AI-powered learning
Trending
Save this course
Applied AI Engineer: Build, Evaluate, and Operate Production LLM
Build, evaluate, and operate production-ready LLM applications. Gain hands-on experience with RAG, agents, multimodal pipelines, deployment, and AI security.
4.7
39 Lessons
5h
Updated 1 week ago
Join 3.1 million developers at
Join 3.1 million developers at
LEARNING OBJECTIVES
- Select LLMs and define the operational requirements for production AI applications.
- Build RAG pipelines and multi-step agents using hybrid search, chunking, and tool workflows.
- Evaluate and fine-tune LLMs with structured outputs, automated test suites, and A/B testing.
- Deploy LLM pipelines as API microservices optimized for cost, latency, and throughput.
- Integrate speech, vision, and image generation into a reliable multimodal pipeline.
- Secure AI systems with adversarial defenses, PII protection, bias testing, and layered guardrails.
KEY OUTCOMES
Architect Production-Grade AI Systems
Build resilient AI applications that effectively integrate model selection, retrieval architectures, and deployment strategies.
Optimize RAG Pipelines
Implement efficient hybrid search and chunking strategies to enhance the performance and reliability of AI workflows.
Evaluate AI Model Performance
Conduct thorough evaluations and fine-tuning of LLMs using automated testing and structured evaluation sets.
Secure AI Applications
Deploy comprehensive safety and privacy measures to protect production AI systems from adversarial threats and data breaches.
Why choose this course?
Stay Relevant in a Rapidly Evolving Field
As AI technology advances, developers face the fear of becoming obsolete. Without mastering production-grade AI systems, your skills may not meet industry demands.
The Stakes Are High for Developers
Even skilled engineers struggle to implement robust AI solutions. Failing to adapt can lead to missed opportunities, stagnant careers, and the inability to deliver reliable applications.
Master Production-Grade AI Systems
This course equips you with the tools to build resilient AI applications. Learn to architect end-to-end systems, optimize performance, and ensure safety with practical, hands-on projects.
Elevate Your Career Today
Join a community of forward-thinking developers and gain the expertise needed to thrive in AI. Enroll now to secure your place at the forefront of AI engineering.
Learning Roadmap
2.
Foundations Refresher and LLM Landscape
Foundations Refresher and LLM Landscape
Master LLM operations, model selection, and efficient environment setup for production.
3.
Prompt Engineering for Production
Prompt Engineering for Production
4 Lessons
4 Lessons
Master effective AI interactions through prompt strategies, structured outputs, and testing.
4.
Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation (RAG)
5 Lessons
5 Lessons
Master vector-based retrieval techniques and build efficient RAG pipelines for AI applications.
5.
Agents and Tool Use
Agents and Tool Use
4 Lessons
4 Lessons
Master safe tool usage, agent frameworks, and effective memory management for AI systems.
6.
Fine-tuning and Customization
Fine-tuning and Customization
4 Lessons
4 Lessons
Master techniques for fine-tuning AI models, ensuring optimal performance and evaluation.
7.
Evaluation and Testing
Evaluation and Testing
4 Lessons
4 Lessons
Master evaluation techniques for large language models, focusing on relevance, faithfulness, and accuracy.
8.
Deployment and MLOps for AI Apps
Deployment and MLOps for AI Apps
4 Lessons
4 Lessons
Optimize LLM APIs with caching, logging, and CI/CD for reliable performance.
9.
Multimodal AI
Multimodal AI
4 Lessons
4 Lessons
Explore advanced techniques in multimodal AI, enhancing interactions across text, images, and audio.
10.
Responsible and Safe AI Engineering
Responsible and Safe AI Engineering
4 Lessons
4 Lessons
Enhance AI safety by addressing prompt risks, data privacy, bias, and content moderation.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Complete more lessons to unlock your certificate
Developed by MAANG Engineers
ABOUT THIS COURSE
Large language models power a growing range of products, but moving from a working prototype to a reliable production system takes more than good prompts. Applied AI engineering brings model selection, retrieval, agents, evaluation, and deployment together so applications stay accurate, affordable, and safe under real traffic.
You’ll start with LLM fundamentals and model selection, then build RAG pipelines with hybrid search and multi-step reasoning agents. Next, you’ll evaluate and fine-tune models, and deploy pipelines as API microservices with caching and CI/CD tests that catch hallucinations. You’ll then combine speech, vision, and image generation into one multimodal pipeline. You’ll finish by securing systems against prompt injection, protecting PII, testing for bias, and adding layered guardrails and monitoring.
By the end, you’ll be able to build, evaluate, and operate production-ready LLM applications that stay reliable, cost-efficient, and secure.
ABOUT THE AUTHOR
Khayyam Hashmi
Computer scientist and Generative AI and Machine Learning specialist. VP of Technical Content @ educative.io.
Trusted by 3.1 million developers working at companies
A
Anthony Walker
@_webarchitect_
E
Evan Dunbar
ML Engineer
S
Software Developer
Carlos Matias La Borde
S
Souvik Kundu
Front-end Developer
V
Vinay Krishnaiah
Software Developer
Built for 10x Developers
No Passive Learning
Learn by building with project-based lessons and in-browser code editor
Personalized Roadmaps
The platform adapts to your strengths & skills gaps as you go
Future-proof Your Career
Get hands-on with in-demand skills
AI Code Mentor
Write better code with AI feedback, smart debugging, and "Ask AI"
MAANG+ Interview Prep
AI Mock Interviews simulate every technical loop at top companies
Free Resources
