Mathematics Courses and Certifications

Microcredential

Modern Statistics for Data-Driven Decision-Making

Master statistical methods for data-driven decisions across business, industrial, and social environments with probability, regression, Bayesian concepts, and classification techniques.

• Coursera
• 4 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 4 courses

Bayesian Statistical Concepts and Methods

Master Bayesian methods for data analysis using posterior distributions, MCMC algorithms, and hierarchical models with R and Stan platform implementation.

• Coursera
• 5 hours 30 minutes
• Self-Paced
• Paid Course

Modern Statistical Computing and Regression Modeling in R

Discover statistical computing with R, Excel, Tableau, and Jupyter Notebooks while mastering Monte Carlo methods and regression analysis through hands-on practice with real datasets.

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

Indian Institute of Management Ahmedabad

Pre-MBA Statistics

301 ratings at Coursera

Comprehensive introduction to descriptive and inferential statistics, covering data types, probability, sampling methods, estimation, and hypothesis testing for effective data analysis and interpretation.

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

Integral Calculus and Numerical Analysis for Data Science

109 ratings at Coursera

Intuitive approach to integral calculus and numerical analysis, covering integration, root-finding, matrix decomposition, and partial derivatives for data science applications.

• Coursera
• 3 hours 32 minutes
• Self-Paced
• Paid Course

Statistics with SAS

301 ratings at Coursera

This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression.

• Coursera
• 20 hours 19 minutes
• Self-Paced
• Paid Course

Linear Algebra for Machine Learning

Learn the linear algebra concepts behind machine learning.

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

Statistics for Machine Learning

Learn the statistical concepts behind machine learning.

• edX
• 4 weeks, 3-6 hours a week
• Self-Paced
• Free Online Course (Audit)

R, ggplot, and Simple Linear Regression

3899 ratings at Udemy

Begin to use R and ggplot while learning the basics of linear regression

• Udemy
• 2 hours 14 minutes
• Self-Paced
• Free Online Course

Data Analysis for Managerial Decision-Making

18 ratings at Coursera

Refresh quantitative skills for MBA programs through practical examples and Excel-based data analysis, covering math, statistics, and real-world applications.

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

Statistical Methods

10 ratings at Coursera

Learn statistical methods through real-life examples, R programming, and probability experiments. Develop skills in data analysis, visualization, and interpretation using RStudio. Gain practical insights applicable to various fields.

• Coursera
• 11 hours 52 minutes
• Self-Paced
• Paid Course

Linear Algebra, Part 1

5 ratings at edX

This course is an introduction to linear algebra. You will discover the basic objects of linear algebra – how to compute with them, how they fit together theoretically, and how they can be used to solve real problems.

• edX
• 8 weeks, 6-8 hours a week
• Self-Paced
• Free Online Course (Audit)

Stability and Capability in Quality Improvement

17 ratings at Coursera

Aprende a analizar la estabilidad del proceso y el control estadístico, crear gráficos de control con R, y evaluar la capacidad del proceso para mejorar la calidad.

• Coursera
• 9 hours 40 minutes
• Self-Paced
• Paid Course

Statistics for Applications

1 review

This course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications.

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

Ordinary Differential Equations and Linear Algebra - Part 1

Explore mathematical modeling of natural phenomena through qualitative and quantitative analysis of 1st order differential equations and linear algebra.

• edX
• 7 weeks, 2-8 hours a week
• Self-Paced
• Free Online Course (Audit)