[100% Off] Ai Agents: From Foundations To Enterprise Systems
Design, build, deploy, and govern intelligent AI agents across workflows, teams, and enterprise environments
What you’ll learn
- Design and implement single-agent and multi-agent AI systems using modern agent architectures
- Build AI agents with memory, planning, reasoning, and tool-calling capabilities
- Deploy retrieval-augmented, data-driven, and multi-modal AI agents for real-world tasks
- Orchestrate, monitor, and optimize agent workflows for performance, cost, and reliability
- Apply security, governance, and responsible AI principles to production-grade agents
- Integrate AI agents into enterprise workflows across HR, finance, IT, and operations
Requirements
- No prior experience with AI agents or agent frameworks is required
- Basic familiarity with programming concepts (any language) is helpful but not mandatory
- Comfort using a computer, web tools, and cloud-based applications
- Willingness to experiment, troubleshoot, and learn through hands-on labs
- Access to a laptop or desktop with internet connectivity
- Optional: prior exposure to Python, APIs, or LLM tools will accelerate learning but is not required
Description
Disclaimer:
This course contains the use of artificial intelligence(AI).
AI agents are rapidly transforming how software is built, decisions are made, and work gets done across industries. This course is a comprehensive, hands-on journey into designing, building, and deploying intelligent AI agents—from foundational concepts to enterprise-grade systems. Over 52 structured weeks, learners progress step by step through the full lifecycle of agentic AI without relying on a single capstone project, ensuring continuous, practical learning every week.
You begin by mastering the core foundations of AI agents, including agent architectures, perception–action loops, reasoning, planning, and memory. Early modules focus on understanding how large language models power modern agents, how prompts differ from programs, and how agents decompose complex goals into executable tasks. Through guided labs, you build your first agents, add memory, enable tool usage, and implement structured reasoning patterns that go far beyond simple chatbots.
As the course progresses, you move into agent frameworks, orchestration, and multi-agent collaboration. You learn how agents communicate, delegate tasks, resolve conflicts, and operate as coordinated systems rather than isolated components. Hands-on labs emphasize real execution—building sequential and parallel workflows, debugging agent failures, evaluating outputs, and optimizing for latency and cost. You gain practical experience designing agents that are reliable, explainable, and measurable.
A major focus of the course is knowledge-driven and data-aware agents. You build retrieval-augmented agents, integrate structured and unstructured data sources, work with documents, and design long-term memory systems that persist and evolve over time. You also explore advanced capabilities such as multi-modal agents that reason across text, images, and audio, as well as real-time and event-driven agents that respond dynamically to changing inputs.
The course then shifts into enterprise-grade agent systems. You learn how to secure agents, prevent prompt injection, enforce governance, and design human-in-the-loop workflows. Topics such as observability, monitoring, versioning, scaling, and cost optimization prepare you to deploy agents in production environments. Ethical considerations and responsible AI practices are woven throughout, ensuring agents are safe, transparent, and aligned with organizational policies.
In the final phase, you apply agentic AI across real business domains including HR, finance, sales, IT operations, compliance, research, and personal productivity. Each week includes multiple topics, two hands-on labs, and a practical homework assignment, reinforcing skills through continuous application rather than a single end-of-course project.
By the end of this course, learners will confidently design, build, deploy, and govern AI agents that operate autonomously, collaborate effectively, and deliver real business value—equipping them with future-ready skills for the rapidly evolving world of agentic AI.
Author(s): Siam Hossain, School of AI
