Coursera

Select Topics in Python: Matplotlib (Coursera)

Offered by Codio,

Code and run your first Python script with Matplotlib in minutes without installing anything! This course is designed for learners with some Python experience, and provides a crash course in Matplotlib. This enables the learners to delve into core data visualization topics that can be transferred to other languages. In this course, you will learn how to use Jupyter, generate and choose the best graphs to represent your data.

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

To allow for a truly hands-on, self-paced learning experience, this course is video-free.
Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours.
Course 3 of 4 in the Select Topics in Python Specialization.

What You Will Learn

Jupyter notebooks
Create charts and plots
Style and customize charts and plots

Syllabus

WEEK 1
Intro to Matplotlib
Welcome to Week 1 of the Select Topics in Python: Matplotlib course. These assignments cover the basics of Jupyter notebooks and Matplotlib, customizing a visualization, as well as box plots and histograms. The module ends with graded coding exercises.

WEEK 2
Intermediate Matplotlib
Welcome to Week 2 of the Select Topics in Python: Matplotlib course. These assignments extend the previous module by introducing line charts, area charts, scatter plots, bubble charts, pie charts, and donut charts. The module ends with graded coding exercises.

WEEK 3
Advanced Matplotlib
Welcome to Week 3 of the Select Topics in Python: Matplotlib course. These assignments cover specialized visualizations, configuring layout and presentation, and adding animations. The module ends with graded coding exercises.

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

IBM

Python Project for Data Science (Coursera)

Statistics & Data Analysis Data Science

This mini-course is intended to for you to demonstrate foundational Python skills for working with data. The completion of this course involves working on a hands-on project where you will develop a simple dashboard using Python. This course is part of the IBM Data Science Professional Certificate and the IBM Data Analytics Professional Certificate.

Jun 4th 2026

1 Week

Python IPython Data Analysis

Coursera

Nanjing University

Data Processing Using Python (Coursera)

CS: Software Engineering Statistics & Data Analysis

This course is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level.

Jun 1st 2026

5-12 Weeks

Python Data Structures Data Analysis

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.

Jun 1st 2026

5-12 Weeks

Python Machine Learning Classification

Coursera

University of Michigan

Understanding and Visualizing Data with Python (Coursera)

Data Science

In this course, learners will be introduced to the field of statistics, including where data come from, study design, data management, and exploring and visualizing data. Learners will identify different types of data, and learn how to visualize, analyze, and interpret summaries for both univariate and multivariate data. Learners will also be introduced to the differences between probability and non-probability sampling from larger populations, the idea of how sample estimates vary, and how inferences can be made about larger populations based on probability sampling.

Jun 1st 2026

4 Weeks

Python Statistics Data Analysis

Coursera

EDHEC Business School

Introduction to Portfolio Construction and Analysis with Python (Coursera)

Economics & Finance Business

The practice of investment management has been transformed in recent years by computational methods. This course provides an introduction to the underlying science, with the aim of giving you a thorough understanding of that scientific basis. However, instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language.

Jun 1st 2026

4 Weeks

Python Portfolio Optimization Portfolio Analysis

Coursera

Tufts University

Hypothesis Testing with Python and Excel (Coursera)

Statistics & Data Analysis Data Science

In today's job market, leaders need to understand the fundamentals of data to be competitive. An essential procedure to understand business and analytics is hypothesis testing. This short course, designed by Tufts University expert faculty, will teach the fundamentals of hypothesis testing of a population mean and a population proportion, using Excel and Python for calculations. You'll also discover the central limit theorem, which is essential for hypothesis testing. To conclude the course, you will apply your newfound skills by creating a plan for an experiment in your own workplace that uses hypothesis testing.

Jun 2nd 2026

1 Week

Python Excel Python Programming

Coursera

University of Washington

Machine Learning: Regression (Coursera)

Statistics & Data Analysis Data Science

Case Study - Predicting Housing Prices. In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression.

Jun 1st 2026

5-12 Weeks

Python Algorithms Machine Learning

Coursera

EDHEC Business School

Python and Machine Learning for Asset Management (Coursera)

Economics & Finance Data Science

This course will enable you mastering machine-learning approaches in the area of investment management. It has been designed by two thought leaders in their field, Lionel Martellini from EDHEC-Risk Institute and John Mulvey from Princeton University. Starting from the basics, they will help you build practical skills to understand data science so you can make the best portfolio decisions.

Jun 1st 2026

5-12 Weeks

Programming Python Machine Learning

Coursera

Rice University

Python Programming Essentials (Coursera)

CS: Software Engineering CS: Programming

This course will introduce you to the wonderful world of Python programming! We'll learn about the essential elements of programming and how to construct basic Python programs. We will cover expressions, variables, functions, logic, and conditionals, which are foundational concepts in computer programming. We will also teach you how to use Python modules, which enable you to benefit from the vast array of functionality that is already a part of the Python language. These concepts and skills will help you to begin to think like a computer programmer and to understand how to go about writing Python programs.

Jun 1st 2026

4 Weeks

Programming Python Debugging

Coursera

Rice University

Python Data Representations (Coursera)

CS: Software Engineering CS: Programming

This course will continue the introduction to Python programming that started with Python Programming Essentials. We'll learn about different data representations, including strings, lists, and tuples, that form the core of all Python programs. We will also teach you how to access files, which will allow you to store and retrieve data within your programs. These concepts and skills will help you to manipulate data and write more complex Python programs.

Jun 1st 2026

4 Weeks

Programming Python Software Development

Coursera

EDHEC Business School

Python and Machine-Learning for Asset Management with Alternative Data Sets (Coursera)

Economics & Finance Business

Over-utilization of market and accounting data over the last few decades has led to portfolio crowding, mediocre performance and systemic risks, incentivizing financial institutions which are looking for an edge to quickly adopt alternative data as a substitute to traditional data. This course introduces the core concepts around alternative data, the most recent research in this area, as well as practical portfolio examples and actual applications.

Jun 1st 2026

4 Weeks

Python Machine Learning Asset Management

Coursera

University of Alberta

Problem Solving, Python Programming, and Video Games (Coursera)

CS: Programming

This course is an introduction to computer science and programming in Python. Important computer science concepts such as problem solving (computational thinking), problem decomposition, algorithms, abstraction, and software quality are emphasized throughout. The Python programming language and video games are used to demonstrate computer science concepts in a concrete and fun manner. However, a learner can take the knowledge and skills from this course and apply them to non-game problems, other programming languages, and other computer science courses.

Jun 1st 2026

5-12 Weeks

Programming Python Algorithms