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10 weeks

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Skip About this course

The job of a data scientist is to glean knowledge from complex and noisy datasets.

Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning.

In this course, part of the Data Science MicroMasters acara, you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get a hands-on experience of applying this theory to actual data using Jupyter notebooks.

Concepts covered included: random variables, dependence, correlation, regression, PCA, entropy and MDL.

At a glance

  • Institution:

    UCSanDiegoX
  • Subject:


    Data Analysis & Statistics
  • Level:

    Advanced

  • Prerequisites:

    1. The previous coursein the MicroMasters programa: DSE200x
    2. Undergraduate level education in:
      • Multivariate calculus
      • Linear algebra
  • Language:

    English

  • Video Transcript:

    English

  • Associated programs:

    • MicroMasters®

      Programa
      in Data Science

Skip What you’ll learn

  • The mathematical foundations for machine learning
  • Statistics literacy: understand the meaning of statements such as “at a 99% confidence level”

Who can take this course?

Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are titinada broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

Ways to take this course

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$350 USD

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Expires on Nov 28

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Source: https://www.edx.org/course/probability-and-statistics-in-data-science-using-p

Source: https://soal.hwatrr.com/python-for-data-science-tutorial-pdf/