Programming Languages I
| Áreas Científicas |
| Classificação |
Área Científica |
| OFICIAL |
Informática |
Ocorrência: 2021/2022 - 2S
Ciclos de Estudo/Cursos
| Sigla |
Nº de Estudantes |
Plano de Estudos |
Anos Curriculares |
Créditos UCN |
Créditos ECTS |
Horas de Contacto |
Horas Totais |
| BINF |
31 |
Study Plan |
1 |
- |
5 |
67,5 |
135 |
Docência - Responsabilidades
Língua de trabalho
Portuguese
Objetivos
This course has as main objectives to offer the student a global vision of the programming paradigm.
At the end of the course unit the learner is expected to be able to:
- Notion of algorithm as the formalisation of the solution to a well-defined problem into a sequence of elementary actions.
- Analyse a given algorithm and predict the final result of its execution;
- Design algorithms in natural language and pseudocode.
- Understand and know: computer programming as a way to describe algorithms in a formal language that can be executed in a general-purpose computer;
- elementary principles of programming: variables, decision instructions, cycle instructions, lists and arrays, the traditional cycle of developing computer programs:
- design, programming and testing.
- Apply the knowledge of these basic principles to phyton programming language.
- Be able to translate a given algorithm into a complete program.
- Being able to solve a given problem by designing, programming and testing it.
Resultados de aprendizagem e competências
Not applicable
Modo de trabalho
Presencial
Programa
The general-purpose computer and its components
Algorithms: Definition and history of algorithms. Examples of simple algorithms. How to describe an algorithm Introduction to programming languages paradigms Elements of programming languages: Variables of elementary types. Expressions and allocation of values. Instruction execution flow. Decision instructions. Cycle instructions. Lists and arrays Classical algorithms: Search algorithms. Sorting algorithms Input and output of data.
Bibliografia Obrigatória
Pavão martins; PROGRAMAÇÃO EM PYTHON. INTRODUÇÃO À PROGRAMAÇÃO UTILIZANDO MÚLTIPLOS PARADIGMAS, IST, 2020
Métodos de ensino e atividades de aprendizagem
The students will have a set of sheets, from Moodle, to consolidate learning, some solved in class and others done on their own, with subsequent supervision of the teacher.
Software
https://www.anaconda.com/open-source
Tipo de avaliação
Distributed evaluation with final exam
Componentes de Avaliação
| Designation |
Peso (%) |
| Teste |
50,00 |
| Trabalho laboratorial |
50,00 |
| Total: |
100,00 |
Componentes de Ocupação
| Designation |
Tempo (Horas) |
| Estudo autónomo |
75,00 |
| Frequência das aulas |
30,00 |
| Trabalho laboratorial |
30,00 |
| Total: |
135,00 |
Obtenção de frequência
Not applicable
Fórmula de cálculo da classificação final
final classification by continuous evaluation: 30% 1st Test + 30% 2nd Test + 40% laboratory evaluation
final classification by Exam: 100 % Exam
Melhoria de classificação
Passing students will only be able to improve in the appeal season.
Observações
- Plagiarism in any evaluation (test, exam and project) will be penalized with its cancellation and forwarded to the competent bodies for disciplinary measures.
- In the case of remote assessments, an oral discussion may be requested for validation of skills, with impact on the grade of that assessment.