Computing for Data Analysis
date_range Starts on August 19, 2019
event_note End date December 21, 2019
list 15 sequences
assignment Level : Advanced
chat_bubble_outline Language : English
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Key information

credit_card Free access
verified_user Fee-based Certificate
timer 120 hours in total

About the content

The modern data analysis pipeline involves collection, preprocessing, storage, analysis, and interactive visualization of data.

The goal of this course, part of the Analytics: Essential Tools and Methods MicroMasters program, is for you to learn how to build these components and connect them using modern tools and techniques.

In the course, you’ll see how computing and mathematics come together. For instance, “under the hood” of modern data analysis lies numerical linear algebra, numerical optimization, and elementary data processing algorithms and data structures. Together, they form the foundations of numerical and data-intensive computing.

The hands-on component of this course will develop your proficiency with modern analytical tools. You will learn how to mash up Python, R, and SQL through Jupyter notebooks, among other tools. Furthermore, you will apply these tools to a variety of real-world datasets, thereby strengthening your ability to translate principles into practice.

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Instructors

Richard (Rich) Vuduc
Professor of Computational Science and Engineering
The Georgia Institute of Technology

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Content designer

The Georgia Institute of Technology
The Georgia Institute of Technology
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Platform

Edx

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