Do I need prior AI or machine learning experience?

No AI background is required. You need basic Python, command-line comfort, and familiarity with security concepts like SIEM, logs, and threats. The course teaches the AI layer from there - machine learning, LLMs such as ChatGPT and Claude, and RAG so you learn how AI is used in cybersecurity by building it yourself, not just studying theory.

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Cybersecurity Operations with AI: Build an AI-Powered SOC

Développez des compétences très recherchées grâce à un abonnement d'un an à Coursera Plus, désormais à 239 $. Profitez-en dès maintenant.

Ce cours n'est pas disponible en Français (France)

Nous sommes actuellement en train de le traduire dans plus de langues.

Cybersecurity Operations with AI: Build an AI-Powered SOC

Instructeurs : Aseem Singhal

Inclus avec En savoir plus

4 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

9 heures à compléter

Planning flexible

Apprenez à votre propre rythme

4 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

9 heures à compléter

Planning flexible

Apprenez à votre propre rythme

Ce que vous apprendrez

Explain AI in cybersecurity workflows and configure Python environments with AI APIs for security automation.
Build automated threat detection for phishing, network anomalies, malware, and IOC extraction using Python, ML, and LLMs.
Create automated incident response workflows for alert triage, investigation, containment, and ticketing using AI and Python.
Design production-ready AI security automation with RAG, playbooks, event-driven workflows, and adversarial AI defenses.

Compétences que vous acquerrez

Catégorie : Incident Management
Catégorie : Application Programming Interface (API)
Catégorie : Network Analysis
Catégorie : API Design
Catégorie : Security Awareness

Outils que vous découvrirez

Catégorie : Python Programming
Catégorie : ChatGPT

Détails à connaître

Certificat partageable

Ajouter à votre profil LinkedIn

Récemment mis à jour !

juin 2026

Évaluations

4 devoirs

Enseigné en Anglais

Découvrez comment les employés des entreprises prestigieuses maîtrisent des compétences recherchées

En savoir plus sur Coursera pour les affaires

logos de Petrobras, TATA, Danone, Capgemini, P&G et L'Oreal

Il y a 4 modules dans ce cours

Transform cybersecurity operations with AI-driven automation. In this hands-on course, cybersecurity professionals learn how to use Python, machine learning, and large language models (LLMs) such as ChatGPT and Claude to automate threat detection, alert triage, incident response, and security operations center (SOC) workflows.

Through real-world coding exercises and security datasets, you will build automated phishing detection systems, network anomaly detection models, threat intelligence enrichment pipelines, and AI-assisted investigation tools. You'll also learn how to integrate security APIs, develop automated response playbooks, implement Retrieval-Augmented Generation (RAG) for security knowledge management, and design production-ready security automation architectures. This course helps you understand how AI is used in cybersecurity to reduce manual workload and accelerate response. By the end of the course, you will have created a complete AI-powered SOC platform that combines detection, investigation, response, and analyst assistance into a unified workflow. Whether you're a SOC analyst, security engineer, or cybersecurity professional, you'll gain practical skills in AI cybersecurity automation, Python security scripting, SOAR workflows, incident response automation, and AI-powered threat analysis that can be applied immediately in modern security environments.

This foundational module establishes the context, architecture, and practical setup required for AI-powered security automation. Students learn why automation is critical for modern SOCs, understand different AI model types and their security applications, and set up their Python development environment with security-focused libraries and AI API integrations. Through hands-on demonstrations, learners compare manual versus automated workflows and build their first AI-integrated security scripts.

Inclus

11 vidéos2 lectures1 devoir1 évaluation par les pairs3 sujets de discussion

11 vidéosTotal 61 minutes

Intro Video to Course 3 minutes
Module Introduction 3 minutes
The Modern SOC Crisis: Alert Fatigue and Resource Gaps 6 minutes
AI as the Force Multiplier: Transforming Security Operations 5 minutes
Hands-On: Manual vs. AI-Automated Alert Analysis 9 minutes
Demystifying AI: ML vs. DL vs. LLMs for Security Practitioners 5 minutes
AI Model Types in Security Operations: Detection, Classification, and NLP 5 minutes
Hands-On: Building Your First Anomaly Detector with Python and AI 8 minutes
Setting Up Your Security Automation Environment 6 minutes
Connecting to AI APIs: ChatGPT and Claude Integration 7 minutes
Hands-On: Your First AI Security Pipeline 5 minutes

2 lecturesTotal 10 minutes

Welcome to the Course: Course Overview5 minutes
Security Orchestration, Automation and Response (SOAR) Explained 5 minutes

