AI applications are evolving beyond traditional chatbots into systems that can reason, use tools, manage state, and perform multi-step tasks. In this hands-on course, you’ll learn Developing AI Agents with DeepSeek, a practical course that helps developers build, control, evaluate, secure, and deploy AI agents using DeepSeek and modern agentic application patterns. Whether you want to understand agentic workflows, connect external tools, implement MCP, improve agent reliability, or deploy AI applications with FastAPI and Docker, this course gives you a structured starting point.

You’ll begin by exploring the foundations of AI agents, including agentic workflows, agent control, state, execution patterns, ReAct, Plan-and-Execute, Router agents, execution loops, tool calling, and the Model Context Protocol (MCP). Then, you’ll move into agent reliability and control by working with state management, task progress, iteration limits, failure recovery, human-in-the-loop approvals, multiple MCP tools, local DeepSeek models, and evaluation datasets. Finally, you’ll explore automated response evaluation, accuracy, relevance, groundedness, tool success metrics, prompt injection, data leakage, tool misuse, model size and quantization, FastAPI endpoints, request validation, health checks, and Docker-based deployment. By the end of this course, you will be able to: -Explain AI agents, agentic workflows, execution patterns, agent state, and the differences between chatbots, workflows, and agents. -Buildcontrolled DeepSeek agents using execution loops, tool calling, MCP integration, state management, and task progress tracking. -Implement agent reliability and control mechanisms using iteration limits, failure recovery, execution boundaries, and human-in-the-loop approvals. -Evaluate DeepSeek applications using structured datasets, automated response checks, accuracy, relevance, groundedness, and tool success metrics while identifying prompt injection, data leakage, and tool misuse risks. -Deploy DeepSeek applications through FastAPI and Docker using request validation, error handling, health checks, and production-oriented configuration. This course is designed for AI developers, Python developers, backend engineers, generative AI developers, software engineers, and anyone who wants to understand how reliable and controlled AI agents are designed, evaluated, secured, and deployed. If you are new to agentic AI or want a practical path from basic DeepSeek integration to tool-enabled and deployment-ready AI agents, this course provides a guided learning experience. You should have basic experience with Python and generative AI concepts. Familiarity with APIs, JSON, command-line usage, and Docker is helpful, along with a willingness to practice through hands-on agent development, evaluation, security testing, and deployment tasks. Enroll now and learn how to build controlled, reliable, secure, and deployment-ready AI agents with DeepSeek.