Foundational Mathematics for Data Science Arabic

This course "Foundational Mathematics for Data Science" provides a comprehensive understanding of linear algebra, statistics, and probability essential for those delving into the realms of machine learning and data science. It stands out as a unique resource in Arabic, offering interactive, application-based training with thorough explanations, catering to beginners' levels to achieve an excellent grasp of the subjects. Suitable for novices without prerequisites, this course caters to individuals interested in AI, its associated mathematics, data analysts, data scientists, and AI engineers.

What you will learn:Linear Algebra:Introduction and ImportanceSystem of Linear EquationsVectors and OperationsVector NormDot ProductMatrices and Matrix OperationsVector SpacesLinear CombinationsVector SpansVectors Linear IndependenceBasis of SpaceLinear TransformationDeterminantSystem of Linear Equation SolutionsGauss-Jordan EliminationInverseEigenvalues and EigenvectorsPCA (Principal Component Analysis)Probability & Statistics:Importance and RelevanceProbability vs. StatisticsEmpirical and Theoretical ProbabilityJoint, Marginal, and Conditional Probability DistributionRandom ExperimentRandom VariablesStatisticsSampling MethodsNumerical Variables and Visualization TechniquesStatistical ToolsCategorical Variables and Visualization TechniquesProbability DistributionsWhether you're an AI enthusiast, developer, student, or data scientist, this course will empower you with the foundational knowledge of mathematics needed for data science. Join us now and embark on an enriching learning journey that will set you on the path in the AI field.

Enroll today.