1 devoirTotal 20 minutes

Foundations of AI-Driven Security Operations20 minutes

1 évaluation par les pairsTotal 20 minutes

Hands-On-Learning: AI-Powered Firewall Alert Analyzer20 minutes

3 sujets de discussionTotal 25 minutes

Recognizing Alert Fatigue in Your Own Environment10 minutes
Matching AI Approaches to Real Security Problems10 minutes
Overcoming Barriers to AI Integration in Your Organization5 minutes

This module focuses on building automated detection systems for common security threats using Python and AI. Students develop practical skills in phishing detection, network anomaly identification, malware classification, and threat intelligence automation. Each lesson combines machine learning techniques with large language model capabilities to create sophisticated yet accessible detection systems that can be deployed in production environments.

Inclus

10 vidéos1 lecture1 devoir1 évaluation par les pairs3 sujets de discussion

10 vidéosTotal 48 minutes

Module Introduction 2 minutes
Anatomy of Phishing Attacks: What Makes Them Work 5 minutes
Building Blocks of AI Phishing Detection Systems 5 minutes
Hands-On: Building a Complete Phishing Detector with Python and AI 5 minutes
Understanding Network Logs and Security Anomalies 4 minutes
Machine Learning for Anomaly Detection: Algorithms and Approaches 5 minutes
Hands-On: Building a Network Anomaly Detection System 6 minutes
Indicators of Compromise: The Language of Threat Intelligence 4 minutes
Malware Classification and Threat Intelligence APIs 5 minutes
Hands-On: Automated IOC Extraction and Threat Intelligence Generation 6 minutes

1 lectureTotal 5 minutes

MITRE ATT&CK Framework: Understanding Adversary Tactics and Techniques 5 minutes

1 devoirTotal 20 minutes

AI-Powered Threat Detection and Analysis20 minutes

1 évaluation par les pairsTotal 20 minutes

Hands-On-Learning: Multi-Source Threat Detection System20 minutes

3 sujets de discussionTotal 30 minutes

Evaluating Phishing Risk in Your Own Organization10 minutes
Applying Anomaly Detection to Your Network Environment10 minutes
Transforming Threat Intelligence from Manual to Automated10 minutes

This module teaches students to build end-to-end automated incident response systems that handle the complete lifecycle from alert triage through containment and documentation. Students create sophisticated workflows that enrich alerts with threat intelligence, perform automated investigations across multiple data sources, execute containment actions via APIs, and integrate with ticketing systems. The focus is on reducing mean time to respond (MTTR) while maintaining high-quality incident handling.

Inclus

10 vidéos1 lecture1 devoir1 évaluation par les pairs1 sujet de discussion

10 vidéosTotal 41 minutes

Module Introduction 1 minute
The Alert Triage Challenge: From Noise to Signal 4 minutes
Building Intelligent Triage Systems: Enrichment and Scoring 4 minutes
Hands-On: Building an AI-Powered Alert Triage System 5 minutes
The Art of Security Investigation: From Alert to Attack Story 4 minutes
Log Correlation and Timeline Reconstruction Techniques 4 minutes
Hands-On: Building an Automated Investigation Engine 5 minutes
Response Automation and SOAR: Speed vs. Safety 5 minutes
API-Driven Response: Integrating Security Tools 4 minutes
Hands-On: Building an Automated Incident Response Playbook 4 minutes

1 lectureTotal 5 minutes

Computer Security Incident Handling Guide 5 minutes

1 devoirTotal 20 minutes

Automating Incident Response Workflows20 minutes

1 évaluation par les pairsTotal 20 minutes

Hands-On-Learning: Automated Incident Response System20 minutes

1 sujet de discussionTotal 10 minutes

Rethinking How Your Team Prioritizes Alerts10 minutes

This advanced module prepares students to deploy AI security automation in production environments. Students learn to build intelligent security assistants using retrieval-augmented generation (RAG), design event-driven automation architectures, implement continuous monitoring systems, and defend against adversarial AI attacks. The module culminates in understanding compliance considerations, model evaluation, and the future trajectory of AI in security operations.

