Final Exam: Introduction to Math
Math | Beginner
- 1 Video | 32s
- Includes Assessment
- Earns a Badge
Final Exam: Introduction to Math will test your knowledge and application of the topics presented throughout the Introduction to Math track of the Skillsoft Aspire Essential Math for Data Science Journey.
WHAT YOU WILL LEARN
perform union and intersection operations on setsrecognize the differences between discrete and continuous data and outline topics in discrete mathematicscreate and work with sets in Python, perform checks for subsets and supersetscreate and work with sets in Pythonmodel entities and relationships in the real-world using graphsrecognize the different types of graphs, their characteristics, and use casesassociate attributes with the graph, individual nodes, and individual edgescompute the shortest path and a minimum spanning tree for a graphcompute the minimum spanning tree and the shortest path for a graphperform topological sorting in a directed acyclic graphcreate directed graphs using NetworkXrecall the assumptions and benefits of integer optimization modelsmodel problems using objectives, decision variables, and constraintssolve the linear programming problem graphicallydetermine the optimal solution from feasible solutionslist the steps in the Simplex method to solve linear programming problemssolve minimization problems using the SciPy librarysolve linear programming problems using the Pulp libraryrecognize the assumptions and benefits of integer optimization modelsuse LP relaxation to find a starting point for the integer programming solutionformulate the integer programming model for Becca Luxury Goodssolve the manufacturing and distribution problem using Pulpformulate the integer programming model for a capital budgeting problemgain a basic understanding of calculus and describe differentiation and derivativesdescribe differentiation and derivativesuse built-in functions to compute derivativesoutline how to compute the slope at a point by exploring the geometric definition of derivativesuse derivatives in real-world scenariosoutline how partial derivatives workcompute derivatives of linearly changing functions using built-in functions
outline derivatives and slopecreate partial derivatives with multiple independent variablescompute the velocity of a moving particledefine the integral as the limit of a sum and as the area under a curvedifferentiate between definite and indefinite integralscompute integrals of quadratic and polynomial functionscompute integrals from first principlesframe integration as inverse operationscreate a matrix and perform matrix operationscompute determinants and transpose matricesperform matrix additionperform matrix multiplicationrecognize properties of matricesidentify and work with diagonal and zero matricescompute the inverse of an invertible matrixcreate matrices using SciPymathematically define matrix decompositionrecognize several types of matrix operationsperform LU decompositionmathematically define QR and Cholesky decompositionperform QR decompositioninstall libraries in Pythonmathematically define eigenvectors and eigen valuesexplore properties of eigenvalues and eigenvectorscompute eigenvalues and eigenvectors of a matrixderive the characteristic equationdifferentiate between eigen decomposition and Singular Value Decomposition (SVD)import an image to perform SVDperform Singular Value Decomposition (SVD) on a matrixsimplify an image with SVD
IN THIS COURSE
1.Introduction to Math33sUP NEXT
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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