Data Processing and Exploration with NumPy & Pandas

Overview

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Dive into the world of data manipulation and numerical analysis with NumPy and Pandas, two of the most essential tools in the data science toolkit. Learn how to manipulate, process, and analyze large datasets with ease and efficiency. Whether you're working with numerical data, handling missing values, or exploring data through visualization, this course will equip you with the skills you need to tackle a wide range of data tasks. The course is divided into two major sections—NumPy and Pandas—each offering focused lessons on core concepts. You’ll start by learning the fundamentals of NumPy for numerical computing, including array creation, reshaping, and advanced operations such as broadcasting and universal functions. Then, you will delve into Pandas, exploring Series and DataFrame objects, handling missing data, and mastering powerful functions like groupby, merge, and pivot tables. This course is perfect for anyone looking to enhance their data processing and analysis skills. Whether you're an aspiring data scientist, business analyst, or just someone who works with data regularly, this course will provide you with the tools to work efficiently and effectively. No prior programming experience is required, but basic familiarity with Python will be helpful. The course is suitable for beginners to intermediate learners, with a focus on practical applications and hands-on exercises. By the end of the course, you will be able to work with large datasets, perform complex data manipulations, use NumPy for numerical operations, and confidently analyze data with Pandas. You’ll also gain expertise in data cleaning, reshaping, merging, and creating advanced data visualizations to inform data-driven decisions.

Syllabus

NumPy for Numerical Data Processing

In this module, we will explore NumPy, a powerful library for numerical data processing in Python. You will learn how to create and manipulate arrays, use advanced functions like slicing, masking, and broadcasting, and apply mathematical operations using universal functions (ufuncs). This module also includes practical exercises, such as playing with images and implementing KNN classifiers, to help you solidify your understanding.

Pandas for Data Manipulation and Understanding

In this module, we will dive into Pandas, a powerful library for data manipulation and analysis. You’ll learn how to work with Series and DataFrames, handle missing data, and apply advanced data operations like group by, merging, and rolling windows. The module also includes real-world examples, such as working with COVID-19 data, to reinforce your learning through hands-on practice.