Mathematics 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

Honors Algebra 2: Linear and Quadratic Functions

Master linear and quadratic functions through rigorous exploration of equations, graphing, and real-world modeling with university-level depth and mathematical reasoning.

• Coursera
• 12 hours 22 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

Business Analytics with Excel: Intermediate to Advanced

Master advanced Excel optimization techniques including linear, integer, network, and nonlinear programming with VBA macros for sophisticated business decision-making and multi-objective analysis.

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

Honors Algebra 2: Series, Trigonometry, and Probability

Master sequences, series, trigonometry, and probability through real-world applications, from modeling population growth to analyzing periodic patterns and quantifying uncertainty.

• Coursera
• 18 hours 24 minutes
• Self-Paced
• Paid Course

Data Science Decisions in Time: Using Causal Information

Explore causal decision-making in data science, focusing on optimizing policies, pricing, and actions using causal structures and advanced analytical techniques for business, medical, and technological applications.

• Coursera
• 1 day 5 hours 23 minutes
• Self-Paced
• Paid Course

Honors Algebra 2: Polynomials and Complex Numbers

Master polynomial functions, complex numbers, and advanced algebraic techniques to solve higher-order equations and analyze mathematical relationships in this rigorous algebra course.

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

Honors Algebra 2: Algebraic, Exponential & Log Functions

Master advanced function families including exponential, logarithmic, radical, and inverse functions through theory and real-world applications like growth modeling and data analysis.

• Coursera
• 15 hours 2 minutes
• Self-Paced
• Paid Course

Microcredential

Honors Algebra 2

Master advanced algebraic concepts including exponential, logarithmic, and polynomial functions while developing problem-solving skills for STEM applications and college readiness.

• Coursera
• Self-Paced
• Paid Course
• 3 courses

Microcredential

Honors Algebra 2

Master advanced algebraic concepts including exponential, logarithmic, and polynomial functions while developing problem-solving skills for real-world STEM applications.

• Coursera
• Self-Paced
• Paid Course
• 4 courses

Goldsmiths University of London;  University of London

Foundations of Data Science: K-Means Clustering in Python

735 ratings at Coursera

Learn essential data science concepts, focusing on K-means clustering in Python. Develop mathematical, statistical, and programming skills through hands-on exercises and a practical data clustering project.

• Coursera
• 1 day 5 hours 8 minutes
• Self-Paced
• Paid Course

Linear Regression in R for Public Health

529 ratings at Coursera

Aprenda a criar modelos estatísticos em R para analisar fatores que afetam doenças e resultados de saúde, focando em regressão linear e suas aplicações em saúde pública.

• Coursera
• 15 hours 2 minutes
• Self-Paced
• Paid Course

Causal Inference

104 ratings at Coursera

Rigorous mathematical exploration of causal inference methods, including randomization, regression, propensity scores, and matching. Ideal for understanding and applying causal relationships in various fields.

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

Probability & Statistics for Machine Learning & Data Science

681 ratings at Coursera

Explore probability, statistics, and data analysis for machine learning. Apply concepts using Python in hands-on exercises. Gain skills in estimation, hypothesis testing, and exploratory data analysis.

• Coursera
• 1 day 9 hours 28 minutes
• Self-Paced
• Paid Course

Inferential Statistics

609 ratings at Coursera

Explore inferential statistics, from hypothesis testing to advanced techniques like regression and ANOVA. Learn to analyze data, make inferences, and interpret results using various statistical tests.

• Coursera
• 14 hours 41 minutes
• Self-Paced
• Paid Course