Informatics for Science and Engineering D
The fundamental components of a computer.
The tools of a software development system.
The essential constructions of an imperative programming language.
Some fundamental notions of relational databases.
Some basic concepts involved in the World Wide Web.
Decompose a problem into simpler problems.
Design an algorithm for solving a simple problem.
Write a program, making a correct use of the basic constructions of an imperative programming language.
Test a program in a given programming environment.
State a very simple SQL query.
Access resources available in the network inside a program.
Ability to do a programming project.
Skills in time management.
Teresa Isabel Lopes Romão
Weekly - 4
Total - 59
This unit has no access requirements.
Allen B. Downey. Think Python: How to Think Like a Computer Scientist. PDF and HTML at http://greenteapress.com/wp/think-python-2e/
Charles Severance. Python for Everybody: Exploring Data Using Python 3. PDF and HTML at https://www.py4e.com/book.php. This is based on the previous reference, containing chapters about Internet and Data Bases. There is also a version (trinket.io) were you can change and execute the examples inside the book.
Notes by Prof. Ludwig Kripahl (http://iceb.ssdi.di.fct.unl.pt/1920/files/ICEB_notes.pdf)
There are two hours of lectures and a lab session of two hours each week.
Lectures are problem-driven. They start with a concrete problem, which motivates the presentation of some computer systems topic, some data type or some programming language construct, and end with the complete source code of a program that solves it.
In the lab classes, students design, implement and test programs for solving simple problems in Science and Engineering fields.
The assessment consists of two components: the laboratory component and the theoretical-practical component.
***** Laboratory Component and Frequency *****
The laboratory component consists of three exercises and one practical work, carried out in a group of two students (or individually, in justified cases). The practical work will be done mostly outside of class.
The evaluation of the works is done individually, during the corresponding tests, which will include a group of questions related to the respective works. The evaluation of these groups of questions will affect the final grade given to the works, but not the test grades.
The grade of the laboratory component (CompL) is obtained as follows:
• compL = 0,2 Q1 + 0,2 Q2 + 0,6 TP (where Q1 and Q2 are the two best results of the three exercises).
To obtain frequency it is necessary that CompL ≥ 8.0.
***** Theoretical-Practical Component *****
The theoretical-practical component consists of two tests (during class time) or an exam (at the time of recourse). The three tests are individual, written and without consultation.
The grade of the theoretical-practical component (CompTP) is the arithmetic mean of the test scores (T1 and T2) or the exam grade (Ex):
• CompTP = max (0.5 T1 + 0.5 T2 , Ex).
To obtain approval, CompTP ≥ 8.0 is required.
During the individual written assessment tests or exams, students are not allowed to consult any material, nor use any electronic device. Failure to comply with this rule leads to the automatic fail in the assessment test or exam.
***** Final grade *****
The final grade (NF) of students with frequency is calculated as follows:
• NF = CompTP, if CompTP < 8.0;
• NF = 0.3 CompL + 0.7 CompTP, if CompTP ≥ 8.0 .
All grades are rounded to the nearest decimal, on a scale from 0 to 20, except for the final grade (NF) which is rounded to the nearest integer.
***** Rankings Obtained in Previous Years *****
Students who have attended UC since the year 2018/19 (when the Python language was used) can keep this grade.
If they want to keep the previous grade, they should not enroll in practical classes and this grade corresponds to CompL above. If they enroll in practical classes, the CompL grade will be the grade obtained this year (2022/23).
Introduction: Problems, algorithms, programs, and computers. Goals and components of computer systems. Program execution. The interpreter.
Fundamental Concepts of Programming examplified in Python:
Constants, variables and expressions. Numbers and strings. Predefined functions. Assignment statement and sequence of statements.
Levels of abstraction in problem-solving. Functions. Source code files. Program life cycle. Kinds of error. Unit testing.
FOR loops. Vectors. The IF statement. Relational and logical operators. Matrices. Graphics. WHILE loops. File systems. Binary and ASCII files. Dictionaries.
Networks and communication protocols. The World Wide Web.
Introduction to databases: the relational model, relations, some basic SQL queries.
Simulation of continuous models.