Generative AI vs Agentic AI
Published 10/2025
Duration: 1h 19m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 944.13 MB
Genre: eLearning | Language: English
Published 10/2025
Duration: 1h 19m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 944.13 MB
Genre: eLearning | Language: English
Explore the key differences between Generative AI and Agentic AI, covering autonomy, decision-making, ethical implicatio
What you'll learn
- Understand the Foundations of AI/Evolution from rule-based systems to generative and agentic models
- Explore Generative AI/How Generative AI creates content (text, images, code, music)/Tools like ChatGPT, DALL·E, Midjourney/Use cases in marketing, design, writi
- Dive into Agentic AI/What makes AI agentic (autonomy, goal-setting, decision-making)/Examples like AutoGPT, ReAct agents/Applications in automation, task manage
- Compare Generative vs Agentic AI/Key differences in autonomy, memory, learning, and interaction/Visual frameworks to distinguish their roles in real-world scena
- Hands-On Practice on Prompt engineering for generative models,Designing workflows for agentic systems,Ethical considerations and limitations
Requirements
- No Programming and IT skills required in this
Description
This Course has been designed carefully for all who are enthusiastic about Artificial Intelligence evolution.
Welcome toGenerative AI vs Agentic AI, a comprehensive course designed to demystify two of the most transformative paradigms in artificial intelligence. As AI continues to evolve, understanding the distinction between generative models and agentic systems becomes crucial for developers, researchers, and decision-makers.
In this course, you’ll dive deep into the foundations ofGenerative AI, which focuses on creating content—text, images, code, and more—based on learned patterns. You’ll explore how models like GPT and diffusion models work, their training processes, and their applications across industries.
On the other hand,Agentic AIrefers to systems capable of autonomous decision-making, goal-setting, and interaction with environments. These agents go beyond pattern generation to exhibit behaviors that resemble reasoning, planning, and adaptation. We’ll examine frameworks like reinforcement learning, multi-agent systems, and emerging agentic architectures.
Through engaging lectures, hands-on projects, and real-world case studies, you’ll gain a clear understanding of:
The technical and philosophical differences between Generative and Agentic AI
Use cases in business, healthcare, education, and robotics
Ethical considerations and future implications of autonomous systems
By the end of this course, you’ll be equipped to critically evaluate AI systems, design intelligent solutions, and contribute meaningfully to the future of AI.
Who this course is for:
- • AI/ML Enthusiasts and Beginners
- • Data Scientists and Software Engineers
- • Product Managers and Business Leaders
- • Anyone interested in the future of AI and automation
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