RANJITH KUMAR KAMLIKAR

Motivated Computer Science graduate with strong proficiency in Python programming and a solid understanding of software development principles. Seeking an entry-level position where I can leverage my coding skills and contribute to innovative software solutions.

• Building Static Website & Building Responsive Website course from NxtWave using HTML5, CSS, Bootstrap, Flexbox
• SQL (DBMS & RDBMS) in SQLite course from NxtWave
• Data Science with Python from Nuage Compusys Technologies Pvt Ltd (NUCOT)

Academic project:

1) Library Management System

• Developed a comprehensive library management system to streamline book lending, returns, and inventory management. I developed a web application using Visual Basic Studio and .NET Framework. Connected the application to a SQL Server database to manage library operations, including book lending and inventory management.
• .NET Framework, Visual Basic Studio, SQL Server technologies used to develop application.
• Designed and implemented a user-friendly application to manage library operations, including cataloging, member registration, and transaction tracking.

Data Science hands on projects:

1) Spam Checker using Python KNN

• Developed a spam checker using the K-Nearest Neighbors (KNN) algorithm to classify emails as spam or ham.
• Used Python libraries such as Pandas, NumPy, and Scikit-learn to build the model.
• Cleaned and preprocessed the data by removing common punctuation and symbols, lowercasing all letters, and removing stop words.
• Split the data into training and testing sets and trained the KNN model on the training set.
• Evaluated the model on the testing set and achieved an accuracy of 95%. Deployed the model to production and used it to filter spam emails.

2) Customer churn prediction using Python (KNN, Naive Bayes, Decision Tree & ANN) Classifications.

• I initiated the project with meticulous data cleaning procedures to ensure the integrity and reliability of customer churn datasets. Skilled in identifying and addressing various data quality issues to prepare data for advanced analytics and predictive modeling.

3)Web Scraping Project: Amazon Laptop Information

• Developed a web scraping tool using Python's BeautifulSoup and Requests libraries to extract laptop details from Amazon.
• Captured product information including image, title, rating, price, and ad/organic status.
• Implemented error handling to ensure robust data extraction and verified the functionality by checking HTTP response codes.
• Parsed the HTML content to fetch relevant attributes, enhancing data collection for further analysis or presentation.
• Using decision tree algorithms to analyze customer data, identify key churn drivers, and predict customer churn probabilities, enabling proactive retention strategies.
• Utilized advanced data visualization techniques to communicate data quality insights. I generated robust predictive insights into customer churn dynamics.

I hereby affirm that the information in this document is accurate and true to best of my knowledge.