STEM Courses and Certifications

Career Certificate

Integral Calculus through Data and Modeling

Develop integral calculus skills through data analysis, scientific computing, and mathematical modeling. Apply techniques to real-world problems in natural and social sciences.

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

Calculus through Data & Modelling: Vector Calculus

Explore vector calculus applications, including vector fields, line integrals, and Green's Theorem. Develop advanced mathematical skills for data analysis and real-world problem-solving in multivariable calculus.

• Coursera
• 4 hours 42 minutes
• Self-Paced
• Paid Course

Foundational Mathematics for AI

Gain insights into essential mathematical concepts powering AI - from functions and matrices to calculus and probability - with practical applications in machine learning and data analysis.

• Coursera
• 2 days 1 hour 8 minutes
• Self-Paced
• Paid Course

What are the Chances? Probability and Uncertainty in Statistics

Explore probability, uncertainty, and statistical significance in data analysis. Learn to interpret findings, conduct hypothesis tests, and understand regression analysis for informed decision-making.

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

Linear Algebra: Orthogonality and Diagonalization

Explore orthogonality, diagonalization, and symmetric matrices, gaining skills applicable to AI and machine learning. Develop a strong foundation for advanced studies in data science and mathematics.

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

Calculus through Data & Modeling: Applying Differentiation

Apply differentiation to optimize functions, estimate complex equations, and solve real-world problems in data analysis, machine learning, and business through linear approximations and multivariable calculus techniques.

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

Calculus through Data & Modelling: Techniques of Integration

Explore multivariable integration, vector functions, and numerical techniques. Extend calculus concepts to higher dimensions and real-world applications through data analysis and modeling.

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

Infectious Disease Modeling in Practice

Explore practical applications of mathematical modeling for infectious diseases, covering model principles, data integration, and use cases for control strategies, transmission rate analysis, and forecasting.

• Coursera
• 4 hours 22 minutes
• Self-Paced
• Paid Course

Black Agricultural Solutions to Food Apartheid: A Teach-Out

Explore Black agricultural solutions to food apartheid, focusing on ancestral connections, food sovereignty, and community resilience. Gain insights into spiritual relationships with land and practical urban farming techniques.

• Coursera
• 5 hours 27 minutes
• Self-Paced
• Paid Course

Neuroscience Methods

Master cutting-edge neuroscience methods, from neuroimaging and fNIRS to eye tracking and biometric systems. Gain practical skills in data collection, analysis, and research design for understanding cognitive and emotional processes.

• Coursera
• 15 hours 4 minutes
• Self-Paced
• Paid Course

Foundations of Probability and Random Variables

Master fundamental probability concepts and random variable analysis while gaining practical R programming skills for data science and statistical modeling applications.

• Coursera
• 2 days 1 hour 8 minutes
• Self-Paced
• Paid Course

Calculus through Data & Modelling: Integration Applications

Explore calculus applications through data and modeling, focusing on integration techniques for real-world problem-solving in areas like physics, economics, and geometry.

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

Career Certificate

Statistical Methods for Computer Science

Master advanced probability and statistical modeling techniques for data analysis, from fundamental concepts to computational methods, using R programming for real-world applications.

• Coursera
• 12 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 3 courses

Introduction to Uncertainty Quantification

Master the fundamentals of Uncertainty Quantification through probability theory, uncertainty propagation, surrogate modeling, reliability analysis, and Bayesian methods for mathematical and engineering systems.

• Coursera
• 1 day 5 hours 57 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