Subject Datasheet
Completion requirements
Subject Datasheet
Download PDFI. Subject Specification
1. Basic Data
1.1 Title
Programming Basics
1.2 Code
BMEEOFTBSFC001-00
1.3 Type
Module with associated contact hours
1.4 Contact hours
| Type | Hours/week / (days) |
| Lab | 2 |
1.5 Evaluation
Midterm grade
1.6 Credits
3
1.7 Coordinator
| name | Dr. Ekler Hajnalka |
| academic rank | Assistant professor |
| ekler.hajnalka@emk.bme.hu |
1.8 Department
Department of Photogrammetry and Geoinformatics
1.9 Website
1.10 Language of instruction
english
1.11 Curriculum requirements
Compulsory in the Civil Engineering (BSc) programme
1.12 Prerequisites
1.13 Effective date
1 September 2025
2. Objectives and learning outcomes
2.1 Objectives
The main goal of the course is for students to acquire basic programming knowledge and be able to independently solve simple algorithmic tasks using the Python programming language. We encourage students to develop programming habits that will enable them to work in teams on more complex engineering tasks and modify larger codebases in the future.
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
1. Knows the most important data structures.
2. Knows the most important control structures.
3. Is familiar with the basic tools and methods of algorithm design.
4. Knows the fundamental principles of programming.
5. Is familiar with various Python libraries.
6. Understands the possibilities of importing, visualizing, and exporting data.
7. Knows the basic syntax of the Python language.
8. Knows the most important programming terms in English as well.
9. Understands the role and importance of programming in civil engineering practice.
B. Skills
1. Is able to choose a programming language and environment for civil engineering calculation tasks.
2. Can confidently solve civil engineering calculation problems using the Python programming language.
3. Is able to organize the computational methods of civil engineering design into functions that other engineers can later use.
4. Can read, use, and modify code created by others.
5. Can search the internet for answers to programming-related questions, and then filter and validate the relevant answers.
6. Can organize calculations and associated documentation into an interactive notebook.
7. Can interpret error messages and fix errors based on them.
C. Attitudes
1. Is capable and open to learning new programming languages.
2. Is capable and open to independently expanding their IT knowledge.
3. Understands that the programming language is English, so they strive to deepen their English (professional) language skills.
4. Always keeps in mind that their code should be understandable, clear, and easily modifiable by others.
5. Avoids unnecessary complexity and strives for transparent, elegant solutions.
6. Strives to complete their tasks to the best of their ability and at a high standard.
D. Autonomy and Responsibility
1. Can independently solve smaller engineering tasks using the Python programming language.
2. Applies a systems-based approach when solving tasks.
3. Checks and validates their work in every case.
4. Takes responsibility for the quality of the code they write.
2.3 Methods
As a laboratory practice, the most significant role in the teaching is given to interactive in-person education:
During the practice, students work in interactive notebooks where theoretical sections are clearly interrupted by programming tasks. The attention, activity, and the breaking of monotony during the classes are ensured by alternating between theoretical and active programming tasks.
During the practice, students do not see the solutions to the tasks. However, afterward, we make the solutions (both the code and its textual explanation) publicly available. This ensures that students can independently catch up on the material in case of absence.
At the end of the notebooks, summaries, review questions, and practice tasks also help with preparation.
In addition to regular contact hours, the acquisition of the subject's competencies is supported by the Study Room, where a teaching assistant answers any arising questions.
In the provided interactive notebooks, clearly marked sections or other learning materials (videos, websites, book excerpts) must be studied independently by the students, and they can ask questions related to these materials during the laboratory practices, Study Room sessions, or online consultations. These materials will be assessed.
The provided interactive workbooks include clearly marked supplementary materials that either aid understanding or contain additional knowledge related to the curriculum that goes beyond the current level of the students' knowledge (e.g., missing mathematics concepts) but will be necessary for their future studies. These supplementary materials will, of course, not be assessed.
2.4 Course outline
1. Bevezetés a Pythonba
2. Adattípusok és függvények
3. Függvények írása
4. List adatszerkezet
5. Tuple, set, dictionary adatszerkezetek
6. Részösszefoglalás, for ciklus
7. Részösszefoglalás, while ciklus
8. Programozási alaptételek I.
9. Programozási alaptételek II.
10. Numpy alapismeretek
11. Adatok olvasása és írása
12. Adatok és egyváltozós függvények ábrázolása
13. Programozás alapjai 2. tematika
14. Összefoglalás
The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
2.5 Study materials
Interactive notebooks for every exercise found in Moodle.
2.6 Other information
-
2.7 Consultation
Consultation hours: as specified on the department's website, or by prior arrangement via email; email: ekler.hajnalka@emk.bme.hu .
This Subject Datasheet is valid for:
2025/2026 semester I
II. Subject requirements
Assessment and evaluation of the learning outcomes
3.1 General rules
During the semester, students will complete 10 short theoretical tests at the beginning of the practical sessions, and they are also required to complete two practical midterm exams.
If a student’s absence exceeds 30% of the total laboratory hours, the course credits cannot be obtained.
3.2 Assessment methods
| Teljesítményértékelés neve (típus) | Jele | Értékelt tanulási eredmények |
|---|---|---|
| Control tests | CT1 - CT10 | A1 - A10, B1, B4, C1-C3 |
| Midterm test 1 | MT1 | A1, A5, A7, B2, B3, B6,B7, C4, C5, C6, D1 - D4 |
| Midterm test 2 | MT2 | A1 - A10, B2, B3, B6, B7, C4, C5, C6, D1 - D4 |
The dates of deadlines of assignments/homework can be found in the detailed course schedule on the subject’s website.
3.3 Evaluation system
| Jele | Részarány |
|---|---|
| A1 - A10, B1, B4, C1-C3 | 30% |
| A1, A5, A7, B2, B3, B6,B7, C4, C5, C6, D1 - D4 | 20% |
| A1 - A10, B2, B3, B6, B7, C4, C5, C6, D1 - D4 | 50% |
| Összesen | 100% |
3.4 Requirements and validity of signature
No signature can be obtained for this course.
3.5 Grading system
| Érdemjegy | Pontszám (P) |
|---|---|
| jeles(5) | 85≤P |
| jó(4) | 75≤P<85% |
| közepes(3) | 65≤P<75% |
| elégséges(2) | 50≤P<65% |
| elégtelen(1) | P<undefined% |
3.6 Retake and repeat
There is no minimum point requirement for the CTs (Controlt Test), but during the retake week, all CTs can be retaken/modified in an overall test. The better result will be considered, encouraging students to review the theoretical material at the end of the semester.
The minimum passing score for the first midterm test is 10 points (50% of the achievable points), and a retake opportunity will be provided in the next lab. The last score obtained will be taken into account.
The minimum passing score for the second midterm test is 20 points (50% of the achievable points), and a retake opportunity will be provided outside of regular class time during the retake week. Again, the last score obtained will be taken into account.
If a student actively participates in at least 70% of the Study Rooms, we will provide a second retake opportunity for both the overall control test and both midterm tests. For the overall control test, the better result will be considered, while for the midterms, the last result will be taken into account.
3.7 Estimated workload
| Tevékenység | Óra/félév |
|---|---|
| Participation in contact lessons | 14 x 2 = 28 |
| Preparation for practical sessions | 14 x 2 = 28 |
| Preparation for theoretical tests | 10 x 1 = 10 |
| Preparation for practical assessments | 2 x 12 = 24 |
3.8 Effective date
1 September 2025
This Subject Datasheet is valid for:
2025/2026 semester I