Building practical security projects, automation, and technical problem-solving skills.
I like understanding how systems work, finding the signal inside the noise, and building tools that make the next investigation easier.
My current direction is cybersecurity, with a strong foundation in Python, SQL, systems, troubleshooting, and analytical thinking.
Understand the system → collect the evidence → find the signal → investigate → respond → improve the process.
This profile follows a practical progression from technical problem solving → systems → cybersecurity → SOC operations.
The emphasis is on fundamentals first, then hands-on security work:
- 💻 Computer and operating-system fundamentals
- 🌐 Networking and common protocols
- 🐧 Linux fundamentals
- 🪟 Windows fundamentals
- 🔐 Cybersecurity fundamentals
- 🧭 MITRE ATT&CK and attacker behavior
- 🛡️ SOC workflows and alert triage
- 📊 SIEM and log analysis
- 🚨 Threat detection and investigation
- 🧯 Incident response fundamentals
- 🕵️ Threat intelligence
- 🐍 Python for security automation
Current lab status: deeper SOC labs and end-to-end investigation exercises are pending / in progress. They are intentionally shown as learning work rather than completed professional experience.
Cybersecurity is the current specialization. Python, SQL, analytics, and engineering remain useful foundations for security work.
Security-focused Python project for identifying risky coding patterns and producing structured findings.
Focus: Static analysis • Security rules • Python • Automation • Security reporting
Repository: https://github.com/Jaspinder-12/Ai-Code-Risk-Analyzer
Modular Python project focused on automation, backend experimentation, and structured engineering practice.
Focus: Python • Automation • Modular architecture • Backend logic
Repository: https://github.com/Jaspinder-12/MGR-S-Complete
NLP-based semantic similarity project that compares text beyond simple exact keyword matching.
Focus: NLP • Similarity analysis • Python • Scikit-learn
Repository: https://github.com/Jaspinder-12/Plagiarism-Detector
The earlier analytics and ML work stays here as part of the engineering foundation behind the current security path.
Power BI dashboard work focused on sales, revenue, customer, and product performance.
Focus: Power BI • Excel • Data Modeling • Business Analytics
Machine-learning workflow for identifying customers likely to leave and exploring the factors behind churn.
Focus: Python • Pandas • Scikit-learn • Feature Engineering
Classification project using chemical properties to explore wine-quality prediction.
Focus: Python • Pandas • Scikit-learn • Model Evaluation
Regression project exploring the factors that influence property prices.
Focus: Python • Regression • Feature Analysis • Visualization
These are part of the learning portfolio. Deeper SOC labs are still being built, so the status below reflects the actual stage rather than pretending a course badge magically grants field experience.
| Area | Status | Current Focus |
|---|---|---|
| Microsoft Sentinel | 🔄 Learning | SIEM concepts, monitoring, investigation |
| Splunk | 🔄 Learning | Dashboards, logs, security analysis |
| Microsoft Defender for Cloud | 🔄 Learning | Cloud security concepts |
| MITRE ATT&CK | 🔄 Learning | Technique mapping and attacker behavior |
| PortSwigger Web Security Academy | 🔄 Learning | Web-security fundamentals and testing |
| SOC Investigation Labs | 🕐 Pending | Deeper hands-on investigation practice |
| Incident Response Case Studies | 🕐 Pending | Investigation → containment → recovery |
| Status | Stage | Focus |
|---|---|---|
| ✅ | Phase 1 | Python Reconstruction for Cybersecurity |
| ✅ | Foundation | SQL + Technical Problem Solving |
| 🔄 | Phase 2 | Computer Fundamentals + Networking |
| 🔄 | Phase 3 | Linux + Windows Fundamentals |
| 🔄 | Phase 4 | Cybersecurity Fundamentals |
| 🔄 | Phase 5 | MITRE ATT&CK |
| 🔄 | Phase 6 | SOC Fundamentals |
| 🔄 | Phase 7 | SIEM + Log Analysis |
| 🔄 | Phase 8 | Threat Detection + Investigation |
| 🔄 | Phase 9 | Incident Response |
| 🔄 | Phase 10 | Threat Intelligence |
| 🕐 | Next Build | Hands-on SOC Labs + Home Lab |
Computer Fundamentals
↓
Networking
↓
Linux + Windows
↓
Cybersecurity Fundamentals
↓
MITRE ATT&CK
↓
SOC Fundamentals
↓
SIEM + Log Analysis
↓
Threat Detection
↓
Incident Response
↓
Threat Intelligence
↓
Python Security Automation
↓
Hands-on Labs + Case Studies
↓
Security Portfolio
| Principle | How I apply it |
|---|---|
| 🔎 Evidence first | Investigate the data before deciding what happened |
| 🧩 Break it down | Reduce complex problems into smaller signals |
| 🛠️ Troubleshoot systematically | Reproduce, isolate, test, document |
| 🐍 Automate repetition | Use Python when manual work can be made safer and faster |
| 🔐 Security-minded design | Think about failure and misuse early |
| 📝 Document the reasoning | Explain the why, not just the commands |
| 🔁 Build and iterate | Turn learning into something usable |
✅ Python foundations
✅ Security-focused Python project
✅ Systems / engineering projects
✅ Data & analytics foundation
🔄 Networking + OS fundamentals
🔄 Cybersecurity fundamentals
🔄 MITRE ATT&CK
🔄 SIEM + log analysis
🔄 Threat detection
🕐 SOC investigation lab
🕐 Incident response case study
🕐 End-to-end home lab
2026
Computer science foundation covering programming, systems, databases, and software engineering concepts.
Technical support and troubleshooting experience shaped the way I approach technical problems: understand the issue → reproduce it → isolate the cause → resolve it → document the result.
Earlier internships and projects built practical experience with Python, SQL, analytics, dashboards, and structured problem solving. Those skills now support the cybersecurity path.
- 🛡️ Mastercard Cybersecurity Virtual Experience
- 🏦 Commonwealth Bank Cybersecurity Virtual Experience
- 🔐 Microsoft Sentinel learning / practice
- ☁️ Microsoft Defender for Cloud learning
- 🌐 PortSwigger Web Security Academy practice
- 📊 Deloitte Data Analytics Job Simulation
- 🗄️ Microsoft SQL Server 2017 — Udemy
- 🤖 EDVANE — Data Formats for Data Engineering & AI
- 📚 Data / Analytics internship learning experiences
- 🎖️ NCC Sergeant
- 🐍 Python and debugging practice
- 🧠 Systems, cybersecurity, AI, and automation
- ⚽ Football enthusiast
- 🔧 Building practical tools and experimenting with technology
- 🖥️ Computer & OS fundamentals
- 🌐 Networking
- 🐧 Linux
- 🪟 Windows
- 🔐 Cybersecurity fundamentals
- 🧭 MITRE ATT&CK
- 🛡️ SOC fundamentals
- 📊 SIEM and log analysis
- 🚨 Threat detection
- 🧯 Incident response
- 🕵️ Threat intelligence
- 🐍 Security automation with Python
- SQL
- Git / GitHub
- Docker fundamentals
- Backend concepts
- Data analysis and visualization
Learn the fundamentals. Investigate the evidence. Build the tool. Document the result.
while learning:
study()
lab()
investigate()
build()
document()
improve()