Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
AI, Generative AI, and Agentic AI for Cybersecurity: A Practical, Hands-On Approach Using Python

AI, Generative AI, and Agentic AI for Cybersecurity: A Practical, Hands-On Approach Using Python

Az, Bhat

Paperback

Computer Security

ISBN13: 9798275560633
Publisher: Independently Published
Published: Nov 22 2025
Pages: 418
Weight: 2.12
Height: 0.85 Width: 8.50 Depth: 11.00
Language: English
AI, Generative AI, and Agentic AI for Cybersecurity: A Practical, Hands-On Approach Using Python is written for a new era in security operations, where adversaries are faster, attacks are more automated, and defenders must rely on intelligent systems to keep pace. Traditional defenses built on signatures, static rules, and isolated tools no longer scale against today's threat landscape. This book provides a grounded, intuitive, and highly practical journey into how AI can transform the SOC: from enhancing telemetry understanding to spotting anomalies, prioritizing threats, accelerating incident response, and ultimately enabling autonomous decision-support. Whether you are an analyst, engineer, student, or security leader, this book welcomes you into the world of AI-augmented cyber defense without requiring a machine learning or math background.

This book is also deeply hands-on. Each concept connects to real security workflows and is backed by lightweight, executable Python examples that demonstrate how data can be shaped, analyzed, and used to drive intelligent detections and response. From descriptive analytics to behavioral modeling, from synthetic datasets to step-by-step capstones, and from generative intelligence to agentic copilots, the chapters build a complete learning path grounded in realism but free from proprietary systems. By the end, readers will not only understand how AI, GenAI, and agents apply to cybersecurity, they will be able to prototype their own tools, reason about their limitations, and integrate these capabilities responsibly into modern SOC environments.

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