6 EC
Semester 1, periode 1, 2
5141YODW6Y
| Eigenaar | Bachelor Science, Technology & Innovation |
| Coördinator | dr. A. Pérez de Alba Ortíz |
| Onderdeel van | Bachelor Science, Technology & Innovation, jaar 1 |
In this course, you will first learn the basic concepts of computational thinking. In a formal manner, you will be familiarized with the concept of problem decomposition and learn how to solve problems using algorithms. During the course and practical sessions, you will also learn how to logically organize data and to abstract physical phenomena through modelling and simulation. Computational thinking allows you to explore problems that are difficult or even impossible to explore in the real world. During the first half of the course, you will learn how to produce well-structured and efficient code. In the second half, you will apply this coding skills to tackle relevant problems from different disciplines, e.g., physics, chemistry, biology, engineering, etc. This course is a steppingstone for developing advanced programming skills for modelling, simulation, and data-analysis, which are key to scientific and technological advancement.
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The lectures are meant to first introduce the week’s topic and then to give an in-depth follow-up after the students have had some hands-on experience with the subject matter during the computer lab sessions. The computer lab sessions help the students to better grasp the concepts explained during the lectures and to understand their applicability. Blended learning will be provided through the availability of online materials (knowledge clips, quizzes) to be studied before entering a lecture/computer lab session. Flipped classroom will be used in the last sessions (14,13) when revisiting previous exercises. The self-study and working independently hours will be devoted to assignments, studying for the exam, and preparing presentations. Presentations will serve to contextualize knowledge and practice SRE.
Activiteit | Uren | |
Hoorcollege | 28 | |
Laptopcollege | 56 | |
Presentatie | 4 | |
Tentamen digitaal | 3 | |
Zelfstudie | 77 | |
Totaal | 168 | (6 EC x 28 uur) |
Aanvullende eisen voor dit vak:
For computer lab (i.e., laptop) sessions ("laptopcollege") attendance is compulsory . In these sessions, students apply the knowledge gained during lectures. This knowledge application is central to achieving the course’s learning objectives and requires active, guided participation. Teaching Assistants explain the assignments and reports, which are compulsory, and help the students. After the session, students can still submit questions online via TicketVise.
Attendance to the Final Presentation is compulsory as part of the assessment. The students' computer modelling fundamentals and communication skills will be assessed during these sessions.
Attending lectures is highly recommended, because they give essential information about the practical assignments. The lecturer also offers small quizzes during the lectures to help understanding new material. Lecture recordings are provided when classroom equipment is available, which is not always the case.
| Onderdeel en weging | Details |
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Eindcijfer | |
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40% Assignments and Reports | |
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4% A1: Algorithms in natural language | |
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13% A10: Population dynamics | |
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13% A11: Particle dynamics | |
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7% A2: Introduction to Python | |
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7% A3: Python functions and random numbers | |
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7% A4: Introduction to numerical programming with Python | |
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7% A5: Animations & simulations in Python | |
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7% A6: Plotting & Physics based simulations | |
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7% A7: Data processing and analysis | |
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13% A8: Cellular Automata | |
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15% A9: Computational Chemical Kinetics (Design challenge) | |
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40% Poster and Presentation | |
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1 (100%) Poster project | |
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20% Exam | Moet ≥ 5.5 zijn |
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1 (100%) Tentamen digitaal |
There are 5 elements to the assessment:
Programming assignments: The compulsory programming assignments, both individual and in teams, are provided and guided during the practical sessions. Code and documentation will be assessed by TAs, and students will receive feedback.
Written reports: The written report is meant to practice and evaluate communication skills. The reports will be based on the programming assignments, describe the constructed program in natural language, provide visualisations and discuss the interpretation thereof. Written reports are compulsory and assessed by TAs.
Exam: The digital exam (in ANS) will test the major computational and coding concepts discussed during the first half of the course. The exam will consist of a combination of closed and open questions. The format of the exam will be similar to that of the coding assignments and example questions available per topic.
Project Poster: During the second part of the course the students will work in small teams (2-3 students) on a larger project, based on previous assignments. Teams will present the outcome of this final project in poster format. The content of the poster and code behind will be assessed by staff.
Project Pitch: During the poster session, they students will pitch the outcome of their project work to their peers and be assessed by staff. The students will be invited to review each other’s posters and to discuss the computational implementations.
Feedback on assignment reports and exam will be provided in Canvas via the rubric sub-scores and comments from the assessors. Students can discuss assignment results with the Teaching Assistants during the scheduled sessions. Questions about the exam results can be addressed to the Teachers via the exam platform.
Dit vak hanteert de algemene 'Fraude- en plagiaatregeling' van de UvA. Hier wordt nauwkeurig op gecontroleerd. Bij verdenking van fraude of plagiaat wordt de examencommissie van de opleiding ingeschakeld. Zie de Fraude- en plagiaatregeling van de UvA: http://student.uva.nl
| Week | Topic |
| 1 | Introduction to Computational Thinking |
| 2 | Introduction to Python |
| 3 |
Python functions and random numbers |
| 4 | Introduction to numerical programming with Python |
| 5 | Animations & simulations in Python |
| 6 | Plotting & Physics based simulations |
| 7 | Data processing and analysis |
| 8 | Midterm assessment (Exam) |
| 9 | Introduction Modelling and Simulation (Cellular Automata) |
| 10 | Design Challenge |
| 11 | Population Dynamics |
| 12 | Particle dynamics |
| 13 | Performance & error analysis |
| 14 | Evolutionary computing & optimization |
| 15 | Introduction to AI |
| 16 | Final assessment (Poster and Presentation) |