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Home / Cybersecurity Certification / AI/GenAI for Cybersecurity

AI/GenAI for Cybersecurity Certification Training Program

Classroom Training and Live Online Courses

Revolutionize your cybersecurity practice with Artificial Intelligence and Generative AI. This program teaches you how to leverage LLMs, machine learning models, and AI agents for threat detection, automated incident response, malware analysis, phishing simulation, and security automation — preparing you to become an AI‑first security professional.

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60% hands-on labs & real‑world projects: build AI‑powered security assistants, automated SOC agents, and GenAI deception tools.

Curriculum covers LLM security, adversarial machine learning, prompt injection defense, AI-driven threat hunting, and safe GenAI integration.

Learn from AI security researchers and red‑teamers who specialize in offensive & defensive AI for enterprises.

AI/GenAI for Cybersecurity – Program Overview

Integrate Large Language Models (GPT‑4, Gemini, Claude) and classical ML into your security operations. Learn to automate alert triage, generate detection rules, simulate intelligent adversaries, and protect your organization from AI‑powered threats — all while understanding the unique risks of GenAI.

Course Highlights

✔ 60% hands-on labs • 15+ AI security projects • Build your own SOC copilot • Red‑team vs. Blue‑team AI simulations • Capstone: Autonomous security agent • 24/7 cloud lab access.

Skills You Will Gain

LLM prompt engineering for security, AI‑based log analysis, anomaly detection (isolation forest, autoencoders), GenAI for phishing generation/defense, AI security guardrails, adversarial ML, OWASP Top 10 for LLMs, and secure RAG pipelines.

Eligibility & Prerequisites

Basic knowledge of Python and cybersecurity fundamentals (threats, logs, network) is recommended. No prior AI/ML experience required — we start from basics.

Real-World Projects

Build a GenAI‑powered SIEM assistant, create an automated phishing detection system, develop an LLM‑based deception honeypot, and implement a RAG chatbot for security documentation.

Career Support

Mock tests, resume review, portfolio building, and interview preparation for AI Security Engineer, SecOps Automation Engineer, and Cyber AI Specialist roles.

Corporate Training

Tailored AI security upskilling for teams and enterprises

Custom Learning Paths

Choose from AI defense, offensive AI, or AI governance tracks.

Sandbox AI Environments

Hands-on labs with secure LLM playgrounds and Jupyter notebooks.

Team Dashboards

Monitor progress and skill gaps with detailed analytics.

Flexible Pricing

Volume discounts for teams of 10+, plus pay-as-you-go options.

24/7 Lab Support

Dedicated AI security mentors to assist your learners anytime.

Account Manager

Single point of contact for seamless training delivery.

AI Cybersecurity Corporate Training - Coding Now

Ready to upskill your team on AI‑driven security?

Get a custom quote for your organization's GenAI security training.

Skills You Will Gain In Our AI/GenAI for Cybersecurity Program

From LLM Security to Autonomous Defense Agents

LLM Security & Prompt Engineering for Defense

Master prompt injection prevention, output filtering, and secure prompt design. Build system prompts that resist adversarial manipulation.

AI‑Powered Threat Detection & Log Analysis

Use transformer models and LLMs to parse massive log volumes, detect anomalies, and generate natural language incident summaries.

Generative AI for Deception & Honeypots

Create dynamic, AI‑generated decoy content and realistic fake infrastructure to lure attackers.

Adversarial Machine Learning & Model Hardening

Understand evasion attacks, data poisoning, and model extraction. Defend with adversarial training and robust ML pipelines.

Secure RAG (Retrieval-Augmented Generation)

Build safe GenAI applications that retrieve internal security knowledge without leaking sensitive data.

Automated Incident Response with AI Agents

Develop autonomous agents that triage alerts, execute playbooks, and escalate with human‑in‑the‑loop.

Who This Program Is For

Ideal Candidates for AI/GenAI for Cybersecurity Certification

Security Analysts / SOC Engineers

Penetration Testers & Red Teamers

AI/ML Engineers entering cybersecurity

DevSecOps & Cloud Security Engineers

GRC / Compliance professionals exploring AI risks

Security Architects designing AI‑first defenses

Designed for cybersecurity and IT professionals with basic Python skills and security awareness. This program bridges AI technology with security operations, making you a pioneer in one of the fastest‑growing fields. Average salaries for AI Security Engineers in India range from ₹12 Lakhs to ₹30+ Lakhs per year.

AI/GenAI for Cybersecurity – Program Roadmap

Your Step‑by‑Step Path to AI‑Powered Defense

AI Cybersecurity Roadmap - Learning path at Coding Now

Step 1: Foundations of AI & Machine Learning

Learn core AI/ML concepts, Python for data science, and apply them to security datasets like logs and network flows.

