Course Description
This introductory course provides a concise overview of Agentic AI systems, covering their evolution, current state, and practical applications. You will explore key topics including the history of Agentic AI systems, the role of agents today, multi-agent systems, and practical solutions for implementing them. Perfect for those seeking a foundational understanding of intelligent Agentic AI systems in action.
Course curriculum
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1
Creating Problem-Solving Agents using GenAI for Action Composition
- Introduction
- Overview- Count the Number of Agents
- A brief history of Agentic Systems
- Agents Today
- Multi-Agent Systems Today
- Practical Solutions
Certificate of Completion
Who should Enroll?
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Beginners in AI and ML looking to understand agentic systems and their real-world applications.
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Tech enthusiasts and developers interested in learning the basics of creating intelligent, problem-solving agents.
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Professionals exploring multi-agent systems for automation and dynamic task orchestration in various domains.
About the Instructor
Vikas Agrawal - Senior Principal Data Scientist at Oracle Analytics Cloud
Frequently Asked Questions (FAQs)
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What is an agentic system?
An agentic system refers to an AI-based structure where agents can autonomously perform tasks, often in collaboration, to solve complex problems.
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Do I need prior AI knowledge to take this course?
No, this course is beginner-friendly and provides an introduction to agentic systems and their applications.
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Are there any hands-on projects in this course?
Yes, you will see practical demos that illustrate how agents are created and used in real-world applications.
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How will this course benefit me professionally?
You'll gain foundational knowledge of AI agents, enabling you to apply these concepts to automation, AI development, and other tech projects involving intelligent systems.
Key Takeaways
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Understand the evolution and current capabilities of agentic systems.
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Learn the basics of agents and multi-agent systems, including their role in solving complex problems.
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Gain insights into practical applications of agents and how they function in real-world scenarios.