AI Agents and Workflows: Build Intelligent Automations with Python

Artificial intelligence is evolving from simple chat interfaces into autonomous systems that can think, plan, and execute tasks. Understanding how to build these agentic workflows is the key to unlocking the next generation of software automation. This text-based course guides you through the core concepts of AI agents and structured workflows, moving past the industry buzzwords to focus on practical, programmatic implementation. You will transition from writing basic prompts to developing sophisticated multi-agent systems that can manage memory, interact with external tools, and self-evaluate their outputs. What you'll learn: - Understand the foundational differences between linear AI workflows and autonomous agentic systems. - Build multi-agent architectures that share data, delegate specialized tasks, and collaborate to solve complex problems. - Implement short-term and long-term memory systems to help your agents maintain context across interactions. - Integrate external APIs and tools, enabling your agents to interact with third-party services and real-world data. - Apply retrieval-augmented generation (RAG) patterns and structured JSON outputs to ensure reliable, high-quality results. - Configure human-in-the-loop checkpoints to safely review and guide autonomous decision-making processes. You will start by exploring fundamental AI concepts and API mechanics before gradually constructing increasingly complex workflows, culminating in fully autonomous multi-agent systems. Through clear written explanations and practical Python code snippets, you will gain a deep, conceptual understanding of agentic design. This course is designed for beginners eager to explore AI engineering, requiring only a basic familiarity with Python and no prior experience with machine learning or AI APIs. Start reading today to begin building your own intelligent, autonomous AI applications.