Coursera

Python Packages for Data Science (Coursera)

Offered by University of Colorado Boulder,

How many times have you decided to learn a programming language but got stuck somewhere along the way, grew frustrated, and gave up? This specialization is designed for learners who have little or no programming experience but want to use Python as a tool to play with data.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Now that you have mastered the fundamentals of Python and Python functions, you will turn your attention to Python packages specifically used for Data Science, such as Pandas, Numpy, Matplotlib, and Seaborn.
Course 3 of 3 in the Expressway to Data Science: Python Programming Specialization.

Are you ready? Let's go!

What You Will Learn

By successfully completing this course, you will be able to use Python pacakges developed for data science.
You will learn how to use Numpy and Pandas to manipulate data.
You will learn how to use Matplotlib and Seaborn to develop data visualizations.

Syllabus

WEEK 1
Hello, packages!
Now you have learned the basics of Python to be able to play the magic! In this module, you are going to learn Python packages and experience their convenience and power. You are going to use the packages for something fun. Are you ready? Let's go!

WEEK 2
Data Manipulation: Numpy and Pandas
In Data Science, we play with data. Python has many useful packages for data creation, integration, and manipulation. In this module, you are going to learn NumPy and Pandas, the most widely used two packages for data science. Are you ready? Let's go!

WEEK 3
Data Visualization: Matplotlib
An outstanding data scientist is good at not only data processing and data analyzing but also data visualization and communication. In this module, you are going to learn Matplotlib, one of the most widely used Python package to transform your data in a much more interesting taste. Are you ready? Let's go!

WEEK 4
Data Visualization: Seaborn
Data visualization can be done by matplotlib, and it is not enough. Seaborn is built upon matplotlib, and it provides even more power and convenience to the project. Are you ready? Let's go!

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Coursera

University of Colorado System

Business Intelligence Concepts, Tools, and Applications (Coursera)

Statistics & Data Analysis Data Science

This is the fourth course in the Data Warehouse for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will gain the knowledge and skills for using data warehouses for business intelligence purposes and for working as a business intelligence developer. You’ll have the opportunity to work with large data sets in a data warehouse environment and will learn the use of MicroStrategy's Online Analytical Processing (OLAP) and Visualization capabilities to create visualizations and dashboards.

Jul 6th 2026

5-12 Weeks

Data Analysis Decision Making Business Intelligence

Coursera

IBM

Data Science Methodology (Coursera)

Statistics & Data Analysis Data Science

Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.

Jul 10th 2026

3 Weeks

Data Modeling Methodology Data Science

Coursera

The Hong Kong University of Science and Technology - HKUST

Understanding China, 1700-2000: A Data Analytic Approach, Part 2 (Coursera)

Statistics & Data Analysis Data Science

The purpose of this course is to summarize new directions in Chinese history and social science produced by the creation and analysis of big historical datasets based on newly opened Chinese archival holdings, and to organize this knowledge in a framework that encourages learning about China in comparative perspective. Our course demonstrates how a new scholarship of discovery is redefining what is singular about modern China and modern Chinese history.

Jul 6th 2026

4 Weeks

History China Data Science

Coursera

University of Washington

Machine Learning: Classification (Coursera)

Statistics & Data Analysis Data Science

Case Studies: Analyzing Sentiment & Loan Default Prediction. In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,...). In our second case study for this course, loan default prediction, you will tackle financial data, and predict when a loan is likely to be risky or safe for the bank.

Jul 6th 2026

5-12 Weeks

Python Machine Learning Classification

Coursera

University of California, San Diego

Biology Meets Programming: Bioinformatics for Beginners (Coursera)

CS: Software Engineering CS: Theory

Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python.

Jul 6th 2026

4 Weeks

Health Biology Programming

Coursera

PwC

Data Visualization with Advanced Excel (Coursera)

Statistics & Data Analysis Data Science

In this course, you will get hands-on instruction of advanced Excel 2013 functions. You’ll learn to use PowerPivot to build databases and data models. We’ll show you how to perform different types of scenario and simulation analysis and you’ll have an opportunity to practice these skills by leveraging some of Excel's built in tools including, solver, data tables, scenario manager and goal seek.

Jul 6th 2026

4 Weeks

Databases Excel Data Analysis

Coursera

Google

Using Python to Interact with the Operating System (Coursera)

CS: Information & Technology Computer Science

By the end of this course, you’ll be able to manipulate files and processes on your computer’s operating system. You’ll also have learned about regular expressions -- a very powerful tool for processing text files -- and you’ll get practice using the Linux command line on a virtual machine. And, this might feel like a stretch right now, but you’ll also write a program that processes a bunch of errors in an actual log file and then generates a summary file. That’s a super useful skill for IT Specialists to know.

Jul 7th 2026

5-12 Weeks

Programming Python Regular Expressions

Coursera

Johns Hopkins University

Reproducible Research (Coursera)

Statistics & Data Analysis Data Science

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations.

Jul 6th 2026

4 Weeks

Data Analysis Data Science Reproducible Research

Coursera

Johns Hopkins University

Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera)

Statistics & Data Analysis Data Science

Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: a basic understanding of linear algebra and multivariate calculus; a basic understanding of statistics and regression models; at least a little familiarity with proof based mathematics; basic knowledge of the R programming language.

Jul 6th 2026

4 Weeks

Algebra Linear Algebra Data Science

Coursera

University of Michigan

Using Python to Access Web Data (Coursera)

CS: Software Engineering

This course will show how one can treat the Internet as a source of data. We will scrape, parse, and read web data as well as access data using web APIs. We will work with HTML, XML, and JSON data formats in Python.

Jul 6th 2026

5-12 Weeks

Programming Python XML

Coursera

Johns Hopkins University

Regression Models (Coursera)

Statistics & Data Analysis Data Science

Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models.

Jul 6th 2026

4 Weeks

Statistics Regression Linear Regression

Coursera

IBM

Python for Data Science, AI & Development (Coursera)

CS: Programming Data Science

Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. Python is one of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries.

Jul 7th 2026

5-12 Weeks

Programming Python Artificial Intelligence