Probability Theory Courses and Certifications

Advanced Probability and Statistical Methods

Master advanced probability concepts through joint distributions, statistical testing, and Markov chains, building expertise in data analysis and statistical inference for real-world applications.

• Coursera
• 1 day 23 hours 46 minutes
• Self-Paced
• Paid Course

Random Processes

Master correlation functions, spectral analysis, and Monte Carlo simulation techniques for understanding and modeling random processes in engineering systems, with focus on practical applications and data analysis.

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

Computational and Graphical Models in Probability

Master computational probability through simulation techniques, network analysis, and graphical models using R. Build expertise in ERGMs and PGMs while gaining practical skills for complex data analysis and machine learning applications.

• Coursera
• 15 hours 56 minutes
• Self-Paced
• Paid Course

Statistics for International Business

316 ratings at Coursera

Introduces core statistical concepts for business, covering data presentation, probability, and estimation. Develops essential skills for international business and MBA studies through practical examples and self-assessment.

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

Credential

Essential Math for AI Programming & Data Structures

Master essential math concepts (discrete math, calculus, linear algebra, probability) and Python programming skills needed for AI, including data structures and key libraries like NumPy and Pandas.

• edX
• 7 weeks, 1-3 hours/week
• Self-Paced
• $150.00

Topics in Mathematics with Applications in Finance

4 ratings

The purpose of the class is to expose students to the mathematical concepts and techniques used in the financial industry. Mathematics lectures are mixed with lectures illustrating the corresponding application in the financial industry.

• MIT OpenCourseWare
• 32 hours
• Self-Paced
• Free Video

Credential

Data Science Foundations: Statistical Inference

357 ratings at Coursera

Gain a solid foundation in probability theory, statistical inference, and data analysis using R. Master essential skills for statistical hypothesis testing and confidence intervals in data science applications.

• Coursera
• 12 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Introduction to Process Safety and Risk Analysis

219 ratings at Coursera

Gain practical skills in identifying, evaluating, and mitigating hazards in chemical process engineering. Learn from historical incidents and apply risk assessment techniques for safer industrial practices.

• Coursera
• 8 hours 48 minutes
• Self-Paced
• Paid Course

Credential

Data Analysis with R

Comprehensive R-based data analysis program covering probability, inference, regression, and Bayesian statistics. Develop practical skills for data visualization, wrangling, and reproducible reporting.

• Coursera
• 30 weeks, 3 hours a week
• Self-Paced
• Paid Course
• 5 courses

Probability Foundations for Data Science and AI

287 ratings at Coursera

Explore probability foundations, random variables, and the Central Limit Theorem. Gain essential skills for data analysis and statistical inference in this comprehensive introduction to probability theory.

• Coursera
• 1 day 18 hours 21 minutes
• Self-Paced
• Paid Course

Emerging Technology, Disruption, and AI

33 ratings at Coursera

Explore emerging tech frontiers, predict future trends, and develop skills to thrive in a disruptive world. Gain insights on AI, futurism, and decision-making to lead innovation in the digital era.

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

Credential

Essential Mathematics for Computer Science

6 ratings at Coursera

Master discrete mathematics, logic, algebra, calculus, and algorithmic reasoning to build the rigorous mathematical foundation essential for computing, data science, and software engineering.

• Coursera
• 8 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 5 courses

Mathematics-Basics to Advanced for Data Science And GenAI

3787 ratings at Udemy

Build Strong math foundation with linear algebra,stats,probability,differential calculus for mastering data science

• Udemy
• 22 hours 56 minutes
• Self-Paced
• Paid Course

Introduction to Scientific Machine Learning

1 rating

Learn the basics of machine learning with hands-on practical examples on engineering applications.

• edX
• 16 weeks, 6-7 hours/week
• Self-Paced
• Free Online Course

Credential

Statistics and Applied Data Analysis

46 ratings at Coursera

Master statistical concepts from basics through advanced analysis, using Excel and R for data visualization, hypothesis testing, and predictive modeling across three progressive levels.

• Coursera
• 12 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses