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Explore the core principles of agentic AI, from foundational concepts and safe system setup to advanced prompting and reasoning strategies. Learn to design, implement, and secure intelligent agents using Python and modern LLM APIs.
This course introduces the essential building blocks of agentic AI, guiding learners through the evolution of AI systems, the architecture of autonomous agents, and the critical importance of safety and threat modeling. Delve into advanced prompt engineering, mastering the language of agents and leveraging reasoning frameworks such as ReAct and Chain of Thought. By the end of the course, you will be able to design, implement, and evaluate robust agentic systems that can perceive, reason, and act autonomously while maintaining security and reliability.
Learners progress through a blend of conceptual overviews, practical coding examples, and structured quizzes, ensuring a deep understanding of agentic AI foundations and advanced prompting techniques. The course emphasizes both theoretical frameworks and real-world implementation, enabling learners to build and secure intelligent agents from the ground up.
This course is part one of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey.
This course is based on Agentic AI Systems Design, Build, and Deploy Intelligent Agents, by Vinit Kumar Singh.
Copyright © 2026 Vinit Kumar Singh . All rights reserved. No part of this course may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
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