Bundle4 courses
The Autonomous Systems & Agentic Engineering Suite
Built for software engineers and AI developers looking to architect, test, and deploy production-grade RAG pipelines, autonomous agents, and evaluation frameworks.
What you'll gain
Build end-to-end RAG pipelines and multi-step autonomous agents capable of real-world task execution.Implement automated evals and quality metrics to reliably measure model performance and output quality.Deploy output guardrails to prevent hallucination, data leakage, and unwanted model behaviors in production.Integrate persistent memory mechanisms to maintain state, context, and history across complex agent sessions
Skills you will gain
- RAG Architecture & Retrieval
- Production Agent Engineering
- LLM Evals & Benchmarking
- System Guardrails & Safety
About this bundle
Transition your AI applications from basic prototypes to reliable, production-ready enterprise systems. This comprehensive bundle guides software engineers and AI developers through the end-to-end engineering lifecycle of autonomous agents and Retrieval-Augmented Generation (RAG) systems. You will learn how to design agentic architectures, implement robust evaluation methodologies, set up guardrails for system safety, and integrate long-term memory for stateful AI interactions.
Courses in this bundle
4 courses · 64 lessons. One code opens them all.
intermediateBuilding Production-Ready RAG & Agentic SystemsA hands-on, developer-focused course designed to guide software engineers and data practitioners through the core concepts, patterns, and tooling required to build, evaluate, and deploy intelligent AI systems using modern Python frameworks, vector databases, and orchestration libraries.2 modules3 lessons
intermediateBuilding Your First Production AgentA hands-on course for engineers who already call LLM APIs and want to ship a tool-using agent that survives production: recovering from failed tool calls, capping runaway spend, extending itself with an MCP server, passing task-completion evals, and deploying with logging enabled.7 modules23 lessons
foundationalLLM Guardrails, Evals and Agentic MemoryLearn to take LLM applications from prototype to production.5 modules22 lessons
intermediateEvaluating LLM Output QualityHow to tell whether an LLM feature is actually working.5 modules16 lessons
Common questions
Do I need programming experience for this bundle?
Yes. This bundle is designed for software engineers, backend developers, and AI practitioners who already call LLM APIs and want to ship production-grade software.
Does this cover testing and quality evaluation?
Yes. Two of the courses focus specifically on evaluating LLM output quality, setting up guardrails, and building robust evaluation pipelines.
What frameworks or concepts are covered?
You will cover RAG architecture, agent orchestration, memory management, evaluation metrics, and guardrail implementation for production LLM deployments.
How is this bundle different from basic prompting courses?
Unlike basic prompting, this suite focuses on backend system design, infrastructure stability, state management, and reliable software deployment.