Probability Theory Courses and Certifications

Topics in Mathematics with Applications in Finance - Fall 2024

Explore mathematical concepts and techniques used in finance through linear algebra, probability, statistics, stochastic processes, and numerical methods with industry applications.

• YouTube
• 1 day 2 hours 12 minutes
• On-Demand
• Free Video

MindYourDecisions

The Famous Batteries and Flashlight Logic Puzzle - Optimal Testing Strategy

Solve a famous logic puzzle: determine the minimum tests needed to find 2 good batteries out of 4 good and 4 bad ones to power a flashlight. Explores strategies and provides proof.

• YouTube
• 18 minutes
• On-Demand
• Free Video

Numberphile

The Big Daddy of Infinite Integrals - Exploring the Gaussian Integral

Discover the Gaussian Integral, the most important infinite integral in mathematics, through expert exploration of its elegant proof and wide-ranging applications.

• YouTube
• 21 minutes
• On-Demand
• Free Video

NPTEL;  IIT Madras

Probability Foundation for Electrical Engineers

Comprehensive exploration of probability theory for electrical engineers, covering fundamental concepts, random variables, expectation, and limit theorems with rigorous mathematical foundations.

• YouTube
• 1 day 14 hours
• On-Demand
• Free Video

NPTEL;  IIT Kharagpur

Mathematics - Probability and Statistics

Comprehensive exploration of probability and statistics, covering set theory, probability laws, distributions, sampling, descriptive statistics, estimation, and hypothesis testing.

• YouTube
• 1 day 14 hours
• On-Demand
• Free Video

NPTEL;  IIT Kharagpur

Estimation of Signals and Systems

This course covers lessons on probability theory, random variables, mean and variance, linear signal models, z-transform, Kalman filter, variants of least squares estimation, and estimation problems in instrumentation and control.

• YouTube
• 1 day 2 hours
• On-Demand
• Free Video

UCLA Automated Reasoning Group

Learning and Reasoning with Bayesian Networks

Master probabilistic reasoning and machine learning through comprehensive coverage of Bayesian networks, from basic probability theory to advanced inference algorithms and causal modeling.

• YouTube
• 22 hours 11 minutes
• On-Demand
• Free Video

Richard McElreath

Statistical Rethinking Fall 2017

Master Bayesian statistical methods and causal inference through comprehensive lectures accompanying the acclaimed "Statistical Rethinking" book by Richard McElreath.

• YouTube
• 19 hours 46 minutes
• On-Demand
• Free Video

AnalystPrep

FRM Part 1 - Book 2 - Quantitative Analysis

Master quantitative analysis for FRM Part 1 with probability, hypothesis testing, regression, and machine learning concepts through detailed examples and practice questions.

• YouTube
• 7 hours 45 minutes
• On-Demand
• Free Video

3Blue1Brown

Convolutions and Adding Random Variables, Visually Explained

Visual explanation of convolutions and adding random variables, exploring discrete and continuous cases, with connections to the central limit theorem and practical examples.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Data Compression I - Lecture 5: Asymptotic Equipartition Property

Explore the Asymptotic Equipartition Property in data compression, a fundamental concept for understanding information theory and efficient coding techniques.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Free Video

Stanford EE274: Data Compression - Beyond IID Distributions: Conditional Entropy - Lecture 8

Explore conditional entropy and advanced data compression techniques beyond IID distributions in this Stanford lecture, enhancing understanding of complex information theory concepts.

• YouTube
• 1 hour 16 minutes
• On-Demand
• Free Video

Deep Generative Models - Maximum Likelihood Learning - Lecture 4

Explore maximum likelihood learning in deep generative models with Stanford's Stefano Ermon. Gain insights into advanced AI techniques and their applications in this comprehensive lecture.

• YouTube
• 1 hour 24 minutes
• On-Demand
• Free Video

Deep Generative Models - Lecture 2: Background

Explore fundamental concepts and background for deep generative models, covering essential topics to build a strong foundation in this advanced machine learning field.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Free Video

Alan Turing Institute

Constructing Physics-Consistent Neural Networks Using Probability Theory

Explore the link between probability, physics, and neural networks, focusing on constructing physics-consistent models using Gaussian processes and the central limit theorem.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video