Aspiring Data Analyst and Machine Learning Practitioner with a Statistics background, a Data Analyst internship in marketing, and hands-on projects in data analysis, machine learning, deep learning, SQL, and business analytics.

My work focuses on turning datasets into clear analysis, practical models, visual reporting, and well‑structured GitHub repositories, backed by Topmentor certifications in data science, analytics, business analytics, and specialist tracks in ML, Python, SQL, BI tools, and Generative AI.

I help businesses and professionals turn raw data into clear insights, visualizations, and interactive dashboards.

• Data cleaning and preprocessing
• Exploratory data analysis (EDA)
• Charts and visual reporting in Python
• Interactive Power BI or Excel dashboards
• Business insights from any structured dataset

🔗 Data Analysis in Python → My Gig 1 Link 🔗 Power BI / Excel Dashboard → My Gig 2 Link
🔗 Machine Learning Model → My Gig 3 Link

• Data Analysis and Exploratory Data Analysis
• Machine Learning and Model Comparison
• Deep Learning and Neural Networks
• Python, SQL, Excel, Tableau, Power BI
• Data Cleaning, Visualization, and Reporting
• GitHub Project Presentation and Portfolio Building

A curated set of projects from my learning journey across Machine Learning, Deep Learning, SQL, and Data Analytics.

• 🧠 MNIST ANN Digit Classification — Deep Learning TensorFlow Keras

  • Focus: Handwritten Digit Classification Using Artificial Neural Network.
  • Growth: This project reflects my growth into deep learning, preprocessing, evaluation, and stronger repository presentation.
  • Link: View Project

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• 📊 K-Means Clustering Algorithm — Unsupervised Learning Clustering

  • Focus: Understanding clustering behavior, data grouping, and unsupervised learning patterns.
  • Growth: It highlights clustering logic, visual interpretation, and ML intuition beyond labeled prediction tasks.
  • Link: View Project

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• 🏦 Bank Loan Approval Prediction — Machine Learning Classification AUC

  • Focus: Comparing classification models - Logistic Regression, Decision Tree, and Random Forest with AUC-driven evaluation for approval prediction.
  • Growth: This project shows model comparison, evaluation thinking, and recruiter-friendly storytelling.
  • Link: View Project

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• 🗂️ SQL Normalization Process — SQL Database Design

  • Focus: Demonstrating database normalization from raw structure to 1NF, 2NF, and 3NF.
  • Growth: Shows structured data thinking and database fundamentals beyond notebook-based ML work.
  • Link: View Project

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• 🛒 Sales Data Analysis — Python Pandas Visualization

  • Focus: Exploring retail trends and business insights using Python-based data analysis.
  • Growth: It reflects my development in data cleaning, exploratory analysis, visual storytelling, and turning raw data into clearer business understanding.
  • Link: View Project

I am currently building a Product Recommendation System focused on customer-product interaction patterns, ranking logic, and practical end-to-end project development.

• Moving from mini-projects toward stronger portfolio-grade systems
• Strengthening ML, DL, analytics, and SQL through practical work
• Improving repository storytelling and project presentation
• Preparing more advanced work for upcoming uploads

• Data Analyst Intern – Access Million, Pune
  • Aug 2025 – Feb 2026 | Marketing Department
  • Worked with marketing-related data to support reporting, analysis, and campaign performance tracking.
  • Assisted in organizing datasets, identifying trends, and preparing structured summaries for decision-making.
  • Supported reporting workflows through data cleaning, performance monitoring, and insight-focused analysis.

• Master’s in Data Science – Topmentor (Feb 2026)
• Master’s in Data Analytics – Topmentor (Feb 2026)
• Master’s in Business Analytics – Topmentor (Feb 2026)
• Machine Learning Specialist – Topmentor (Feb 2026)
• Python Specialist – Topmentor (Feb 2026)
• SQL Specialist – Topmentor (Feb 2026)
• Tableau Specialist & Power BI Specialist – Topmentor (Feb 2026)

Additional Topmentor certified areas: R Programming, Advanced Excel, Generative AI – ChatGPT Specialist, and Prompt Engineering (completed Feb 2026).

• Applying my Statistics foundation to analyze data patterns and support model understanding
• Building Machine Learning projects with a focus on classification, clustering, and model comparison
• Expanding into Deep Learning / Neural Networks through Perceptron, MLP, and ANN-based projects
• Strengthening my portfolio through project-based learning and more advanced end-to-end problem solving.
• Improving project quality with cleaner notebooks, better visual storytelling, and stronger GitHub presentation
• Progressing toward real-world and GenAI-inspired projects while preparing for Data Analyst, Data Scientist, and Machine Learning Engineer opportunities

Learning deeply. Building consistently. Turning data into insight, models, and meaningful progress.