Skip to main content
CoursebeginnerFree

Data Analysis with Python

Coursera

⏱ This course requires approximately two hours a week for six weeks.

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement.

Visit resource

More resources on Data Analysis

CourseFree

Data Analysis with Python

Learn data analysis with Python! This free course covers NumPy, Pandas, data cleaning, and visualization. Start your data science journey today!

VideoFree

Data Analysis with Python and Pandas Tutorial

First video in Corey Schafer's pandas series, walking through installing pandas and Jupyter, loading a CSV survey dataset into a DataFrame, and inspecting its shape, columns, and rows. Viewers finish able to set up a working environment for data analysis in Python.

WebsitePaid

DataQuest

Browser-based learning platform teaching data analysis through guided coding exercises and portfolio projects in Python, R, and SQL. Learners work through structured career paths covering data cleaning, visualization, statistics, and databases; a limited free tier precedes a paid subscription.

VideoFree

Excel for Beginners - The Complete Course

Full-length freeCodeCamp course taught by Grand Canyon University professor Shad Sluiter, covering Excel from an empty workbook through formulas, functions, formatting, and charts. Viewers come away able to build and analyze basic spreadsheets for everyday data work.

CourseFree

Data Analysis with R Programming

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data.

VideoFree

Data Visualization Full Course - Learn Data Visualization in 7 Hours

A long-form Python course covering NumPy arrays, Pandas dataframes, and plotting with Matplotlib and Seaborn. Work through it to load, clean and summarize tabular datasets, then chart the results in code.

See all Data Analysis resources →