What will you learn in Google Gemini for Beginners: From Basics to Building AI Apps Course
Grasp the fundamentals of Google Gemini’s capabilities and use cases
Interact with Gemini via API: text prompts, images, embeddings, and chat
Integrate Gemini into applications for content generation, summarization, and Q&A
Fine-tune prompt design and handling for optimal responses
Apply best practices for security, rate limits, and monitoring in production
Program Overview
Module 1: Introduction to Google Gemini
⏳ 1 week
Topics: Overview of Gemini models (Ultra, Pro, Nano), API authentication, and console setup
Hands-on: Obtain API keys and make your first
generateText()call
Module 2: Text Generation & Prompt Engineering
⏳ 1 week
Topics: Crafting effective prompts, controlling output length and style
- Hands-on: Build a microservice that generates marketing copy and handles edge cases
Module 3: Embeddings & Semantic Search
⏳ 1 week
Topics: Generating embeddings, similarity search, vector databases
Hands-on: Index a document corpus and implement a semantic search endpoint
Module 4: Image Understanding & Generation
⏳ 1 week
Topics: Image captioning, visual Q&A, image-to-image transformations
Hands-on: Create an app that tags uploaded images and generates descriptive captions
Module 5: Chat & Conversational Interfaces
⏳ 1 week
Topics: Maintaining context, multi-turn dialogue, persona design
Hands-on: Develop a chatbot prototype with memory and fallback handling
Module 6: Integration & Deployment
⏳ 1 week
Topics: Embedding API calls into web/mobile apps, serverless functions, error handling
Hands-on: Deploy a Flask or Node.js app that serves Gemini-powered endpoints
Module 7: Monitoring, Security & Cost Optimization
⏳ 1 week
Topics: Usage tracking, rate limiting, API quotas, cost estimation
Hands-on: Implement logging, alerts, and budget controls for your Gemini integration
Module 8: Capstone Project
⏳ 1 week
Topics: End-to-end design, testing, and presentation of a Gemini-powered solution
Hands-on: Build and demo a complete application (e.g., AI-driven helpdesk assistant)
Get certificate
Job Outlook
Expertise in cutting-edge LLMs like Gemini is highly sought for roles in AI engineering, product management, and data science
Positions include AI Engineer, Prompt Engineer, NLP Specialist, and AI Product Manager
Salaries range from $120,000 to $200,000+ for experienced professionals integrating LLMs into products
Skills apply across industries: SaaS, healthcare, finance, and consumer apps leveraging AI
Specification: Google Gemini for Beginners: From Basics to Building AI Apps
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