Computational Thinking and Big Data

University of Adelaide
via edX

Learn the core concepts of computational thinking and how to collect, clean and consolidate large-scale datasets.

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Computational thinking is an invaluable skill that can be used across every industry, as it allows you to formulate a problem and express a solution in such a way that a computer can effectively carry it out.

In this course, part of the Big Data MicroMasters program, you will learn how to apply computational thinking in data science. You will learn core computational thinking concepts including decomposition, pattern recognition, abstraction, and algorithmic thinking.

You will also learn about data representation and analysis and the processes of cleaning, presenting, and visualizing data. You will develop skills in data-driven problem design and algorithms for big data.

The course will also explain mathematical representations, probabilistic and statistical models, dimension reduction and Bayesian models.

You will use tools such as R and Java data processing libraries in associated language environments.

Instructor(s)

Lewis Mitchell, Markus Wagner, Simon Tuke, Gavin Meredith, Ian Knight
University of Adelaide
via edX
Free (audit)
English
Paid Certificate Available
Estimated 10 weeks
Self paced
Introductory
Subtitles: English