Conditional Probability Courses and Certifications

Microcredential

Probability/Random Variables

Explore probability concepts and random variables, enhancing modeling skills for real-world applications. Learn about discrete and continuous variables, expected values, and joint distributions using R statistical package.

• edX
• 7 weeks, 6-11 hours a week
• On-Demand
• $498.00
• 2 courses

Probability for Machine Learning

Master probability fundamentals and their direct applications in machine learning algorithms, from Bayes' Theorem to model evaluation metrics like ROC curves.

• edX
• 4 weeks, 2-5 hours a week
• On-Demand
• Free Online Course (Audit)

Discrete Math for Computer Science - Counting & Probability

Master combinatorial counting and probability theory to analyze algorithms, model uncertainty, and solve complex computational problems with systematic mathematical precision.

• Coursera
• 14 hours 21 minutes
• On-Demand
• Paid Course

Probability: Basic Concepts & Discrete Random Variables

Learn fundamental concepts of mathematical probability to prepare for a career in the growing field of information and data science.

• edX
• 6 weeks, 4-6 hours a week
• On-Demand
• Free Online Course (Audit)

Statistics Foundations: Probability

2637 ratings at LinkedIn Learning

Learn to understand your data in beginner-friendly lessons, using probability. Topics include permutations, percentiles, how to use probability trees, and much more.

• LinkedIn Learning
• 1 hour 10 minutes
• On-Demand
• Free Trial Available

Discrete-Time Markov Chains and Monte Carlo Methods

Explore discrete-time Markov chains, Monte Carlo methods, and their applications in AI, reinforcement learning, and stochastic simulation with mathematical rigor.

• Coursera
• 1 day 8 hours 32 minutes
• On-Demand
• Paid Course

Master Statistics for Data Science and Business Analysis

170 ratings at Udemy

Master foundational statistical concepts and their practical applications in data science and business analysis, from central tendency to probability theorems and data classification.

• Udemy
• 7 hours 48 minutes
• On-Demand
• Paid Course

A-Level Maths: Statistics (Year 2)

58 ratings at Udemy

Master the statistics content from A-level maths (second year), and practice on real past paper exam questions.

• Udemy
• 6 hours 11 minutes
• On-Demand
• Paid Course

EDUCBA

Bayesian Statistics: Excel to Python A/B Testing

27 ratings at Coursera

Master Bayesian statistics from Excel basics to Python A/B testing, covering MCMC sampling, hierarchical models, and healthcare decision-making with hands-on probabilistic modeling.

• Coursera
• 6 hours 24 minutes
• On-Demand
• 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
• On-Demand
• Paid Course

Birla Institute Of Technology And Science–Pilani (BITS–Pilani)

Probability and Statistics

Dive into statistical concepts, probability theory, and data analysis techniques to enhance decision-making skills and master real-world applications in various fields.

• Coursera
• 1 day 5 hours
• On-Demand
• Paid Course

CSET Math Subtest II (212): Practice & Study Guide

Comprehensive preparation for CSET Mathematics Subtest 2, covering geometry, probability, and statistics through video lessons and quizzes to help you excel on the exam.

• Study.com
• 12 hours
• On-Demand
• Paid Course

Introduction to Probability

Master probability theory fundamentals from MIT, covering random variables, Bayesian inference, statistical analysis, and Markov chains for data analysis applications.

• MIT OpenCourseWare
• On-Demand
• Free Online Course

Principles of Discrete Applied Mathematics

Master discrete mathematics through counting, probability, optimization, coding theory, and algebraic structures with hands-on problem-solving and communication skills development.

• MIT OpenCourseWare
• On-Demand
• Free Online Course

Stanford CS109 - Introduction to Probability for Computer Scientists 2022

Master probability theory fundamentals through combinatorics, random variables, distributions, and machine learning applications in this comprehensive Stanford computer science program.

• YouTube
• 1 day 11 hours 25 minutes
• On-Demand
• Free Video