Mathematics Courses and Certifications

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
• Self-Paced
• Paid Course

Generalized Linear Models and Nonparametric Regression

21 ratings at Coursera

Explore advanced statistical modeling tools including GLMs, nonparametric regression, and GAMs. Learn to apply these techniques for classification, data analysis, and ethical decision-making in data science.

• Coursera
• 1 day 18 hours 4 minutes
• Self-Paced
• Paid Course

Microcredential

Statistical Learning for Data Science

20 ratings at Coursera

Gain advanced statistical learning techniques for data science, including model selection, regression, classification, and unsupervised learning. Develop skills to explain and justify models effectively.

• Coursera
• 16 weeks, 9 hours a week
• Self-Paced
• Paid Course
• 3 courses

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
• Self-Paced
• Free Online Course (Audit)

From Data to Decisions: Making Predictions with AI

17 ratings at Coursera

Master predictive analytics using AI tools to run regression models, interpret statistical outputs, and transform raw data into actionable business insights and accurate forecasts.

• Coursera
• 1 hour 45 minutes
• Self-Paced
• Paid Course

Probability: Distribution Models & Continuous Random Variables

Learn about probability distribution models, including normal distribution, and continuous random variables to prepare for a career in information and data science.

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

Microcredential

Quantum Technology: Detectors and Networking

Explore quantum detectors, sensors, and networking fundamentals. Gain hands-on experience with quantum computing, covering physics and engineering aspects. Minimal prerequisites required.

• edX
• 38 weeks, 6-8 hours a week
• Self-Paced
• $5,583.00
• 2 courses

Regression and Classification

16 ratings at Coursera

Explore statistical modeling concepts, including regression, classification, and unsupervised techniques. Learn when to use specific models, how to tune them, and understand trade-offs for informed decision-making.

• Coursera
• 1 day 10 hours 50 minutes
• Self-Paced
• Paid Course

Competitive Programming Essentials, Master Algorithms

2647 ratings at Udemy

Master competitive coding techniques - maths, number theory, dynamic programming, advanced data structures & algorithms

• Udemy
• 2 days 8 hours 42 minutes
• Self-Paced
• Paid Course

Math for MBA and GMAT Prep

51 ratings at Coursera

Comprehensive statistics and math refresher for MBA aspirants, covering Excel tools, business concepts, and data analysis techniques.

• Coursera
• 12 hours 54 minutes
• Self-Paced
• Paid Course

Special Relativity

4 reviews

Einstein’s Special Relativity upended our understanding of space, time and energy. While the ideas are subtle, they only require high school algebra, so join this math-based introduction with acclaimed physicist and author, Brian Greene.

• World Science U
• Self-Paced
• Free Online Course

Statistics for Data Analysis Using R

2632 ratings at Udemy

Learn Programming in R & R Studio • Descriptive, Inferential Statistics • Plots for Data Visualization • Data Science

• Udemy
• 12 hours 26 minutes
• Self-Paced
• Paid Course

Measurement Systems Analysis

10 ratings at Coursera

Analyze measurement systems for process stability and capability, covering continuous and discrete data analysis, ANOVA, correlation, and decision-making for process improvement using R software.

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

Regression Analysis

10 ratings at Coursera

Master regression analysis techniques to model relationships, prevent overfitting, and make data-driven decisions. Explore linear and polynomial regression, regularization, cross-validation, and ensemble methods through hands-on practice.

• Coursera
• 1 day 16 hours 1 minute
• Self-Paced
• Paid Course

Probability Theory

12 ratings at edX

This course provides an introduction to probability theory. You will encounter discrete and continuous random variables and learn in which situations they appear, what their properties are and how they interact.

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