Algebra

Code:

EQ0058

Acronym:

A

Keywords
Classification	Keyword
OFICIAL	Physical Sciences (Mathematics)

Instance: 2020/2021 - 1S

Active?	Yes
Responsible unit:	Department of Chemical and Biological Engineering
Course/CS Responsible:	Master in Chemical Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIEQ	88	Syllabus	1	-	5	49	135

Teaching language

Portuguese

Objectives

This course aims to endow students with fundamental knowledge on Algebra (vectors, linear spaces, matrices, determiners, systems of linear equations) as is detailed is in the program of the course.

Learning outcomes and competences

Knowledge about basic principles of Algebra as described in the course program.

Working method

Presencial

Program

1. VECTOR ALGEBRA Operations with vectors; Linear dependence of vectors; Scalar product; Line equation; Plane equation; vector product; scalar triple product; repeated products of three or more vectors; distance from point to plane 2. LINEAR SPACES Linear spaces: examples; Sub-spaces; Base and dimension; Linear spaces with inner product 3. MATRIX ALGEBRA Linear transformations and matrices; Operations with matrices; Linear transformations; R2 and R3 linear transformations. 4. DETERMINANTS Definition; Determinants: basic properties; Determinants calculation 5. LINEAR EQUATION SYSTEMS Coefficient matrix and extended matrix; Gaussian elimination; Elementary operations; Equivalent systems; Matrix characteristics; General properties of solution of linear equation systems; Gauss-Jordan algorithm; Homogeneous systems; Linear space (Ax=0 solutions); Non-homogeneous systems; Linear dependence and characteristic; Singular matrices; Cramer’s rule; LU decomposition 6. INVERSE MATRIX AND RELATED MATRICES Inverse matrix: properties; Adjunct matrix; Inverse matrix calculation by the adjunct matrix; Inverse matrix calculation by elementary operations 7. EIGENVALUES AND EIGENVECTORS Characteristic determinant, characteristic polynomial and characteristic equation of a matrix; Determining eigenvalues and its eigenvalues; Eigenvalues: properties; algebraic multiplicity and geometric multiplicity 8. DIAGONALIZATION OF MATRICES Diagonalizing a matrix: procedures

Mandatory literature

João Mendonça; Sebenta de Álgebra, DEQ/FEUP

Complementary Bibliography

Anton, Howard; Elementary linear algebra. ISBN: 0-471-17052-6
José Augusto Trigo Barbosa; Noções sobre matrizes e sistemas de equações lineares. ISBN: 972-752-069-3 972-752-065-0
José Augusto Trigo Barbosa; Noções sobre álgebra linear. ISBN: 978-972-752-142-5
F. Xavier Malcata; Mathematics for Enzyme Reaction Kinetics and Reactor Performance, John Wiley & Sons Ltd., 2020. ISBN: 9781119490319

Teaching methods and learning activities

General theoretical-practical classes are based on the presentation of the themes of the course and examples are given. The practical classes, which are divided in groups, are intended to clarify students’ doubts about the exercises. Students are supposed to solve the exercises before class.

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	90,00
Teste	10,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	60,00
Frequência das aulas	40,00
Total:	100,00

Eligibility for exams

1 - Students cannot exceed ¼ of the classes previously set 2 - Students have to do all micro-tests 3 - Students who were only admitted on the second phase, will be assessed depending on the date that they were admitted Students who are repeating the course, and who were admitted to exams in the previous year, do not need to attend to classes.

Calculation formula of final grade

The final classification (CF) will be calculated by one of the following expressions:

For approval in normal season:
For students attending: CF = MT + 0.10 * 0.45 * 0.45 * T1 + T2
in which
MT - classification in the micro-tests;
T1 and T2 - classification in the 1st and 2nd tests, respectively;


For students with no attendance:
CF = 0.5 * T1 + 0.5 * T2


For approval during the appeal period:
For students attending: CF = 0.10 MT + 0.9 * EF *
in which
MT - classification in the micro-tests;
EF: appeal exam


For students with no attendance:
CF = EF


For improvement:
CF = EF




Note 1 - 6 micro-tests via moodle are scheduled.
Note 2 - To obtain approval, a minimum of 7 values (out of 20) is required in each test.

Examinations or Special Assignments

Not applicable

Special assessment (TE, DA, ...)

Exam

Classification improvement

The marks of micro-tests will not be added to the Final Mark.

Observations

Students are not allowed to use calculators on tests and exams.