🚀 Course Recommendation System is a machine learning-based project that suggests personalized courses using Coursera dataset analysis. It leverages content-based and collaborative filtering techniques to provide accurate recommendations. Built with Python, pandas, scikit-learn, and Jupyter Notebook

This repository contains materials and assignments from my Data Science journey on Coursera, including Jupyter Notebooks (.ipynb) with code, explanations, and visualizations, along with HTML/PDF exports summarizing key takeaways. It showcases my work on data manipulation, statistical analysis, machine learning, and data visualization techniques.

Contains Jupyter Notebooks (annotated follow-along guides and activity exemplars) in the Coursera course "Regression Analysis: Simplify Complex Data Relationships," the fifth course in the Google Advanced Data Analytics Professional Certificate Program. This repository is mainly for reference.

🧠 **About** This repository contains my projects and assignments from the **IBM Data Science Professional Certificate** on Coursera. It includes Jupyter Notebooks, Python scripts, and datasets covering topics such as data analysis, data visualization, machine learning, and applied data science. The goal of this repository is to document my le

This project fulfills a peer-graded assignment from Coursera by applying a complete data science workflow—data acquisition, cleaning, transformation, analysis, and output generation. It demonstrates hands-on skills in data preprocessing, visualization, and reproducible reporting using Jupyter Notebook, aligning with academic goals and real-world .

This repository houses Jupyter notebooks created as part of the IBM Data Science course on Coursera. These notebooks cover a range of topics essential for data science, including Python programming, data analysis, machine learning, and more.