Google Gemini for Beginners: From Basics to Building AI Apps Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This course takes you from the fundamentals of Google Gemini to building and deploying AI-powered applications. With a hands-on, API-first approach, you'll explore text and image modalities, prompt engineering, embeddings, chat interfaces, and real-world deployment. Each module includes practical exercises and real-world integration scenarios. The course spans 8 modules, designed to be completed in approximately 8 weeks with a time commitment of 4-6 hours per week, totaling around 40 hours of learning and doing.
Module 1: Introduction to Google Gemini
Estimated time: 5 hours
- Overview of Gemini models (Ultra, Pro, Nano)
- API authentication and key management
- Setting up the Google AI Studio and API console
- Making your first generateText() API call
Module 2: Text Generation & Prompt Engineering
Estimated time: 5 hours
- Designing effective text prompts
- Controlling output length, format, and tone
- Handling edge cases and improving response quality
- Building a marketing copy generation microservice
Module 3: Embeddings & Semantic Search
Estimated time: 5 hours
- Generating text embeddings using Gemini
- Understanding vector representations and similarity
- Indexing document corpora for search
- Implementing a semantic search endpoint
Module 4: Image Understanding & Generation
Estimated time: 5 hours
- Image captioning with Gemini Vision
- Answering questions about image content
- Performing image-to-image transformations
- Building an app for tagging and describing uploaded images
Module 5: Chat & Conversational Interfaces
Estimated time: 5 hours
- Designing multi-turn conversations
- Maintaining context and session memory
- Implementing persona-based chatbots
- Adding fallback and error handling in chat flows
Module 6: Integration & Deployment
Estimated time: 6 hours
- Integrating Gemini API into web and mobile apps
- Using serverless functions for scalable AI features
- Implementing robust error handling and retries
- Deploying a Flask or Node.js app with Gemini endpoints
Module 7: Monitoring, Security & Cost Optimization
Estimated time: 5 hours
- Tracking API usage and setting rate limits
- Implementing logging and alerting systems
- Managing API quotas and budget controls
- Securing API keys and user data
Module 8: Capstone Project
Estimated time: 8 hours
- Designing an end-to-end Gemini-powered application
- Implementing and testing a complete AI feature set
- Presenting a demo of your AI-driven helpdesk assistant or similar app
Prerequisites
- Familiarity with REST APIs and HTTP requests
- Basic experience with web development (JavaScript or Python)
- Understanding of JSON and API authentication (API keys)
What You'll Be Able to Do After
- Use Google Gemini APIs to generate high-quality text and images
- Design and optimize prompts for real-world applications
- Implement semantic search and embedding pipelines
- Build and deploy conversational AI interfaces
- Integrate, monitor, and secure Gemini in production environments