i want two courses linear algebra(3361) and discrete structure maths(3362) to be done , if you are well confident to earn atleast a B grade in each one , then only contact me . i am attaching course details of both

Name and Number: Linear Algebra – Math 3361

Instructor: Ricardo Teixeira

Term: Spring 2, from Mar 21 to May 13

Office Phone: (361) 570.4206

Email: teixeirar@uhv.edu (preferred method of communication)

Course Description: Vector spaces, linear transformation, representation of linear

transformations by matrices, matrix algebra, determinants, systems of linear equations and

eigenvalue problems. Applications to 2D and 3D geometric modeling, computer graphics, and

digital game programming.

Prerequisites: MATH 2414 or MATH 3362.

Required Textbook: Webassign access for Linear Algebra: A Modern

Introduction, 4/e, by David Poole, Cengage Learning

Optional Material: You may want to also buy the physical copy of the

textbook ISBN-13: 978-8131530245

Webassign: You must have access to a computer and a fast internet

connection. You also must have the textbook (at least the e-book) and

access Webassign regularly. Computer or internet problems will not be

valid justifications for asking for extensions on assignments. Access it via

www.webassign.net.

Class key:

uhv 0155 1081

Course Map:

Module 1: Vectors (Chapter 1)

March 21 – March 26

1.0. Introduction: The Racetrack Game

1.1. The Geometry and Algebra of Vectors

1.2. Length and Angle: The Dot Product

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1.3. Lines and Planes

1.4. Applications

Module 2: System of Linear Equations (Chapter 2)

March 27 – April 2

2.0. Introduction: Triviality

2.1. Introduction to Systems of Linear Equations

2.2. Direct Methods for Solving Linear Systems

2.3. Spanning Sets and Linear Independence

2.4. Applications

Module 3: Matrices (Chapter 3)

April 3 – April 9

3.0. Introduction: Matrices in Action

3.1. Matrix Operations

3.2. Matrix Algebra

3.3. The Inverse of a Matrix

3.4. The LU Factorization

3.5. Subspaces, Basis, Dimension, and Rank

3.6. Introduction to Linear Transformations

3.7. Applications

Module 4: Eigenvalues and Eigenvectors (Chapter 4)

April 10 – April 16

4.0. Introduction: A Dynamical System on Graphs

4.1. Introduction to Eigenvalues and Eigenvectors

4.2. Determinants

4.3. Eigenvalues and Eigenvectors of n×n Matrices

4.4. Similarity and Diagonalization

4.5. Iterative Methods for Computing Eigenvalues

4.6. Applications and the Perron-Frobenius Theorem

Module 5: Orthogonality (Chapter 5)

April 17 – April 23

5.0. Introduction: Shadows on a Wall

5.1. Orthogonality in ℝn

5.2. Orthogonal Complements and Orthogonal Projections

5.3. The Gram-Schmidt Process and the QR Factorization

5.4. Orthogonal Diagonalization of Symmetric Matrices

5.5. Applications

Module 6: Vector Scpaces (Chapter 6)

April 24 – April 30

6.0. Introduction: Fibonacci in (Vector) Space

6.1. Vector Spaces and Subspaces

6.2. Linear Independence, Basis, and Dimension

6.3. Change of Basis

6.4. Linear Transformations

6.5

Name and Number: Discrete Structures – Math 3362

Instructor: Ricardo Teixeira

Term: Spring 2, from Mar 21 to May 13

Office Phone: (361) 570.4206

Email: teixeirar@uhv.edu (preferred method of communication)

Course Description: Mappings, relations, recurrence, logic, Boolean algebras, graphs,

induction, proofs, languages, state machines, history of artificial intelligence, Turing test, and

applications of these areas.

Prerequisites: MATH 1324 or MATH 2413.

Required Material: Webassign access for “Essentials of Discrete

Mathematics 4th Edition” By David J. Hunter.

Optional Material: The textbook ISBN: 1284184765.

Webassign: You must have access to a computer and a fast internet

connection. You also must have the textbook (at least the e-book) and

access Webassign regularly. Computer or internet problems will not be

valid justifications for asking for extensions on assignments. Access it

via www.webassign.net.

Class key:

uhv 4029 0369

The Big Idea:

1. Understand discrete mathematics ideas.

2. Apply discrete mathematics ideas to algorithms and other areas.

Course Objectives:

1. Students will be able to use logical notation and perform logical proofs.

2. Students will define relational thinking ideas such as graphs, sets, functions,

equivalences, and partial ordering.

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3. Students will apply recursive functions and solve recurrence relations.

4. Students will apply basic and advanced principles of counting and calculate discrete

probabilities.

5. Students will describe useful standard library functions, create functions, declare

parameters, and analyze algorithm complexity.

Course Map:

Module 1: Introduction to Course, and Intro to Logical Thinking (Chapter 1)

March 21 – March 26

MO1: Understand basic logic terminology

MO2: Describe truth tables

MO3: Describe proof sequences

Module 2: Logical Thinking (Chapter 1)

March 27 – April 2

MO1: Understand the duality of text and quantifiers in logic

MO2: Create and identify counterexamples

MO3: Choose and develop the most adequate method of proof in different cases

Module 3: Relational Thinking (Chapter 2)

April 3 – April 9

MO1: Understand graphs, sets and functions

MO2: Identify equivalence relations through graphs

MO3: Understand modular arithmetic

Module 4: Recursive Thinking (Chapter 3)

April 10 – April 16

MO1: Understand and model recurrence relations

MO2: Develop closed form solutions

MO3: Write recursive examples in geometry

MO4: Develop proofs through induction

MO5: Apply recursion to data structures

Module 5: Quantitative Thinking (Chapter 4)

April 17 – April 23

MO1: Define basic counting principles

MO2: Understand and distinguish permutations and combinations

MO3: Understand and apply the pigeonhole principle

MO4: Calculate expected value and conditional prob

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