Building practical AI systems, analytics dashboards, and secure software that solve real business problems.

• 🎓 Final-year B.Tech Computer Science student
• 💼 Data Science Intern @ Hoping Minds
• 💼 Data Science & Analytics Intern @ Future Interns
• 🏅 Deloitte Data Analytics Job Simulation
• 🏅 Mastercard Cybersecurity Virtual Experience
• 🏅 EDVANE Data Formats for Data Engineering & AI
• 🗄 Microsoft SQL Server 2017 (Udemy)
• 🌱 Learning FastAPI, Docker, Data Engineering, MLOps, and LLM applications
• 📍 Punjab, India
• 🌍 Open to Remote Opportunities

I do not just build notebooks. I build workflows.

• Clean data and turn it into usable insight
• Build machine learning models with explainable outputs
• Create Power BI dashboards for business reporting
• Write Python automation and backend logic
• Work with SQL and data pipelines
• Communicate results clearly to technical and non-technical people
• Use security-minded thinking while building AI tools

I want my work to feel useful, not decorative.

My goal is to become a Data Scientist who can take raw data, analyze it honestly, build something deployable, and explain the result well enough that a recruiter, manager, or client understands why it matters.

• Machine Learning
• Data Analytics
• Advanced SQL
• Power BI Storytelling
• FastAPI
• Docker
• Data Engineering
• MLOps Fundamentals
• LLM Applications
• Open Source Contributions

• Keep code clean and maintainable
• Prefer reproducible workflows
• Focus on business value first
• Make outputs explainable
• Build with security in mind
• Document enough that another person can run it

AI-powered static code analysis for identifying risky coding patterns and helping developers write safer Python.

Highlights

• Static analysis of code
• Structured JSON reports
• Security-oriented scoring
• AI-assisted detection logic
• Built for developer safety

Tech Python • AI Logic • Security Concepts • Automation

Repository: https://github.com/Jaspinder-12/Vibe-Code-Risk-Analyzer

Machine learning pipeline focused on identifying customers likely to leave and supporting retention strategy.

Highlights

• Data cleaning and preprocessing
• Feature engineering
• Model training and evaluation
• Explainable outputs
• Business recommendations

Tech Python • Pandas • Scikit-learn • SHAP • Visualization

Power BI dashboard for sales, revenue, customer, and product performance analysis.

Highlights

• KPI tracking
• Revenue trends
• Regional insights
• Customer segmentation
• Executive-style reporting

Tech Power BI • Excel • Data Modeling • Analytics

NLP-based semantic similarity system designed to compare text beyond exact keyword matching.

Highlights

• Text preprocessing
• Similarity analysis
• NLP workflow
• Scikit-learn-based logic
• Practical language understanding

Tech Python • NLP • Scikit-learn

Repository: https://github.com/Jaspinder-12/Plagiarism-Detector

Structured Python project focused on automation, backend experimentation, and modular engineering.

Highlights

• Modular architecture
• Automation workflows
• Backend logic
• Structured code organization
• Practical engineering practice

Tech Python • Automation • Backend Logic

Repository: https://github.com/Jaspinder-12/MGR-S-Complete

Machine learning project that predicts wine quality using chemical properties and classification models.

Highlights

• EDA
• Model comparison
• Feature importance
• Predictive classification
• Data preprocessing

Tech Python • Pandas • Scikit-learn

Repository: https://github.com/Jaspinder-12/Wine-Quality-ML

Regression-based ML project exploring the factors that influence property prices.

Highlights

• Regression modeling
• Feature analysis
• Data visualization
• Predictive workflow
• Business use case framing

Tech Python • Regression Models • Visualization

Repository: https://github.com/Jaspinder-12/House-Price-Predictor

These are the repositories I want recruiters to notice first.

• Vibe-Code-Risk-Analyzer
  AI-powered code safety and static analysis.

• Plagiarism-Detector
  NLP similarity detection for text comparison.

• MGR-S-Complete
  Modular Python engineering and automation work.

• Wine-Quality-ML
  Classification project with clean ML workflow.

• House-Price-Predictor
  Regression project with business framing.

• Portfolio
  Personal portfolio and presentation layer.

July 2026 – August 2026

• Data cleaning and exploratory analysis
• Dashboard creation and reporting
• Business insights from datasets
• Practical application of analytics concepts

• Data analysis
• Dashboard work
• ML practice
• Python-based task execution

• EDVANE – Data Formats for Data Engineering and AI
• Deloitte Data Analytics Job Simulation
• Future Interns Data Science & Analytics Internship
• Hoping Minds Data Science Internship
• Mastercard Cybersecurity Virtual Experience
• Microsoft SQL Server 2017 (Udemy)

B.Tech in Computer Science Engineering
Expected Graduation: 2026

• NCC Sergeant
• Mentored peers in Python and debugging
• Football enthusiast
• Interested in AI, analytics, and cybersecurity

[](https://github-readme-stats.vercel.app/api?username=Jaspinder-12&show_icons=true&theme=tokyonight)

[](https://raw.githubusercontent.com/Jaspinder-12/Jaspinder-12/output/github-contribution-grid-snake.svg)

• FastAPI
• Docker
• SQL Optimization
• Feature Engineering
• Machine Learning Deployment
• Data Engineering
• LLM Applications

Great projects do not just train models. They solve problems, communicate clearly, and create measurable impact.

while alive:
    learn()
    build()
    improve()

Building practical AI systems one project at a time 🚀