Essential Mathematics and Statistics for Machine Learning with MATLAB
SkillDynamo’s Essential Mathematics and Statistics for Machine Learning with MATLAB course builds the mathematical foundation needed to understand data, optimization, probability, model fitting, and predictive algorithms.
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-by SkillDynamo
- 0 Students
- Last updated
Course Description
SkillDynamo’s Essential Mathematics and Statistics for Machine Learning with MATLAB course builds the mathematical foundation needed to understand data, optimization, probability, model fitting, and predictive algorithms.
What You Will Learn
- Use vectors, matrices, functions, and calculus concepts in MATLAB.
- Summarize data using descriptive statistics and visual analysis.
- Apply probability distributions, sampling, and hypothesis-testing concepts.
- Connect mathematical foundations with regression, classification, and optimization.
Who Should Attend
Beginners in data science, machine learning, analytics, engineering, and technical research.
Recommended Prerequisites
Basic school-level algebra is recommended. No advanced statistics or machine-learning experience is required.
SkillDynamo Training Approach
This independently rewritten course combines explanations, guided MATLAB exercises,
data or model validation, troubleshooting, and practical project work. Review toolbox availability
and release-specific features in the MATLAB environment used for delivery before publishing.
Curriculum
- 1 Section
- 4 Lessons
- 16 Hours
- Course Curriculum4 Items
SkillDynamo Expert Team
SkillDynamo Expert Team
The SkillDynamo Expert Team delivers practical training in MATLAB programming, data analysis,
machine learning, deep learning, signal and image processing, scientific computing, control systems,
Simulink, and engineering simulation.
- Hands-on MATLAB scripts, functions, apps, and modeling exercises
- Structured data, AI, signal, control, and simulation workflows
- Practical validation, troubleshooting, and project guidance
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