The course Introduction to computational science provides a broad overview of the fundamentals of computational
science and more broadly the use of computational tools in natural science. Concepts are introduced with the aim
of providing a general understanding of the field and showing the range of available tools and options. Examples
of specific software are provided with focus on open-source software. Practical hands-on exercises offer the
opportunity to practice the concepts introduced in the course and to gain experience in the use of these tools.
Poslední úprava: Kopecký Vladimír, RNDr., Ph.D. (16.02.2022)
Podmínky zakončení předmětu - angličtina
Class credit is given for completing practical exercises and homework. The final grade will be based on a midterm test (25 %), a final test (25 %), and oral examination (50 %).
Poslední úprava: Houfek Karel, doc. RNDr., Ph.D. (02.05.2023)
Literatura - angličtina
Nell Dale, John Lewis, Computer science illuminated, Jones & Bartlett Learning, 2020
Joakim Sundnes, Introduction to Scientific Programming with Python, Springer International Publishing, 2020
Lecture notes and other provided material
Poslední úprava: Kopecký Vladimír, RNDr., Ph.D. (16.02.2022)
Kontroly studia předmětu a podmínky pro jejich úspěšné vykonání, způsob hodnocení - angličtina
The requirements for the exam correspond to the course syllabus to the extent that was given in the lectures.
Poslední úprava: Houfek Karel, doc. RNDr., Ph.D. (02.05.2023)
Sylabus - angličtina
Modern computer architecture, personal computers, workstations, supercomputers
Operating systems, history, currently available systems, user interface types, command line
Networking, the Internet, encrypted communication, using remote computers
Fundamentals of programming and software development, types of programming languages, programming paradigms, program flow control, data structures
Computer algebra systems and symbolic manipulation
Numerical computation
Interactive computing, notebook-style interface
Data processing and plotting
Sharing code and data, version control systems, repositories
Computer graphics, vector and raster images
Desktop publishing, preparing publication-quality documents, presentations, plots, and graphics
Tools for live online collaboration
Parallelization and high-performance computing
Machine learning, artificial intelligence
Poslední úprava: Maršálek Ondřej, RNDr., Ph.D. (03.10.2023)
Výsledky učení - angličtina
Upon successful completion of the course, students will be able to:
explain the basic principles of modern computer systems, operating systems, computer networks, and high-performance computing;
use command-line tools, remote computing environments, and online collaboration platforms for scientific work;
develop simple programs using appropriate programming concepts, data structures, and software development practices;
apply numerical and symbolic computation tools to solve scientific problems;
process, visualize, and present scientific data using appropriate computational tools;
prepare publication-quality scientific documents, figures, and presentations;
use version control systems and code repositories to manage and share computational projects;
describe the basic principles and applications of parallel computing, machine learning, and artificial intelligence in computational science.
Poslední úprava: Houfek Karel, doc. RNDr., Ph.D. (07.07.2026)
