🎓 MCA Student at Thapar Institute of Engineering & Technology

I am an MCA student with a strong interest in Data Analytics, Machine Learning, Data Science, and Software Development. I enjoy transforming raw data into actionable insights, solving business problems through analytics, and building machine learning solutions using real-world datasets.

My current focus is building a strong portfolio in Data Analytics and Machine Learning while preparing for internships and full-time opportunities in Data Analytics, Data Science, Machine Learning, and Software Development.

• Python
• SQL
• C++

• Pandas
• NumPy
• Matplotlib
• Seaborn
• Scikit-Learn

• Logistic Regression
• Decision Trees
• Random Forest
• Feature Engineering
• Model Evaluation
• Classification

• Git
• GitHub
• Jupyter Notebook
• VS Code

Skills Applied

• Data Cleaning
• Exploratory Data Analysis (EDA)
• Data Visualization
• Correlation Analysis
• Insight Generation

Skills Applied

• Business Analytics
• Feature Engineering
• KPI Analysis
• Time-Series Analysis
• Customer Analytics
• Product Performance Analysis
• Profitability Analysis
• Business Recommendations

Key Findings

• Identified the highest-performing regions and product categories.
• Analyzed customer and product-level performance.
• Evaluated the impact of discounts on profitability.
• Generated actionable business recommendations.

Skills Applied

• Customer Analytics
• Revenue Analysis
• RFM Analysis
• Customer Segmentation
• Customer Behavior Analysis
• Business Recommendations

Key Findings

• Identified high-value customer segments using RFM Analysis.
• Analyzed customer purchasing behavior and spending patterns.
• Evaluated customer engagement through recency, frequency, and monetary metrics.
• Generated customer retention and loyalty recommendations.

Skills Applied

• Marketing Analytics
• Campaign Performance Analysis
• Customer Response Analysis
• KPI Analysis
• Business Recommendations

Objective

Predict whether a telecom customer is likely to churn based on demographic information, account details, and service usage patterns.

Project Workflow

• Data Cleaning
• Exploratory Data Analysis (EDA)
• Feature Engineering
• Feature Scaling
• Model Training
• Model Evaluation
• Feature Importance Analysis

Models Evaluated

• Logistic Regression
• Decision Tree
• Random Forest

Best Model

🏆 Logistic Regression

• Accuracy: 80.74%
• Precision: 64.67%
• Recall: 60.70%
• F1 Score: 62.62%

Key Insights

• Customers with shorter tenure are more likely to churn.
• Higher monthly charges increase churn risk.
• Long-term contracts improve retention.
• Fiber optic customers exhibit higher churn rates.
• Electronic check users are more likely to churn.

• Data Cleaning
• Exploratory Data Analysis (EDA)
• Data Visualization
• KPI Analysis
• Customer Analytics
• Business Analytics
• Revenue Analysis
• RFM Analysis
• Customer Segmentation
• Time-Series Analysis

• Data Preprocessing
• Feature Engineering
• One-Hot Encoding
• Feature Scaling
• Classification Modeling
• Model Evaluation
• Feature Comparison
• Feature Importance Analysis

• Python Programming
• SQL
• Git & GitHub
• Jupyter Notebook
• VS Code

• Analyzed 550,000+ records across multiple real-world datasets.
• Built end-to-end analytics projects from data cleaning to business recommendations.
• Completed an end-to-end machine learning classification project.
• Applied customer analytics, business analytics, KPI tracking, and machine learning techniques.
• Created professional visualizations and documented findings through GitHub projects.
• Developed structured workflows aligned with real-world business problems.

• Building Machine Learning Project Portfolio
• Learning Advanced SQL
• Strengthening Data Structures & Algorithms
• Exploring Model Optimization Techniques
• Preparing for Internship Opportunities

• HR Analytics
• Supply Chain Analytics
• E-commerce Analytics

• House Price Prediction
• Loan Approval Prediction
• Customer Segmentation
• Credit Risk Prediction
• Sales Forecasting

• Complete 10+ Data Analytics & Machine Learning Projects
• Strengthen SQL and Data Structures & Algorithms
• Build an Industry-Ready Portfolio
• Maintain Consistent GitHub Contributions
• Secure an Internship or Full-Time Role in Data Analytics, Data Science, Machine Learning, or Software Development

📧 Email: harshitpoonia31@gmail.com

• Data Analytics
• Machine Learning
• Data Science
• Business Analytics
• Customer Analytics
• Python Development

"The best way to learn is by building."