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AI Engineering in Practice
This hands-on course teaches you the engineering practices that separate prototypes from production AI systems. You'll learn evaluation frameworks, deployment patterns, monitoring strategies, and cost optimization techniques used at scale.
11 lessons8 hoursAdvanced
Course in Development
This course is currently being created. Follow me to get notified when it launches.
What You'll Learn
Design evaluation frameworks for LLM outputs
Implement streaming responses and function calling
Deploy AI systems with proper observability
Monitor costs and optimize token usage
Build guardrails and safety mechanisms
Create an end-to-end AI product from scratch
Course Syllabus
1
The AI Engineering Mindset35 min
2
Evaluation Framework Design50 min
3
Streaming & Real-time Responses40 min
4
Function Calling Patterns45 min
5
Error Handling & Retries35 min
6
Caching Strategies40 min
7
Monitoring & Observability45 min
8
Cost Optimization Techniques40 min
9
Guardrails & Safety35 min
10
Deployment Patterns45 min
11
Capstone: Ship an AI Product60 min
Prerequisites
- •Experience with LLMs
- •Python and API development
- •Basic DevOps knowledge
About the Author
PB
Pranay Bathini
Senior Software Engineer @ Booking.com
Building streaming systems at scale by day, writing about them by night. Forever learner, occasional blogger, and firm believer that the best way to understand something is to teach it.
Member of Booking Holdings India AI Committee, working on AI-powered solutions for travel at scale.