Exploratory data analysis, or EDA in python, is a crucial step in the data analysis process that involves studying, exploring, and visualizing information to derive vital insights. To find patterns, trends, and relationships in the data, it makes use of statistical tools and visualizations. This helps to formulate hypotheses and direct additional investigations.

Python provides strong EDA tools with its diverse library ecosystem, which includes Seaborn, Matplotlib, and Pandas. An essential phase in the data science pipeline, this procedure improves data comprehension and provides information for further modeling decisions.

Exploratory Data Analysis(EDA) is the crucial step in the process of various data analysis. It helps data to visualize the patterns, characteristics, and relationships between variables. Python provides various libraries used for EDA such as NumPy, Pandas, Matplotlib, Seaborn, and Plotly. You will acquire wide practical exposure to expand your business / company by enhancing your existing python application with this well curated comprehensive fundamental course.

This course is open to both engineering and arts college students. Upon successful completion they will certainly get a good job with nice package. And is suitable for working professionals as well who wish to have their domain change. This course is for everyone being fresh graduates, pre final year trying for placements (both computer and non computer engineering / arts), UG, PG to be graduates, working professionals seeking for domain change/ new offer with nice package and for professors from any department and research scholars, and to all UG, PG students who wish to do final semester project using Python. 15+ projects will be taught and new challenges will be given based on participants wish to make them try on their own.