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Python for Data Science

Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets.

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Choose your session:

314,832 already enrolled!
Starts Nov 21
Ends Nov 22
Starts Dec 6

Python for Data Science

Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets.

10 weeks
8–10 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

Choose your session:

314,832 already enrolled! After a course session ends, it will be archivedOpens in a new tab.
Starts Nov 21
Ends Nov 22
Starts Dec 6

About this course

Skip About this course

In the information age, data is all around us. Within this data are answers to compelling questions across many societal domains (politics, business, science, etc.). But if you had access to a large dataset, would you be able to find the answers you seek?

This course, part of the Data Science MicroMasters program, will introduce you to a collection of powerful, open-source, tools needed to analyze data and to conduct data science. Specifically, you'll learn how to use:

  • python
  • jupyter notebooks
  • pandas
  • numpy
  • matplotlib
  • git
  • and many other tools.

You will learn these tools all within the context of solving compelling data science problems.

After completing this course, you'll be able to find answers within large datasets by using python tools to import data, explore it, analyze it, learn from it, visualize it, and ultimately generate easily sharable reports.

By learning these skills, you'll also become a member of a world-wide community which seeks to build data science tools, explore public datasets, and discuss evidence-based findings. Last but not least, this course will provide you with the foundation you need to succeed in later courses in the Data Science MicroMasters program.

At a glance

  • Institution: UCSanDiegoX
  • Subject: Data Analysis & Statistics
  • Level: Advanced
  • Prerequisites:

    Previous experience with any programming language (Java, C, Pascal, Fortran, C++, Python, PHP, etc.) is expected.This includes a high school, or undergraduate equivalent, to an introduction to computer science course.Learners should be comfortable with loops, if/else, and variables.

  • Language: English
  • Video Transcript: English
  • Associated programs:

What you'll learn

Skip What you'll learn
  • Basic process of data science
  • Python and Jupyter notebooks
  • An applied understanding of how to manipulate and analyze uncurated datasets
  • Basic statistical analysis and machine learning methods
  • How to effectively visualize results

About the instructors

Who can take this course?

Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

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