Difference between revisions of "LII:Python for Data Science"
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'''Publication date''': 2022 | '''Publication date''': 2022 | ||
This is a UC San Diego course that is released on the edX platform. The 10-week course "that will introduce you to a collection of powerful, open-source, tools needed to analyze data and to conduct data science." The course is free to take, with a Verified Certificate of completion available for $350. (Note that the free Audit track expires | This is a UC San Diego course that is released on the edX platform. The 10-week course "that will introduce you to a collection of powerful, open-source, tools needed to analyze data and to conduct data science." The course is free to take, with a Verified Certificate of completion available for $350. (Note that the free Audit track expires November 19, 2022.) The course requires on average eight to 10 hours a week of effort. | ||
The edX course description: | The edX course description: | ||
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===The course=== | ===The course=== | ||
[[File:PDF.png|40px|link=https://www.edx.org/course/python-for-data-science-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/python-for-data-science-2 Data Analysis & Statistics] category. Access to the class began | [[File:PDF.png|40px|link=https://www.edx.org/course/python-for-data-science-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/python-for-data-science-2 Data Analysis & Statistics] category. Access to the class began September 2022 and ends November 22, with the free audit track closing November 19, 2022. Another session will begin on December 6. | ||
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[[Category:LII:Courses]] | [[Category:LII:Courses]] | ||
Revision as of 18:04, 10 September 2022
Title: Python for Data Science
Author for citation: Leo Porter and Ilkay Altintas
License for content: Unknown
Publication date: 2022
This is a UC San Diego course that is released on the edX platform. The 10-week course "that will introduce you to a collection of powerful, open-source, tools needed to analyze data and to conduct data science." The course is free to take, with a Verified Certificate of completion available for $350. (Note that the free Audit track expires November 19, 2022.) The course requires on average eight to 10 hours a week of effort.
The edX course description:
"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?"
"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."
NOTE: This course is part of an overall Data Science MicroMasters program offered by UC San Diego.
About the authors
The instructors for this course are Leo Porter and Ilkay Altintas. See each professor's profile for full details.
General layout and contents of the course
No syllabus is publicly provided. The EdX page notes:
"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"
The course
: The course can be found on the edX site, under the Data Analysis & Statistics category. Access to the class began September 2022 and ends November 22, with the free audit track closing November 19, 2022. Another session will begin on December 6.
