AI Forward Deployed Engineer: 52-Week Mastery
This course contains the use of artificial intelligence.Become an AI Forward Deployed Engineer who can transform ambitious AI ideas into secure, scalable, measurable, production-ready enterprise solutions.AI Forward Deployed Engineer: 52-Week Mastery is a comprehensive, hands-on program designed for developers, AI engineers, software engineers, solution architects, technical consultants, and technology professionals who want to master production AI engineering, Generative AI, Retrieval-Augmented Generation (RAG), AI agents, cloud deployment, enterprise integration, and customer-facing technical delivery.Over 52 weeks, you will learn the complete AI solution delivery lifecycle, from customer discovery and requirements gathering to architecture, development, testing, deployment, monitoring, governance, and business value measurement. You will learn how Forward Deployed Engineers identify high-value business problems, define technical requirements, design practical architectures, build rapid prototypes, integrate enterprise systems, and move AI applications into production.The course begins with essential engineering skills including Python, FastAPI, REST APIs, SQL, Git, backend development, testing, logging, data pipelines, and API integration. You will build reliable AI services that connect models with databases, documents, enterprise applications, APIs, and business workflows.You will then explore machine learning and Generative AI, including large language models, prompt engineering, structured outputs, context management, model selection, latency optimization, token management, and AI cost optimization. You will build secure conversational AI applications with guardrails, user sessions, feedback systems, and human approval workflows.A major focus of the program is Retrieval-Augmented Generation (RAG). You will work with embeddings, vector databases, semantic search, hybrid search, metadata filtering, reranking, document ingestion, citations, hallucination reduction, and RAG evaluation. You will build enterprise knowledge assistants that generate grounded answers using trusted organizational information.You will also design AI agents and multi-agent systems capable of using tools, calling APIs, querying databases, maintaining memory and state, recovering from failures, and escalating sensitive actions to humans. Advanced topics include agent routing, supervisor-worker architectures, multi-agent orchestration, shared context, tool calling, and the Model Context Protocol (MCP).Production engineering modules cover Docker, CI/CD pipelines, cloud deployment, secrets management, scaling, observability, tracing, monitoring, rollback strategies, incident response, reliability, and AI cost tracking. You will learn how to deploy and operate AI applications safely in real enterprise environments.The program also covers AI security and governance, including prompt injection defense, access control, privacy, responsible AI, audit logging, data protection, human oversight, and enterprise AI risk management.Throughout the course, you will complete hands-on exercises, architecture challenges, customer-style scenarios, and portfolio projects. You will practice customer discovery, stakeholder communication, solution demonstrations, technical trade-off discussions, and business-value presentations.The 52-week journey concludes with a complete enterprise AI capstone project that you will design, build, deploy, document, evaluate, and present.By the end of the program, you will have practical experience across AI engineering, RAG, Generative AI, AI agents, FastAPI, APIs, Docker, cloud deployment, enterprise architecture, AI security, governance, technical consulting, and customer-facing delivery—the core skills required for modern AI Forward Deployed Engineer roles.No advanced AI background is required. The curriculum progresses from foundational software engineering to production-grade enterprise AI delivery, giving you a structured roadmap and portfolio evidence to demonstrate your ability to solve real-world AI problems.
