Familiarity with Google Cloud Platform
  • Basic understanding of AI concepts
  • Access to a Google Cloud account

What You'll Be Able to Do After

  • Understand the fundamentals of generative AI and its applications
  • Use Google’s Generative AI Studio effectively
  • Create, test, and deploy AI models in real-world scenarios
  • Apply prompt engineering to text and image generation tasks
  • Deploy AI responsibly with ethical considerations
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