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Free Agentic AI Course
Getting Started with Agentic AI
Enroll in our free Agentic AI course to learn how intelligent systems make decisions independently. You will gain hands-on experience with the latest tools to develop your problem-solving skills and earn a completion certificate.
Instructor:
Mr. Amish SuchakGetting Started with Agentic AI
11.1K+ learners enrolled so far
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Skills you will gain
Fundamentals of AI Agents
AI Agent Core Components
Agent Planning
Agent Reasoning
Agent Execution
Agent Memory Systems
AI Agent Design Patterns
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Key Highlights
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About this course
Getting Started with Agentic AI is a free course for beginners who are interested in the topic of autonomous decision-making machines and their impact on intelligent technologies of the future. The journey will begin from the basics of agentic intelligence and continue through exploring the use of Generative Agentic Intelligence agents in various industries and what they entail, including the basic concepts of planning, reasoning, execution, and memory.
At the completion of this course, learners will be able to grasp how Generative Agentic Intelligence agents work and how to think like an engineer developing intelligent systems.You will also receive a certificate to showcase your skills and step into the fast-growing world of AI.
Stand out with an industry-recognized certificate
10,000+ certificates claimed, get yours today!
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Share on professional channels
Globally recognised
Land your dream job
Course outline
Introduction to Agents
In this module, you will be introduced to what AI agents actually are, how they operate, and what effect they have on modern software technology.
Generative AI Agents: Use Cases
In this module, you will be introduced to the use cases of Generative AI agents where they can create new opportunities for business by transforming user experience.
Opportunities and Challenges in GenAI Agents
The module will help you explore the various opportunities and limitations associated with Generative AI agents including the challenges, risks, and limitations.
Core Components of AI Agents
In this module, you will understand the process through which an AI agent works based on its main components which include planning, reasoning, execution, and memory.
Get access to the complete curriculum once you enroll in the course
Getting Started with Agentic AI
4.57
3.0 Hours
Beginner
11.1K+ learners enrolled so far
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Master in-demand skills & tools
Test your skills with quizzes
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Highly Recommended
Johns Hopkins University
Certificate Program in Agentic AI
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Learner reviews of the Free Courses
5.0
Our course instructor
Mr. Amish Suchak
Data Science Team Lead @ XSOLIS
ChatGPT and Generative AI Expert
Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
What is Agentic AI?
Agentic AI refers to the autonomous systems that use intelligent models to process environmental data, learn from feedback, and solve problems without human intervention.
Who is this course for?
The free Agentic AI course is a beginner’s guide to autonomous decision-making systems. This course is helpful for people who have no background in AI and programmers who want to work with Agentic AI systems.
What is the difference between Generative AI and Agentic AI?
The key distinction between Generative AI and Agentic AI is:
Generative AI generates new content (text, images, music) based on the learned patterns from the existing data. Generative AI focuses on content generation
Agentic AI makes autonomous decisions and takes actions to achieve specific goals. Agentic AI focuses on decision-making and actions.
Do I need prior programming experience to take this course?
The course does not demand prior programming experience from learners. The course provides essential coding education, which includes hands-on Python development that allows you to create your own AI models. Mastering basic programming principles can enhance learning, but it is not necessary.
What tools and technologies will I learn to use in this course?
In this program, you will learn to:
- Build Q-learning reinforcement learning algorithms as your practical assignments.
- Learn to program in Python to facilitate AI development.
- Run AI framework software to develop autonomous systems.
- Improve the decision-making processes in these systems.
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