AI-Driven SOC Operations with Claude and Splunk

Name: AI-Driven SOC Operations with Claude and Splunk
Rating: 4.7 (17 reviews)

Master alert triage, threat enrichment & UEBA with real case studies and a hands-on Claude + Splunk lab

Created byRaghu The Security Expert

Last updated 7/2026

English

English [Auto],

What you'll learn

Triage and prioritize security alerts using AI to reduce analyst fatigue and response time.
Enrich alerts with threat intelligence automatically using AI-powered context and IOC analysis.
Detect anomalies and insider threats using AI-driven UEBA techniques in a SOC environment.
Analyze real-world SOC case studies across alert triage, threat intel, and UEBA use cases.
Integrate Claude Desktop with a local Splunk instance to build an AI-augmented SOC pipeline.
Apply AI workflows hands-on to investigate, enrich, and respond to simulated security incidents.

Course content

6 sections • 25 lectures • 2h 54m total length

Introduction and Agenda6:15
Discover the fundamentals of AI and machine learning for security operations, and explore core SOC use cases - alert triage, UEBA, and threat intelligence - through hands-on Splunk integration.

Agenda Items of AI and ML Basics section2:14
Explore the basics of generative AI, its market examples, and how artificial intelligence powers these models, while examining machine learning types and key models like GPT, DALY, CODEC.
Generative AI - Understanding and some use cases3:55
Explore the basics of generative artificial intelligence and how it creates images, text, music, and code, with examples like chatGPT, Copilot, and CodeT5.
AI, ML Basics and Machine Learning Types7:02
Explore the foundations of artificial intelligence and machine learning, including supervised, unsupervised, and reinforcement learning. Learn how models train with labeled data and algorithms to identify patterns and outcomes.
Understanding AI Models in simple terms4:50
Explore what a model is through a cake analogy: data collection, algorithm, training, refinements, and deployment-ready models, including supervised and unsupervised learning.
What are Tokens and Embeddings in AI Models?6:19
Learn how prompts are broken into tokens and converted to embeddings, and how tokenization types: word-level, sub-word, and character-level, feed neural networks to generate outputs.
Let's understand the ML type, Algorithm and Model in ChatGPT3:32
Explore how ChatGPT works: from its training data and learning methods—unsupervised, supervised, and reinforcement learning from human feedback—to the generative pre-trained transformer model and its evolution across versions.
Let's understand the ML type, Algorithm and Model in Github Copilot3:24
Explore the transformer-based CodeX model powering GitHub Copilot, trained with unsupervised learning and supervised fine-tuning on a large public code dataset to generate code snippets.

What is SOC without AI?12:53
Define the security operations center and its 24/7 threat monitoring. Outline tiered roles, SIEM tools like Splunk, and tasks like alert triage, threat hunting, insider risk, and incident response.
SOC Challenges and why AI is needed to solve these Challenges?6:34
Explore how AI drives SOC operations by reducing alert fatigue and false positives, improving context for analysts, shortening time to respond, and enabling scalable security across cloud and hybrid environments.
AI-Driven SOC Benefits12:00
Leverage AI-driven SOC operations to automate triage, reduce noise, and correlate threats with advanced analytics and threat hunting, while recognizing the need for human supervision to avoid false conclusions.

First SOC challenge that AI can help to solve8:56
Discover how ai enhances alert triage and prioritization in the security operations center, reducing alert fatigue, false positives, and mean time to repair by providing context-rich risk-based prioritization.
Second SOC challenge that AI can help to solve - Part 113:25
Discover how AI-driven behavioral and anomaly-based threat detection replaces signature-based methods with user, device, and workload analytics to identify threats. UEBA correlates weak signals to reveal insider and zero-day threats.
Second SOC challenge that AI can help to solve - Part 29:17
Explore how behavioral and anomaly-based threat detection, powered by AI, outperforms signature-based methods, illustrated by the JPMorgan Chase 2014 credential-leak incident and UEBA tools like Splunk and Microsoft Sentinel.
Third SOC challenge that AI can help to solve9:12
Convert isolated alerts into actionable insights by clustering indicators of compromise, adding context, and mapping external intel to internal telemetry, reducing false positives.

