AI Powered Security Automation with Python
This course in Toronto teaches you to automate real security operations work with Python, large language models (LLMs), and the Model Context Protocol. You will build agentic tools that take genuine load off an analyst.
The theme throughout is restraint. An automation that acts on bad output is worse than no automation, so you learn to build tools that fail safely, log everything, and keep a human in the loop for any consequential decision.
- Duration
- 8 weeks
- Format
- Live online, instructor-led
- Prerequisites
- None required
- Class size
- Capped at 14 learners
What you will be able to do
- Automate repetitive security operations tasks in Python
- Integrate an LLM into a tool without trusting it blindly
- Use the Model Context Protocol to connect tools to a model
- Design automations that fail safely and log their reasoning
- Decide which actions must always require human approval
- Measure whether an automation actually saved analyst time
Course outline
6 modules
- Project structure, packaging, and testing
- Working with security APIs and data
- Error handling that does not hide failure
- Scheduling and running tools reliably
What you need before you start
- You can program in Python at an intermediate level
- You work in or understand security operations
- You have used an LLM tool, though not necessarily its API
- You are willing to test that your automation fails safely
Who this course is for
- SOC analysts who want to automate the repetitive parts of their work
- Security engineers building internal tooling
- Detection and response teams adding AI assistance
- Practitioners moving toward AI-assisted operations
Questions about this course
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