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UCSanDiegoX: Probability and Statistics in Data Science using Python

3.6 stars
11 ratings

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data.

Probability and Statistics in Data Science using Python
10 weeks
10–12 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

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Starts Mar 19
Ends Mar 22
Starts Mar 26
Ends Jul 12

About this course

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 program, 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

  • Language: English
  • Video Transcript: English
  • Associated programs:
  • Associated skills:Python (Programming Language), Jupyter, Random Variables, Data Science, Probability And Statistics

What you'll learn

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 not 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.

This course is part of Data Science MicroMasters Program

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Expert instruction
4 graduate-level courses
10 months
9 - 11 hours per week

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