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Mathematics I

Code: 105037
Credits: 6
2026/2027
Degree programme Type Course
Chemistry FB 1

Contact lecturer

Name :
Juan Carlos Cantero Guardeño
Email :
juancarlos.cantero@uab.cat

Teaching staff

Alberto Debernardi Pinos
Juan Carlos Cantero Guardeño
Maria Doris Potosí Rosero

Group languages

You can consult this information at the end of the document.

Prerequisites

It is advisable to master the mathematical content that allows you to pass the Mathematics exam for the PAU without any problems. In particular, students are expected to be familiar with and skilfully perform the following: (i) agility in performing algebraic manipulations, (ii) discussion of systems of linear equations and solving them where possible, (iii) calculation of derivatives, (iv) calculation of primitives and definite integrals. Students who are having difficulties with these items may (and should) consult their tutor at the beginning of the course to receive guidance.



Objectives

This course consists of a brief introduction to complex numbers, linear algebra and differential equations.

The objectives of the course are:

(i) Understand the basics in each of these parts. These concepts include both the definitions of the mathematical objects that are introduced and their interrelation.

(ii) To be able to apply the concepts studied coherently to the approach and resolution of problems.

(iii) Acquire skills in mathematical writing and in calculus.

Learning outcomes

  • CM04 (Propose the optimal mathematical tools for solving problems in the field of Chemistry.) Propose the optimal mathematical tools for solving problems in the field of Chemistry.
  • CM05 (Solve real, basic mathematical problems applied to chemistry and, to a lesser extent, to other scientific fields.) Solve real, basic mathematical problems applied to chemistry and, to a lesser extent, to other scientific fields.
  • KM04 (Identify the presence of underlying mathematics in science, with special emphasis on chemistry, taking into account analytical thinking, abstraction, and logical and rigorous reasoning.) Identify the presence of underlying mathematics in science, with special emphasis on chemistry, taking into account analytical thinking, abstraction, and logical and rigorous reasoning.
  • KM05 (Identify elementary mathematical models and tools for calculus, linear algebra, and differential equations.) Identify elementary mathematical models and tools for calculus, linear algebra, and differential equations.
  • KM06 (Describe the concepts of numerical methods: precision, discretisation, numerical error, conditioning and normalisation for use in solving physical problems.) Describe the concepts of numerical methods: precision, discretisation, numerical error, conditioning and normalisation for use in solving physical problems.
  • SM05 (Analyse the mathematical nature of certain chemical phenomena by abstracting essential variables and formulating mathematical models to describe them.) Analyse the mathematical nature of certain chemical phenomena by abstracting essential variables and formulating mathematical models to describe them.
  • SM06 (Use mathematical calculations to solve simple problems in the field of Chemistry and, to a lesser extent, in other scientific fields.) Use mathematical calculations to solve simple problems in the field of Chemistry and, to a lesser extent, in other scientific fields.
  • SM07 (In the field of Chemistry, use graphic and numerical methods in the exploration, description and interpretation of mathematical data.) In the field of Chemistry, use graphic and numerical methods in the exploration, description and interpretation of mathematical data.

Contents

(1) Complex numbers

- Definition and elementary operations.

- Polar form.

- n-th root of complex numbers.

- Factoritzation of polynomials.

(2) Linear algebra

- Sistems of linear equations. The Gauss methode.

- Matrices and determinants.

- Vectorial spaces: linear dependence, basis and dimension.

- Eigenvalues and eigenvectors. Diagonalisation.



(3) Differential and Integral calculus


- Functions. Derivative. Graphical representation.


. Primitives. Fundamental calculus theorem.

- Change of  variable. Integration by  parts.

- Primitives of rational functions.


(4) Diferential equations of first order

- Diferential equations: Definition and geometrical interpretatioon. Examples.

- Equations of separated variables.

- Linear equations of first order.

- Linear equations of greatest order.

- Linear equations of second order with constants coefficients.

-  Systems of diferential equations.

Learning activities and methodology

Title Hours ECTS Learning outcomes
Problem solving 40 1.6
Problems 22 0.88
Theory 25 1
Tutorial 6 0.24
Seminars 3 0.12
Study 42 1.68

Lectures where definitions, initial results and examples are presented. It is necessary to study the theoretical results covered in these sessions, as they will form the core content of the assessment tests.


Problem-solving sessions where these examples are explored in depth, and where students are expected to attempt to solve the problems independently before attending the session.


To achieve a positive result in this module, it is highly recommended to follow the following steps when preparing for your studies:


(i) Read the theory notes posted on the Virtual Campus beforehand. Identify any concepts that you may find more difficult.


(ii) Attend the corresponding theory sessions. Students are expected to participate actively, asking any questions they may have at all times. All questions are welcome (and encouraged) during the theory sessions.


(iii) Reading and attempting to solve the corresponding problems. It is strongly recommended to first make an active, individual effort to solve the problems. In a second iteration, working in groups to solve the problems is a good idea. Finally, once you have attempted them individually and as a group, you may resort to (though it is by no means essential) AI tools for assistance. It is important not to alter this order of operations and not to start by using this tool directly. In fact, for this module, it is recommended to avoid using generative Artificial Intelligence tools, as current models tend to agree with and confirm the user's hypotheses, which can create a false sense of mastery over the subject matter.