Inclus

11 vidéos1 lecture1 devoir2 évaluations par les pairs3 sujets de discussion

11 vidéosTotal 52 minutes

Module Introduction 2 minutes
From Static SOPs to Dynamic AI Playbooks 4 minutes
Understanding RAG: How AI Accesses Your Security Knowledge 4 minutes
Hands-On: Building a Security Analyst AI Assistant with RAG 4 minutes
Event-Driven Security Architecture: From Reactive to Proactive 4 minutes
Workflow Orchestration and Human-in-the-Loop Decision Making 5 minutes
Hands-On: Building a Production-Ready Phishing Response Pipeline 5 minutes
The Adversarial AI Threat Landscape: How Attackers Weaponize AI 5 minutes
Defensive AI: Hardening Models and Detecting AI-Generated Threats 6 minutes
Hands-On: Adversarial Testing and the Future of AI Security 7 minutes
Course Wrap-Up6 minutes

1 lectureTotal 5 minutes

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks 5 minutes

1 devoirTotal 20 minutes

Production-Ready AI Security Automation20 minutes

2 évaluations par les pairsTotal 80 minutes

Hands-On-Learning: AI Security Operations Center Platform20 minutes
Project: AI-Powered SOC Platform60 minutes

3 sujets de discussionTotal 30 minutes

Assessing the Quality of Your Organization's Security Documentation10 minutes
Moving from Manual Triggers to Continuous Security Automation10 minutes
Preparing Your Defenses for AI-Powered Attacks10 minutes

Instructeurs

Aseem Singhal

15 Cours11 248 apprenants

Offert par

STARWEAVER

En savoir plus sur Security

Packt
ChatGPT for SOC Analyst - Master Cyber Security with AI
Cours
Board Infinity
AI for Cybersecurity: Threat Detection & Incident Response
Cours
STARWEAVER
AI Agents for Cybersecurity: Threat Detection & SOC Ops
Cours
Packt
Artificial Intelligence for Cybersecurity
Cours

Pour quelles raisons les étudiants sur Coursera nous choisissent-ils pour leur carrière ?

Felipe M.

Étudiant(e) depuis 2018

’Pouvoir suivre des cours à mon rythme à été une expérience extraordinaire. Je peux apprendre chaque fois que mon emploi du temps me le permet et en fonction de mon humeur.’

Jennifer J.

Étudiant(e) depuis 2020

’J'ai directement appliqué les concepts et les compétences que j'ai appris de mes cours à un nouveau projet passionnant au travail.’

Larry W.

Étudiant(e) depuis 2021

’Lorsque j'ai besoin de cours sur des sujets que mon université ne propose pas, Coursera est l'un des meilleurs endroits où se rendre.’

Chaitanya A.

’Apprendre, ce n'est pas seulement s'améliorer dans son travail : c'est bien plus que cela. Coursera me permet d'apprendre sans limites.’

Qu’est-ce qui vous amène sur Coursera aujourd’hui ?

Commencer ma carrière

Changer de voie

M’améliorer dans mon rôle actuel

Découvrez des sujets en dehors du travail

Acquérez des compétences durables, maintenant à 239 $
Économisez dès maintenant
Offrez de nouvelles compétences à votre équipe
Économisez 40 % dès maintenant

Foire Aux Questions

AI in cybersecurity automates the work that used to eat an analyst's day including spotting threats, triaging alerts, investigating incidents, and responding to them. In practice, machine learning flags network anomalies and phishing, while large language models like ChatGPT and Claude help enrich threat intelligence and speed up investigations. This course teaches you to build exactly these systems: automated threat detection, alert triage, and incident response using Python and AI.

No. AI changes the work rather than replacing the professional. It handles the repetitive, high-volume tasks (sorting alerts, pulling context, drafting reports) so analysts can focus on judgment, strategy, and complex threats. The professionals who thrive are the ones who know how to use AI, which is what this course builds: practical AI for cybersecurity skills you can apply in a real SOC.

This course is built for practising security professionals including SOC analysts, security engineers, and cybersecurity practitioners who want to automate their day-to-day work with AI. If you already understand core security concepts and have basic Python, this AI for cybersecurity course shows you how to apply machine learning and large language models to real detection, investigation, and response tasks.

It's hands-on throughout. You work with real security datasets and coding exercises, writing Python to automate threat detection, alert triage, incident response, and SOC workflows. Rather than explaining AI in cybersecurity in the abstract, the course has you build production-ready automation - detection systems, investigation tools, and event-driven response pipelines.

The demand for professionals who can combine security expertise with automation is growing fast. This course builds job-relevant skills including Python security scripting, SOAR workflows, incident response automation, and AI-powered threat analysis that map directly to modern SOC roles. Learning to automate cybersecurity operations with AI positions you for the roles security teams are actively hiring for.

To access course materials, assignments, and earn a Certificate, you'll need to purchase the Certificate experience when you enroll in a course. Eligible learners may also have the option to start with a Free Trial. Some courses may also offer a Full Course, No Certificate option. This lets you access course materials, submit required assessments, and receive a final grade, but you won't be able to earn or purchase a Certificate.