Coursera

Python Packages for Data Science (Coursera)

Offered by University of Colorado Boulder,
Python Packages for Data Science (Coursera)

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

Experimentation for Improvement (Coursera) Coursera
McMaster University

Experimentation for Improvement (Coursera)

Statistics & Data Analysis Data Science

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

Jun 22nd 2026
5-12 Weeks
Statistics Data Science Regression Models
Details
Exploratory Data Analysis (Coursera) Coursera
Johns Hopkins University

Exploratory Data Analysis (Coursera)

Statistics & Data Analysis Data Science

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.

Jun 22nd 2026
4 Weeks
Statistics Data Analysis Data Science
Details
Introduction to Genomic Technologies (Coursera) Coursera
Johns Hopkins University

Introduction to Genomic Technologies (Coursera)

Statistics & Data Analysis Data Science

This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed.

Jun 22nd 2026
4 Weeks
Biology DNA RNA
Details
Python for Data Science, AI & Development (Coursera) 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.

Jun 23rd 2026
5-12 Weeks
Programming Python Artificial Intelligence
Details
Introduction to Machine Learning (Coursera) Coursera
Duke University

Introduction to Machine Learning (Coursera)

Data Science

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction.

Jun 26th 2026
5-12 Weeks
ML NLP Machine Learning
Details
Introduction to Data Science in Python (Coursera) Coursera
University of Michigan

Introduction to Data Science in Python (Coursera)

CS: Software Engineering Statistics & Data Analysis

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

Jun 22nd 2026
4 Weeks
Python Data Analysis Data Science
Details
Business Intelligence Concepts, Tools, and Applications (Coursera) 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.

Jun 22nd 2026
5-12 Weeks
Data Analysis Decision Making Business Intelligence
Details
Hypothesis Testing with Python and Excel (Coursera) 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 23rd 2026
1 Week
Python Excel Python Programming
Details