Probability Distributions Courses and Certifications

Foundations for Machine Learning

Master essential probability distributions and Bayesian vs frequentist perspectives to build a strong mathematical foundation for machine learning and data science applications.

• Coursera
• 21 hours 28 minutes
• Self-Paced
• Paid Course

Statistics and Calculus Methods for Data Analysis

Master essential mathematical foundations for data science through statistics, calculus, and Python applications in expected values, derivatives, and integrals.

• Coursera
• 16 hours 5 minutes
• Self-Paced
• Paid Course

Probability Theory and Regression for Predictive Analytics

Master probability theory and regression techniques to build predictive models using Python, covering Bayes' Theorem, distributions, OLS, and advanced regression methods.

• Coursera
• 12 hours
• Self-Paced
• Paid Course

Ball State University

Statistical Methods for Data Science

Master statistical methods and probability theory for data science through hands-on applications in R, covering distributions, inference, multivariate analysis, and real-world problem-solving techniques.

• Coursera
• 1 day 15 hours 59 minutes
• Self-Paced
• Paid Course

Engineering Probability and Statistics Part 1

Discover foundational statistics and probability concepts including variables, distributions, and data analysis techniques for engineering applications.

• Coursera
• 22 hours 22 minutes
• Self-Paced
• Paid Course

Foundations for Data Analytics Part 2

Master time series analysis, text mining, network theory, and probability distributions through hands-on applications in data cleaning, clustering, and statistical modeling.

• Coursera
• 9 hours 43 minutes
• Self-Paced
• Paid Course

Econometrics - Theory and Practice

Master econometric theory and practice through regression analysis, hypothesis testing, and statistical inference for analyzing economic relationships and data.

• Coursera
• 1 day 7 hours 43 minutes
• Self-Paced
• Paid Course

Statistical Methods and Data Analysis

Discover statistical methods and R programming for data analysis, covering visualization, descriptive statistics, probability, sampling, significance tests, regression, and big data techniques.

• Coursera
• 20 hours 23 minutes
• Self-Paced
• Paid Course

American Psychological Association

Intro to Null Hypothesis Significance Testing with z-test

Master statistical hypothesis testing fundamentals through z-tests, probability concepts, and sampling distributions while learning to evaluate significance, effect size, and confidence intervals.

• Coursera
• 6 hours 3 minutes
• Self-Paced
• Paid Course

Introduction to Statistics: Help and Review

Comprehensive statistics review covering key concepts from data summarization to hypothesis testing, ideal for catching up or enhancing understanding.

• Study.com
• 18 hours 16 minutes
• Self-Paced
• Paid Course

Contemporary Math: Help and Review

Comprehensive review of contemporary math concepts, including problem-solving, statistics, probability, voting mathematics, graph theory, algebra, and arithmetic, with simplified video lessons for improved understanding and grades.

• Study.com
• 1 day 5 hours 28 minutes
• Self-Paced
• Paid Course

Contemporary Math

Explore graph theory, probability, statistics, and problem-solving techniques to enhance mathematical reasoning and apply contemporary math concepts to real-world scenarios.

• Study.com
• 14 hours 16 minutes
• Self-Paced
• Paid Course

Coursera

Simulate with Monte Carlo

Master Monte Carlo simulation techniques to quantify risk and forecast outcomes, building robust models for ROI analysis and sensitivity testing using Python and Excel.

• Coursera
• 3 hours 13 minutes
• Self-Paced
• Paid Course

Coursera

Forecast Financials with Monte Carlo Mastery

Master Monte Carlo simulation to transform financial forecasting from single-point estimates to probabilistic analysis, quantifying risk and uncertainty in Excel.

• Coursera
• 2 hours 33 minutes
• Self-Paced
• Paid Course

Must-Know Concepts - Basic requirements for data analysis

Master essential mathematical, statistical, and data-handling concepts for football analytics through practical examples and industry-standard tools.

• Coursera
• 17 hours 3 minutes
• Self-Paced
• Paid Course