Math for Data science,Data analysis and Machine Learning

Learn Math essentials for Data science,Data analysis,Machine Learning and Artificial intelligence

What you'll learn
Learn the foundational concepts of Linear Algebra
Learn the foundational concepts of statistics
Learn the foundational concepts of Geometry
Learn the foundational concepts of Calculus
Application of key mathematical topics

Requirements
Basic knowledge of Math will be needed to finish the course

Description
In this course, we will learn Math essentials for Data science,Data analysis and Machine Learning.  We will also discuss the importance of Linear Algebra,Statistics and Probability,Calculus and Geometry in these technological areas. Since data science is studied by both the engineers and commerce students ,this course is designed in such a way that it is useful for both beginners as well as for advanced level. The lessons of the course is also beneficial for the students of Computer science /artificial intelligence and those learning Python programming.Here, this course covers the following areas :Importance of Linear AlgebraTypes of MatricesAddition of Matrices and its PropertiesMatrix multiplication and its PropertiesProperties of Transpose of MatricesHermitian and Skew Hermitian MatricesDeterminants ; IntroductionMinors and Co factors in a DeterminantProperties of DeterminantsDifferentiation of a DeterminantRank of a MatrixEchelon form and its PropertiesEigenvalues and EigenvectorsGaussian Elimination Method for finding out solution of linear equationsCayley Hamilton TheoremImportance of Statistics for Data ScienceStatistics : An IntroductionStatistical Data and its measurement scalesClassification of DataMeasures of Central TendencyMeasures of Dispersion: Range, Mean Deviation, Std. Deviation & Quartile DeviationBasic Concepts of ProbabilitySample Space and Verbal description & Equivalent Set NotationsTypes of Events and Addition Theorem of ProbabilityConditional ProbabilityTotal Probability TheoremBaye's TheoremImportance of Calculus for Data science Basic Concepts : Functions, Limits and ContinuityDerivative of a Function and Formulae of DifferentiationDifferentiation of functions in Parametric FormRolle;s TheoremLagrange's Mean Value TheoremAverage and Marginal ConceptsConcepts of Maxima and MinimaElasticity : Price elasticity of supply and demandImportance of Euclidean GeometryIntroduction to GeometrySome useful Terms,Concepts,Results and FormulaeSet Theory : Definition and its representationType of SetsSubset,Power set and Universal setIntervals as subset of 'R'Venn DiagramsLaws of Algebra of SetsImportant formulae of no. of elements in setsBasic Concepts of FunctionsGraphs of real valued functionsGraphs of Exponential , Logarithmic and Reciprocal FunctionsEach of the above topics has a simple explanation of concepts and supported by selected examples. I am sure that this course will be create a strong platform for students and those who are planning for appearing in competitive tests and studying higher Mathematics .You will also get a good support in Q&A section . It is also planned that based on your feed back, new course materials will be added to the course. Hope the course will develop better understanding and boost the self confidence of the students.Waiting for you inside the course! So hurry up and Join now !!

Who this course is for:
Students of engineering, data science, machine learning and python programming