This course is a curated collection of both Supervised and Unsupervised Machine Learning content.
IMPORTANT: This course reuses material from two previous courses available on my Udemy profile. If you have already taken them, note that this is a combined and reorganized version, designed to offer a unified learning experience without switching between separate courses.
Project 1: A/B Testing on Web Traffic
In this project, you’ll work with real web traffic data from a company to evaluate the impact of two page versions on user conversion rates. You will learn to:
- Clean and explore traffic data using Pandas.
- Apply statistical tests like the t-test and hypothesis testing to compare conversion rates.
- Visualize results and make data-driven decisions.
- Create a report with actionable insights to optimize website performance.
Project 2: Bank Data Exploration for Machine Learning
In this practical case, you’ll analyze a financial dataset containing bank client information to detect patterns and prepare data for future Machine Learning models. You’ll focus on:
- Data cleaning and transformation using Pandas and NumPy.
- Visual exploration with Seaborn to identify trends and correlations.
- Using descriptive statistics to understand client behavior.
- Preparing the dataset for predictive modeling.
- The course is intended for anyone who is interested in data science.