Hands-On: AI-Driven SOC Case Study Understanding6:05
Explore an AI-powered soc case study that integrates cloud desktop with Splunk via the MCP server and model context protocol, enabling natural language queries and prioritized alerts.
Prerequisites: Install Git on your Local system4:19
Install git bash on your local system to clone repos, commit changes, and push updates. Download from git-scm.com and use vim, ssh, openssl, and merge, rebase, or fast-forward pull options.
Prerequisites: Install Docker Desktop on your Local system2:22
Install Docker Desktop on Windows, complete download and install, and sign in with Docker Hub. Troubleshoot startup by enabling Virtual Machine Platform and upgrading to WSL 2 if needed.
Prerequisites: Install Python on your Local system1:23
Install python 3.12.4 on Windows, customize installation with add to path, create a dedicated folder, complete setup, and verify version via command prompt.
Prerequisites: Install Claude Desktop on your Local system2:24
Learn how to download and install Claude Desktop on Windows or Mac, sign in with Google, and get started with Cloud Desktop on your local system.
Hands-On: Integrate Splunk instance with Claude Desktop using MCP - Part 110:02
Set up and run a hands-on ai powered soc demo by cloning the ai-driven-soc-demo repo, launching a splunk docker container, and preparing an mcp server to connect cloud to splunk.
Hands-On: Integrate Splunk instance with Claude Desktop using MCP - Part 212:56
Start a Splunk enterprise dashboard, generate and import realistic security events, and prepare data for Claude AI analysis in a hands-on MCP SOC workflow.
Hands-On: Integrate Splunk instance with Claude Desktop using MCP - Part 315:08
Set up a python virtual environment and install required packages from requirements.txt for the Splunk MCP server. Test connectivity to localhost:8089 and configure cloud desktop to run the MCP integration.
Hands-On: Integrate Splunk instance with Claude Desktop using MCP - Part 46:27
Integrate splunk MCP server with cloud desktop to fetch and prioritize high severity alerts within 24 hours, then investigate a compromised IP for brute force activity using AI-assisted SOC workflows.

Requirements

Basic understanding of cybersecurity concepts (e.g., threats, alerts, logs) is helpful but not required.
Familiarity with SIEM tools like Splunk is a plus — beginners will be guided through setup step by step.
A laptop or desktop with internet access capable of running Splunk and Claude Desktop locally.
Curiosity about how AI is transforming cybersecurity operations is all you truly need to get started.

Description

Disclosure: This course contains the use of artificial intelligence.

Security operations teams are overwhelmed — alert volumes are skyrocketing, threats are evolving, and analysts are burning out. AI is the solution. This course gives you the practical skills to bring AI into your SOC, starting today.

What You Will Learn

AI-Powered Alert Triage — Automatically score, rank, and prioritize alerts so analysts focus only on what truly matters
Threat Intelligence Enrichment — Turn raw indicators into actionable intelligence instantly using AI-driven context and external threat feeds
UEBA & Anomaly Detection — Detect insider threats and behavioral anomalies that traditional rule-based systems consistently miss

What Makes This Course Different

Every module is backed by a real-world case study drawn from actual security incidents
Hands-on lab integrating Claude Desktop with a local Splunk instance — step by step, on your own machine
Build a working AI-augmented SOC workflow you can demo, expand, or deploy
Structured for clarity — no fluff, no filler, just practical knowledge you can apply immediately
Learn by doing — not just watching

Who Should Enroll

SOC analysts battling alert fatigue and looking to work smarter
Security engineers exploring AI-powered detection and response tooling
Cybersecurity students and career switchers who want hands-on, job-ready skills
IT professionals curious about how AI is reshaping modern security operations

AI is not replacing SOC analysts — it is making them dramatically more effective. This course shows you exactly how to be on the right side of that shift.

Who this course is for:

SOC analysts, security engineers, and IT professionals looking to apply AI to modernize their security operations.
Aspiring and practicing SOC analysts who want hands-on experience using AI for threat detection and response.
Cybersecurity professionals and students eager to integrate AI tools into real-world SOC workflows.

AI-Driven SOC Operations with Claude and Splunk

What you'll learn

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Course content

Introduction1 lecture • 6min

AI and ML Basics7 lectures • 31min

SOC Basics3 lectures • 31min

SOC challenges that AI can help to solve - Core AI use cases in SOC4 lectures • 41min

Case Study - Integrate Splunk instance with Claude Desktop using MCP server9 lectures • 1hr 1min

Next Steps1 lecture • 3min

Requirements

Description

Who this course is for: