Course Code: INFO 105 • Study year: I • Academic Year: 2024-2025
Domain: Computer Science • Field of study: Computer Science
Type of course: Compulsory
Language of instruction: Romanian
Erasmus Language of instruction: English
Name of lecturer: Ioan Lucian Popa
Seminar tutor: Ioan Lucian Popa
Form of education Full-time
Form of instruction: Class
Number of teaching hours per semester: 56
Number of teaching hours per week: 4
Semester: Autumn
Form of receiving a credit for a course: Grade
Number of ECTS credits allocated 6

Course aims:

After browsing the course, the students will gain skills in the use of mathematical analysis for transposition of problems in various programming languages.
So the discipline contributes to the formation of some general skills specific for the study domain.
-So the discipline contributes to the formation of some general skills specific for the study domain.

Course Entry Requirements:


Course contents:

1.Strings. 1.1 Strings applications, real numbers strings, strings in metric spaces. 1.2 Calculation of string limits 2. Numerical series. 2.1 Applications to numerical series and convergence criteria for series with random terms. 2.2 Applications to absolute convergent series, semiconvergent series, and series with positive terms. 3. Functions between metrical spaces. 3.1 Applications regarding function calculation of the limits in one point. 3.2 Continuity of functions between metric spaces. 4. Integration of real functions. 4.1 Calculation of some integrals out of real functions. 4.2 Applications to calculate defined integrals. 5. Strings and series of functions 5.1 Applications of strings and series of functions. 5.2 Applications of rise series and Taylor series. 6. Functions derivations of more than one variable 6.1 Applications to function derivations of more than one variable, partial derivations. 6.2 Applications to functions differentials of more than one variable and functions extremes of more than one variables. 6.3 Conditioned extremes. 7. Basic knowledge regarding integrals 7.1 Improper integrals applications. 7.2 Applications of integrals with parameters. 7.3 Applications of Eulerian integrals and double integrals

Teaching methods:

Lecture, discussion, exemplification.

Learning outcomes:

In order to obtain credits for this discipline the student have to know how to work with elementary mathematical analysis notions, which are necessary in the basic theoretical bases of computer science and formal models.

Learning outcomes verification and assessment criteria:

Final evaluation – 50%; continuous assessment – 50%.

Recommended reading:

Breaz D., Acu, M., Mathematic Analysis, Editura Risoprint, Cluj Napoca, 2008, -.
Mangatiana A. Robdera, A Concise Approach to Mathematical Analysis, Springer, -, 2003, -.
Graeme L. Cohen, A course in modern analysis and its applications, Cambridge University Press, -, 2003, -.