Forward Deployed Engineer Program: GenAI, Agentic AI & RAG

About this course

This course contains the use of artificial intelligence.

For engineers with basic Python, SQL, API and Git knowledge, this course offers a structured path through production GenAI and Forward Deployed Engineering topics, including RAG, agent workflows, security and deployment. Review the curriculum and free previews to decide whether the level fits your experience.

Starting with essential foundations in Python, APIs, cloud computing, machine learning, and deep learning, you will progressively explore Large Language Model (LLM) architectures, transformer fundamentals, tokenization, embeddings, context engineering, and prompt optimization.

You will learn to build sophisticated Retrieval-Augmented Generation (RAG) applications, implement hybrid search and reranking strategies, work with vector databases, develop multimodal AI solutions, and customize models using techniques such as LoRA, QLoRA, and supervised fine-tuning.

The course then advances into Agentic AI and autonomous systems, where you will design intelligent agents capable of reasoning, planning, using tools, maintaining memory, and executing complex workflows. You will explore modern interoperability approaches, including Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication, to integrate AI agents with enterprise applications and services.

Beyond development, you will gain practical experience with enterprise AI security, authentication, authorization, guardrails, evaluation frameworks, observability, LLMOps, inference optimization, scalability, latency reduction, and cost management.

What makes this program distinctive is its emphasis on the complete Forward Deployed Engineering lifecycle.

You will learn how to translate customer requirements into technical architectures, build proofs of concept, integrate solutions with enterprise infrastructure, evaluate production readiness, manage deployments, and demonstrate measurable business value.

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