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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, MOA and data processing libraries in associated language environments. Categories:
Starts :
2017-09-08 |
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AlternativesIf you know any alternatives, please let us know. PrerequisitesIf you can suggest any prerequisite, please let us know. Certification Exams-- there are no exams to get certification after this course --If your company does certification for those who completed this course then register your company as certification vendor and add your exams to the Exams Directory. | ||
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