Computing for Data Analysis

MOOC
Computing for Data Analysis
Language
English
Duration
4 months
Certificate
Certification paid
Course by EdX
Computing for Data Analysis
What will you learn?
The Big Data Capstone project will give you the chance to demonstrate practically what you have learned in the Big Data MicroMasters program including:How to evaluate, select and apply data science techniques, principles and theory;
How to plan and execute a project;
Work autonomously using your own initiative;
Identify social and ethical concerns around your project;
Develop communication skills using online collaborative technologies.
About the course

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.

Program
Computing for Data Analysis
A hands-on introduction to basic programming principles and practice relevant to modern data analysis, data mining, and machine learning.
Computing for Data Analysis
A hands-on introduction to basic programming principles and practice relevant to modern data analysis, data mining, and machine learning.
Computing for Data Analysis
A hands-on introduction to basic programming principles and practice relevant to modern data analysis, data mining, and machine learning.
Computing for Data Analysis
A hands-on introduction to basic programming principles and practice relevant to modern data analysis, data mining, and machine learning.
Lecturers
Richard (Rich) Vuduc
Richard (Rich) Vuduc
Professor of Computational Science and Engineering The Georgia Institute of Technology
Platform
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All the courses on this platform are free of charge. The authors are top universities and corporations that seek to maintain high quality standards. If you do not meet a deadline for assignments, you lose points. Like on other platforms, the videos in which the theory is explained are followed by practical assignments. Courses are available in English, Chinese, Spanish, French and Hindi.
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