My Roadmap: From Cybersecurity to Applied AI
I’ve spent most of my career in cybersecurity.
In 2024, I decided to pivot — not away from cyber, but toward AI-powered security.
Here’s my roadmap for the transition.
🎯 Step 1: Define a Use Case
I didn’t start with models — I started with a problem:
“How can I make logs easier to understand and analyze?”
That became my first AI-for-cyber project.
📚 Step 2: Learn the Basics of AI/ML
I focused on:
- Python for data and APIs
- Numpy, Pandas
- Scikit-learn for traditional models
- HuggingFace + OpenAI for LLMs
- LangChain for chaining prompts
🔬 Step 3: Build Something Small, Fast
→ Log Analyzer LLM
This was my MVP to apply what I learned.
📈 Step 4: Go Deeper
I’m now:
- Learning clustering + classification
- Experimenting with fine-tuning
- Studying academic papers
- Rebuilding my GitHub profile with applied projects
🧠 Step 5: Share, Reflect, and Publish
This blog is part of that effort.
I’m also:
- Writing a research paper
- Applying for academic/industry roles
- Building a public portfolio of AI + cybersecurity tools
Lessons So Far
- AI is not a destination — it’s a toolkit
- Focus on usefulness, not hype
- You don’t need a PhD to start
🔍 Curious about my work?
Check out my projects or connect on LinkedIn.