Mathematics of Artificial Intelligence
Issued by
Virginia Commonwealth University
Earners have the mathematical skills in linear algebra, calculus, probability, optimization, and discrete mathematics to effectively analyze artificial intelligence (AI) and machine learning. They have the quantitative knowledge to understand how modern AI systems are built, optimized, and interpreted. Earners can critically evaluate AI models, understand how to apply frameworks, and the underlying mechanics of algorithms.
- Type Validation
- Level Intermediate
- Time Months
Skills
- AI Ethics
- Artificial General Intelligence
- Artificial Intelligence (AI)
- Artificial Intelligence Applications
- Attention Mechanisms
- Calculus
- Deep Learning
- General Mathematics
- K-Means Clustering
- K-nearest Neighbors Algorithm (k-NN)
- Linear Algebra
- Machine Learning (ML)
- Mathematical Modeling
- Neural Networks
- Optimization
- Principal Component Analysis (PCA)
- Probability
- Regression Analysis
- RNNs
Earning Criteria
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Complete both Math 310 Linear Algebra (3 cr) and Math 370 Mathematical Foundations for Artificial Intelligence (3 cr) with a C or better.