Algorithmics
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Teaching
Details
Faculty Faculty of Science and Medicine Domain Computer Science Code UE-SIN.03023 Languages English Type of lesson Lecture
Level Bachelor Semester AS-2024 Title
French Algorithmique German Algorithmik English Algorithmics Schedules and rooms
Summary schedule Thursday 13:15 - 17:00, Hebdomadaire (Autumn semester)
Struct. of the schedule 2 x 2 Std. pro Woche während 14 Wochen Contact's hours 56 Teaching
Responsibles - Grossenbacher Bastian Alexander
Teachers - Grossenbacher Bastian Alexander
Assistants - von Moos Richard Walter
Description In this course, we teach the main principles of algorithmic design, study classic algorithmic problems and introduce the most important algorithms for solving them.
Algorithmic design principles are general approaches for developing algorithms. In particular, we consider recursive and inductive methods, divide-and-conquer, backtracking and dynamic programming.
Over the years, a number of algorithmic problems have established themselves as classical problems of computer science, and elegant data structures and algorithms have been developed to solve these problems. In this course, we consider the following problems, data structures and algorithms:
- Sort: merge sort and quicksort
- Search: symbol tables, binary search trees, balanced search trees, hash tables
- Graphs: spanning trees, shortest paths, maximum flows
- Strings: String search, tries, regular expressions, data compression
Applications from practice illustrate the concepts.
Training objectives The students gain a basic understanding of the design and analysis of data structures and algorithms.
Condition of access Basic programming skills, particularly in Java
Comments In general, the course consists of two hours of lecture followed by two hours of classroom exercises, which are overseen by the teachers and their assistants.
Registration to the cours AND exams is mandatory and does not automatically happen if you are registered to a class. Please observe the deadlines of the faculty of science and medicine.
Softskills No Off field No BeNeFri Yes Mobility Yes UniPop No Documents
Bibliography - Textbooks
- (mandatory) Algorithms, Robert Sedgewick und Kevin Wayne,
Addison-Wesley, 4th edition, 2011 - Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, The MIT Press, 3rd edition, 2009
- (mandatory) Algorithms, Robert Sedgewick und Kevin Wayne,
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Dates and rooms
Date Hour Type of lesson Place 19.09.2024 13:15 - 17:00 Cours PER 21, Room F130 26.09.2024 13:15 - 17:00 Cours PER 21, Room F130 03.10.2024 13:15 - 17:00 Cours PER 21, Room F130 10.10.2024 13:15 - 17:00 Cours PER 21, Room F130 17.10.2024 13:15 - 17:00 Cours PER 21, Room F130 24.10.2024 13:15 - 17:00 Cours PER 21, Room F130 31.10.2024 13:15 - 17:00 Cours PER 21, Room F130 07.11.2024 13:15 - 17:00 Cours PER 21, Room F130 14.11.2024 13:15 - 17:00 Cours PER 21, Room F130 21.11.2024 13:15 - 17:00 Cours PER 21, Room F130 28.11.2024 13:15 - 17:00 Cours PER 21, Room F130 05.12.2024 13:15 - 17:00 Cours PER 21, Room F130 12.12.2024 13:15 - 17:00 Cours PER 21, Room F130 19.12.2024 13:15 - 17:00 Cours PER 21, Room F130 -
Assessments methods
Written exam - AS-2024, Session d'hiver 2025
Date 04.02.2025 10:00 - 12:00 Assessments methods By rating Descriptions of Exams Selon modalité A de l'annexe du plan d'études en informatique
Requirements Validation des séries d’exercices selon les critères du cours
Comment Closed book exam
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Assignment
Valid for the following curricula: Additional Courses in Sciences
Version: ens_compl_sciences
Paquet indépendant des branches > Advanced courses in Computer Science (Bachelor level)
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Additional TDHSE programme in Computer Science
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Additional TDHSE Programme Requirements for Computer Science 60 or +30 > Programmes 60 or +30 > Additional Programme Requirements to Computer Science 60 > Additional TDHSE programme for Computer Science 60 (from AS2020 on)
Ba - Business Informatics - 180 ECTS
Version: 2020-SA_V02
2nd year 60 ECTS > Algorithmics
Computer Science 120
Version: 2022_1/V_01
BSc in Computer science, Major, 2nd-3rd year > Computer Science 2nd and 3th year (from AS2021 on)
Computer Science 30
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Minor in Computer science 30 > Computer Science Minor 30 and 60 ECTS compulsory (from SA2020 on)
Computer Science 60
Version: 2022_1/V_01
Minor in Computer Science 60 > Computer Science Minor 30 and 60 ECTS compulsory (from SA2020 on)
Computer Science 50 [BSc_SI/BA_SI]
Version: 2022_1/V_01
BSc_SI/BA_SI, Computer science 50 ECTS, 1st-3rd years > BSc_SI/BA_SI, Computer Science, 2nd-3rd years, elective courses for 50 ECTS (from AS2020 on)
Computer Science [3e cycle]
Version: 2024_2/V_01
Continuing education > Advanced courses in Computer Science (Bachelor level)
Computer Science [POST-DOC]
Version: 2015_1/V_01
Continuing education > Advanced courses in Computer Science (Bachelor level)
Computer Science [TDHSE] 60
Version: 2022_1/V_01
Minor in Computer Science (TDHSE) 60 > Computer Science Minor TDHSE 60 ECTS (from SA2021 on)
Mathematics 30 for Mathematicians (MATH 30MA)
Version: 2022_1/V_01
Mathematics for mathematicians (MATH 30MA), minor 30 (from AS2020 on) > Mathematics, minor MATH 30MA, elective courses (from AS2018 on)
Mathematics 30 for Physicists (MATH 30PH)
Version: 2022_1/V_01
Mathematics for physicists (MATH 30PH), minor 30 (from AS2020 on) > Mathematics, minor MATH 30PH, elective courses (from AS2018 on)
MiBa - Computer Management - 60 ECTS
Version: 2021-SA_V03
Register in the option corresponding to your situation. > Standard > Min. 18 ECTS from the list > Algorithmics
Pre-Master-Programme to the MSc in Bioinformatics and Computational Biology [PRE-MA]
Version: 2022_1/V_01
Prerequisite to the MSc in Bioinformatics and Computational Biology > Advanced courses in Computer Science (Bachelor level)
Pre-Master-Programme to the MSc in Computer Science [PRE-MA]
Version: 2022_1/V_01
Prerequisite to the MSc in Computer science > Advanced courses in Computer Science (Bachelor level)
Pre-Master-Programme to the MSc in Digital Neuroscience [PRE-MA]
Version: 2023_1/V_01
Pre-Master-Programme to the MSc in Digital Neuroscience > Advanced courses in Computer Science (Bachelor level)