Eligibility and Prerequisites for AI/GenAI for Cybersecurity Certification

What You Need Before You Start

Objective: To certify your ability to design, implement, and defend AI‑powered security solutions. Candidates should have:

PREREQUISITES:

Basic Python Programming:

Ability to write simple scripts, use pandas and REST APIs. We provide a Python refresher module.

Cybersecurity Fundamentals:

Understanding of common threats, log formats (Syslog, JSON), and basic incident response steps.

Willingness to Learn AI Tooling & Ethics:

No prior ML experience required — we start from data preprocessing and model training for security use cases.

Course Modules & Curriculum

Comprehensive AI cybersecurity modules – from ML basics to GenAI security agents

Module 1

Foundations of AI/ML for Security Analysts

Lesson 1: AI/ML Basics & Python for Security Data

Supervised vs. unsupervised learning, feature engineering. Work with Pandas, Scikit‑learn on security logs.

Lesson 2: Anomaly Detection in Practice

Implement Isolation Forest, One‑Class SVM, and Autoencoders to detect rare security events.

Module 2

Large Language Models (LLMs) for Security

Lesson 1: Introduction to LLMs (GPT, Gemini, Claude, Llama)

Prompt engineering, API usage, and open‑source models. Understand tokenization and embeddings.

Lesson 2: LLM for Log Triage & Incident Summarization

Use LLMs to parse alerts, enrich incidents, and generate human‑readable executive summaries.

Module 3

Prompt Engineering & LLM Security (OWASP Top 10)

Lesson 1: Prompt Injection & Jailbreak Defenses

Attack techniques: indirect injection, role‑play bypass. Defenses: input sanitization, output filtering, moderation APIs.

Lesson 2: Secure RAG Architectures

Build retrieval‑augmented generation systems that respect access controls and prevent data leakage.

Module 4

Generative AI for Offensive Security (Red Team)

Lesson 1: Automated Phishing & Social Engineering

Generate convincing spear‑phishing emails, realistic lures, and pretexts using GenAI.

Lesson 2: AI‑Powered Payload Generation

Use LLMs to mutate malware, evade signatures, and create dynamic exploit variations.

Module 5

Adversarial Machine Learning & Model Hardening

Lesson 1: Evasion Attacks (FGSM, PGD) & Poisoning

Craft adversarial examples, manipulate training data, and understand model stealing.

Lesson 2: Defenses – Adversarial Training & Robustness

Implement adversarial training, input preprocessing, and certified robustness techniques.

Module 6

AI Agents for Automated Incident Response

Lesson 1: Building SOAR Agents with LLMs

Use LangChain, AutoGen, or CrewAI to create autonomous triage and containment agents.

Lesson 2: Human‑in‑the‑Loop & Playbook Integration

Integrate with SIEMs, ticketing systems, and orchestration workflows.

Module 7

GenAI for Deception: Dynamic Honeypots & Disinformation

Lesson 1: AI‑Generated Decoy Assets

Create realistic fake documents, databases, and network services to trap attackers.

Lesson 2: Adaptive Interaction with Attackers

Use LLMs to converse with intruders in honeypots, wasting their time and gathering intelligence.

Module 8

Privacy, Compliance & AI Governance

Lesson 1: AI Risks & Regulations (EU AI Act, NIST AI RMF)

Understand compliance requirements for AI in security operations.

Lesson 2: Privacy‑Preserving ML (Differential Privacy, Federated Learning)

Apply techniques to train models without exposing sensitive data.

Module 9

Defending Against AI‑Powered Attacks

Lesson 1: Deepfake Detection & Biometric Spoofing

Identify synthetic media, voice cloning, and AI‑generated disinformation.

Lesson 2: AI‑Based Threat Hunting & Forensics

Use LLMs to correlate disparate data sources and uncover stealthy intrusions.

Module 10

Capstone Project: Autonomous Security Agent

Lesson 1: Design & Implementation

Build a fully autonomous agent that ingests logs, detects threats, explains decisions, and recommends containment actions.

Lesson 2: Evaluation & Certification Prep

Test agent efficacy; review LLM security patterns and adversarial ML concepts for final assessment.

E-LEARNING

₹9999

AI/GenAI for Cybersecurity Course

Lifetime Access

Real AI Security Projects

Mentor Support

Practice Assignments

Certificate Preparation

Ready to Lead the AI‑Powered Security Revolution?

Join 9,800+ forward‑looking defenders who have mastered AI/GenAI for cybersecurity. Be part of the next generation of security professionals who defend faster, smarter, and at scale.

✅ Limited seats available for the upcoming batch • EMI options available • Includes LLM API credits

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