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Course Description

Probability and statistics form the mathematical foundation for making informed decisions in the face of uncertainty. These tools are integral to areas such as predictive modeling, data science, and machine learning, helping you analyze variability, identify patterns, and develop robust algorithms.

In this course, you will explore how to evaluate datasets, simulate random systems using Monte Carlo methods, and estimate model parameters using techniques like maximum likelihood estimation. Designed for computational applications, this course equips you to model uncertainty, analyze statistical properties, and apply data-driven insights to improve algorithms and workflows.

Faculty Author

David Bindel; Anil Damle

Benefits to the Learner

  • Define probability distributions, calculate expected values, and apply tail bounds to model uncertainties in data
  • Generate samples from common probability distributions and evaluate statistical properties of datasets
  • Generate random numbers computationally and design Monte Carlo simulations to model stochastic systems
  • Apply estimation techniques, including maximum likelihood estimation, to determine model parameters from observed data

Target Audience

  • Software engineers building AI-powered applications
  • Data analysts and scientists working with large-scale datasets
  • Engineers applying computational methods to complex systems
  • Web and frontend developers integrating machine learning features
  • Computational biologists and scientific researchers modeling real-world phenomena Investment managers leveraging quantitative analysis
  • Game developers optimizing physics engines and AI behaviors
  • Anyone in a technical role seeking to strengthen their mathematical foundation for AI and machine learning

Applies Towards the Following Certificates

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Enroll Now - Select a section to enroll in
Type
2 week
Dates
Oct 21, 2026 to Nov 03, 2026
Total Number of Hours
20.0
Course Fee(s)
Standard Price $999.00
Type
2 week
Dates
Jan 13, 2027 to Jan 26, 2027
Total Number of Hours
20.0
Course Fee(s)
Standard Price $999.00
Type
2 week
Dates
Apr 07, 2027 to Apr 20, 2027
Total Number of Hours
20.0
Course Fee(s)
Standard Price $999.00
Type
2 week
Dates
Jun 30, 2027 to Jul 13, 2027
Total Number of Hours
20.0
Course Fee(s)
Standard Price $999.00
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