Overview

Google, IBM & Meta Certificates – 40% Off

One Coursera Plus subscription covers most Professional Certificates on Coursera.

By the end of this course, you’ll be using Pandas to prepare, explore, transform, and analyze real-world tabular data in Python. You will master working with Series and DataFrames, loading external data, filtering and summarizing datasets, creating visualizations, and reshaping data for deep analysis. You will build the exact practical skills required in everyday data analysis workflows: identifying data quality issues, merging datasets, reshaping data formats, and extracting meaningful insights from raw information. What sets this course apart is that you learn by doing. Instead of just watching videos, you'll solve interactive coding challenges right inside PyCharm, fully integrated with Coursera. You'll apply each new concept the moment you learn it, locking in your skills through hands-on practice. Finally, you’ll tie everything together with a capstone project: "Which TED Talks to watch." Using Pandas, you’ll analyze a real dataset and build a functional recommendation workflow from scratch. You’ll walk away with a strong foundation in Pandas and the confidence to tackle real datasets in your own projects, studies, or career.

Syllabus

Getting Started with Pandas
- In this module, you'll get familiar with the course setup and take your first steps with Pandas. You'll learn how to navigate the course in PyCharm, why Pandas is essential for data analysis, and how to import it into your Python project. From here, you’ll dive into Series, one of the library's core data structures. By the end of this module, you'll have a solid grip on the fundamentals and have completed your first interactive coding tasks.
DataFrames and Loading Data
- In this module, you'll master DataFrames, the primary structure for tabular data in Pandas. You'll create and manipulate data, navigate datasets using indexing, and import information from external sources. You'll also explore how to identify common data quality issues in real-world workflows. By the end of this module, you'll be fully equipped to prepare datasets for analysis using core Pandas tools.
Data Exploration
- In this module, you'll learn how to investigate and understand datasets through exploratory analysis. You'll summarize data, apply filtering techniques, sort records, and create visualizations to reveal hidden patterns. By the end of this module, you'll have the skills to explore datasets efficiently and surface the exact answers you need.
Data Manipulation
- In this module, you'll master advanced techniques for modifying and restructuring data. You'll transform columns, merge datasets, handle MultiIndex structures, and format data for different types of analysis. By the end of this module, you'll be able to organize and manipulate complex datasets with confidence.
Create Your Own Project
- In this final project, you'll apply your new Pandas skills to a real-world dataset of TED Talks. You'll download and prepare the data, analyze its structure, and build a functional recommendation workflow. By the end, you'll have hands-on experience using Pandas to solve a practical data analysis problem and to showcase your findings.