Building AI-Powered Products
From Idea to Production: Create Real AI Applications
Move beyond using AI to building with AI. This course teaches you to create production-ready AI applications. You'll learn to integrate AI APIs, build RAG (Retrieval Augmented Generation) systems, work with vector databases, optimize costs, and deploy scalable AI products. Practical, hands-on, production-focused.
What You'll Learn
- ✓Integrate OpenAI, Anthropic, and open-source AI APIs
- ✓Build RAG systems for custom knowledge bases
- ✓Work with vector databases (Pinecone, Weaviate, Chroma)
- ✓Design effective prompts for production use
- ✓Test and evaluate AI system quality
- ✓Manage costs and optimize API usage
- ✓Deploy and scale AI applications
- ✓Handle ethics, safety, and compliance
Prerequisites
- •Basic programming skills (Python or JavaScript)
- •Understanding of APIs and web development
- •Familiarity with AI concepts from beginner courses
Who This Is For
- →Developers building AI features
- →Product managers shipping AI products
- →Entrepreneurs creating AI startups
- →Technical founders
Course Modules
AI Product Strategy: When AI Makes Sense
Determine if AI is right for your product. Learn to identify good AI use cases and avoid common pitfalls.
API Integration: OpenAI, Anthropic, Open Source
Integrate AI APIs into your application. Compare providers and implement production-ready integrations.
Building RAG Systems from Scratch
Build Retrieval Augmented Generation systems. Give AI access to your custom knowledge base.
Vector Databases and Embeddings
Work with vector databases for semantic search. Choose and implement the right solution.
Prompt Engineering for Production
Design robust prompts for production systems. Handle edge cases and ensure consistent quality.
User Experience for AI Products
Design UX for AI features. Manage expectations, handle failures, and build trust.
Testing and Evaluation
Test AI systems systematically. Build evaluation frameworks and catch issues before users do.
Cost Management and Optimization
Control AI costs at scale. Optimize token usage, caching, and model selection.
Deployment and Scaling
Deploy AI products to production and scale reliably. Handle traffic spikes and ensure uptime.
Ethics, Safety, and Compliance
Build responsible AI products. Handle sensitive data, prevent misuse, and ensure compliance.
Free Resource
AI Product Builder's Toolkit
Complete toolkit with code templates, API integration examples, RAG implementation guide, cost calculator, and production checklists.
Download Free Resource