Learn about probability, statistics, and more using the mathematics that are foundational to the field of data science.
InstructorJose PortillaInstruction provides detailed explanations for core statistical concepts, such as the reasoning behind squaring values in variance calculations.
The curriculum spans essential topics including central tendency, dispersion, various probability distributions, and linear regression.
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
This educational slide illustrates normal distribution by displaying a sample dataset of student test scores alongside a corresponding purple histogram that visually represents the frequency of those scores.
This introductory slide presents the course instructors, Jose Portilla and Krista King, highlighting their combined expertise in mathematical foundations like calculus and programming skills such as Python.
An illustration depicts a student holding a graded paper while sitting on a monitor, accompanied by the text 'Assessment questions to test your understanding.'
Practice problems are often placed at the end of large thematic sections rather than accompanying individual practical videos.
Some theoretical segments may rely on reading from slides without sufficient verbal explanation, creating an inconsistent experience.
Selected from the course's public promotional preview. These images document visible presentation material only; they do not represent the complete paid curriculum.
The curriculum aligns with the goal of providing a mathematical foundation for those interested in data science.
