In this module, we will explore the essentials of Python programming. You will gain a strong understanding of Python syntax, variables, and data types while learning to write efficient and readable code. By the end of this section, you will be able to build simple programs using core Python concepts.

In this module, we will introduce the powerful NumPy library, a key tool for performing numerical computations. You’ll learn how to use NumPy arrays and perform operations that lay the foundation for more advanced data analysis.

In this module, we will dive into Pandas, one of the most essential libraries for data manipulation in Python. You will learn how to import, inspect, and clean data using Pandas, preparing you for deeper data analysis tasks.

In this module, we will introduce Matplotlib, the go-to library for creating data visualizations in Python. You’ll start by learning how to create basic plots and gradually progress to enhancing them with customizations to make your data more visually informative.

In this module, we will explore advanced Pandas concepts, including data merging, concatenation, and pivot table creation. You will also learn how to manage large datasets effectively and efficiently handle missing or duplicate data.

In this module, we will take a deep dive into advanced Matplotlib techniques, including customizing charts and creating scatter plots, histograms, and pie charts. These skills will help you present data in a visually appealing and professional manner.

In this module, we will introduce Seaborn, a powerful library that simplifies the creation of visually rich plots. You’ll learn how to use Seaborn for quick and elegant data visualizations, enhancing your ability to communicate insights.

In this module, we will guide you through a comprehensive project where you’ll analyze real-world data. Using Python, Pandas, and Matplotlib, you’ll demonstrate your ability to extract meaningful insights from data while utilizing Git and GitHub for project management.

In this module, we will wrap up the course by showing you how to share your final project on GitHub. This will help you showcase your work to potential employers or collaborators and reflect on the progress you’ve made throughout the course.