This Data Analysis with Python course provides a complete introduction to working with data using Python programming. It is designed for beginners who want to learn how to analyze, clean, and visualize data using modern data science tools.

The course begins with an introduction to data analysis concepts and explains why Python has become one of the most powerful tools for data analysis compared to traditional tools like Excel. It then covers the full data analysis workflow from reading data to generating insights.

You will learn how to import data from different sources such as CSV files, Excel files, and SQL databases. The course then introduces NumPy, which is used for numerical computations and efficient data processing.

Next, it focuses on Pandas, one of the most important libraries for working with structured data using DataFrames. You will also learn how to clean data by handling missing values, errors, and outliers.

In addition, the course covers data visualization using Matplotlib and Seaborn, helping you create charts and graphs to better understand your data.

By the end of this course, learners will be able to perform full data analysis projects using Python, from data collection to cleaning, analysis, and visualization.