About This Course

Exploratory Data Analysis (EDA) is a critical course that focuses on techniques for understanding and summarizing data to uncover patterns, relationships, and anomalies. Students will learn to use statistical and visualization tools to explore datasets, identify trends, and prepare data for advanced modeling. The course covers descriptive statistics, correlation analysis, feature selection, and data transformation techniques.

Through hands-on projects, students will gain proficiency in tools like Python, R, Pandas, Matplotlib, and Seaborn, enabling them to create insightful visualizations and derive meaningful insights. Emphasis is placed on the importance of storytelling with data and communicating findings effectively. By the end of the course, students will have the skills to approach real-world datasets, identify key insights, and prepare data for predictive analytics and machine learning. This course is essential for building a strong data analysis and decision-making foundation.