(iv) Attendance at the problem-solving sessions corresponding to this block. Active participation from students is expected, asking any questions they may have at all times. All questions are welcome (and encouraged) during the problem-solving sessions.



Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
final exam 50% 4 0.16 CM04, CM05, KM04, KM05, KM06, SM05, SM06, SM07
midterm exam 40% 4 0.16 CM04, CM05, KM04, KM05, KM06, SM05, SM06, SM07
Seminar qualification 10% 4 0.16 CM04, KM05, SM06, SM07

During the course, 3 assessment components will be evaluated:

  1. During problem-solving classes and/or seminars, the content of certain sessions will be assessed. These sessions will be announced sufficiently in advance. This results in a grade S.
  2. A midterm exam will be held approximately halfway through the semester, resulting in a grade P1.

A second midterm exam covering the course content not assessed in the first midterm will be held at the end of the semester, resulting in a grade P2. If min(P1, P2) < 3.5, the student must take the resit examination. Otherwise, the final grade is calculated using the formula N1 = 0.1·S + 0.4·P1 + 0.5·P2. If N1 < 5, the student must take the resit examination. If N1 ≥ 5, the student passes the course with a final grade of N1.


For the resit examination, four possible cases are distinguished:


(a) If max(P1, P2) < 3.5, the student must take a comprehensive resit examination, resulting in a grade R. In this case, the final course grade will be N = 0.1·S + 0.9·R.


(b) If condition (a) is not satisfied and P1 < 3.5, the student has two options and must choose one on the day of the examination.


Option (b1): Take a resit examination for the first midterm, resulting in a grade R1, and obtain a final course grade of N = 0.1·S + 0.4·R1 + 0.5·P2.


Option (b2): Take a full resit examination, resulting in a grade R, and obtain a final course grade of N = 0.1·S + 0.9·R.


(c) If neither condition (a) nor (b) is satisfied and P2 < 3.5, the student has two options and must choose one on the day of the examination.


Option (c1): take a resit examination for the second midterm, resulting in a grade R2, and obtain a final course grade N = 0.1·S + 0.4·P1 + 0.5·R2.


Option (c2): take a full resit examination, resulting in a grade R, and obtain a final course grade N = 0.1·S + 0.9·R.


(d) If neither condition (a), (b), nor (c) is satisfied (that is, P1 ≥ 3.5 and P2 ≥ 3.5, but N1 < 5), the student has three options and must choose one on the day of the examination.


Option (d1): take a resit examination for the first midterm, resulting in a grade R1, and obtain a final course grade N = 0.1·S + 0.4·R1 + 0.5·P2.


Option (d2): take a resit examination for the second midterm, resulting in a grade R2, and obtain a final course grade N = 0.1·S + 0.4·P1 + 0.5·R2.


Option (d3): take a full resit examination, resulting in a grade R, and obtain a final course grade N = 0.1·S + 0.9·R.


In the case of partial resits, the resit grade will only be considered if a minimum score of 3.5 is obtained in the resit component. Thus, in cases (b1) and (d1) , R1 > 3.5 is required, and in cases (c1) and (d2), R2 > 3.5 is required. If this minimum score is not achieved, the course will be considered failed with a final grade of min(N, 4.5).



Students who have opted for the single-assessment modality must complete an oral theory examination and a final written examination covering the entire course syllabus. These will take place on the same day that continuous-assessment students take the second midterm examination. The student’s final grade will be the average of these two assessments.


Students will be considered Not Assessed if they attend only one or none of the assessment activities.


Any irregularity committed during any of the assessment activities described above (academic fraud, plagiarism, or improper use of AI) will result in a grade of 0 for that assessment activity. If multiple irregularities occur across different assessment activities, the final grade for the course will be 0. In addition, disciplinary proceedings may be initiated against any student who commits such irregularities.

Bibliography

M. Moreno, Una introducción al álgebra lineal elemental, UAB, 1990. Codi biblioteca de Ciències: 15-M-9; 512.64 Mor.

S. I. Grossman, Álgebra lineal, McGraw Hill, 1996. Codi biblioteca de Ciències: 15- G.19; 512.64 Gro.

F. Carreras, M. Dalmau, F. Albeniz, M. Moreno, Ecuaciones diferenciales, UAB, 1987. Codi biblioteca de Ciències: 34-E-16; 34-E-17; 517.9 Ecu.

Dennis G. Zill, Ecuaciones diferencials con aplicaciones de modelado, Thomson Editors, 1997. Codi biblioteca de Ciències: 34-Z-5; 517.9 Zil.

C. Neuhauser, Matemáticas para Ciencias, Prentice Hall, 2004, Codi biblioteca de Ciències: 00-N-04

Software

Not applicable

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(TE) Theory 1 Catalan/Spanish first semester morning-mixed
(PAUL) Classroom practices 1 Catalan/Spanish first semester morning-mixed
(SEM) Seminars 1 Catalan/Spanish first semester morning-mixed
(TE) Theory 2 Catalan/Spanish first semester afternoon
(PAUL) Classroom practices 2 Catalan/Spanish first semester morning-mixed
(SEM) Seminars 2 Catalan/Spanish first semester morning-mixed
(PAUL) Classroom practices 3 Catalan/Spanish first semester afternoon
(SEM) Seminars 3 Catalan/Spanish first semester afternoon
(PAUL) Classroom practices 4 Catalan/Spanish first semester afternoon
(SEM) Seminars 4 Catalan/Spanish first semester afternoon