Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

Search result: Catalogue data in Autumn Semester 2018

Computer Science Teaching Diploma Information
More informations at : Link
Educational Science
Course offerings in the category Educational Science are listed under "Programme: Educational Science for Teaching Diploma and TC".
NumberTitleTypeECTSHoursLecturers
851-0242-06LCognitively Activating Instructions in MINT Subjects Restricted registration - show details
Enrolment only possible with matriculation in Teaching Diploma or Teaching Certificate (excluding Teaching Diploma Sport).

This course unit can only be enrolled after successful participation in, or during enrollment in the course "Human Learning (EW 1)".
W2 credits2SR. Schumacher
AbstractThis seminar focuses on teaching units in chemistry, physics and mathematics that have been developed at the MINT Learning Center of the ETH Zurich. In the first meeting, the mission of the MINT Learning Center will be communicated. Furthermore, in groups of two, the students will intensively work on, refine and optimize a teaching unit following a goal set in advance.
Objective- Get to know cognitively activating instructions in MINT subjects
- Get information about recent literature on learning and instruction
Prerequisites / NoticeFür eine reibungslose Semesterplanung wird um frühe Anmeldung und persönliches Erscheinen zum ersten Lehrveranstaltungstermin ersucht.
851-0242-07LHuman Intelligence Restricted registration - show details
Enrolment only possible with matriculation in Teaching Diploma or Teaching Certificate (excluding Teaching Diploma Sport).
Number of participants limited to 30.
This course unit can only be enrolled after successful participation in, or during enrollment in the course "Human Learning (EW 1)".
W1 credit1SE. Stern
AbstractThe focus will be on the book "Intelligenz: Grosse Unterschiede und ihre Folgen" by Stern and Neubauer. Participation at the first meeting is obligatory. It is required that all participants read the complete book. Furthermore, in two meetings of 90 minutes, concept papers developed in small groups (5 - 10 students) will be discussed.
Objective- Understanding of research methods used in the empirical human sciences
- Getting to know intelligence tests
- Understanding findings relevant for education
851-0242-08LResearch Methods in Educational Science Restricted registration - show details
Number of participants limited to 30
This course unit can only be enrolled after successful participation in, or during enrollment in the course "Human Learning (EW 1)".
W1 credit1SP. Edelsbrunner, M. Berkowitz Biran, Z. Lue, C. M. Thurn
AbstractLiterature from the learning sciences is critically discussed with a focus on research methods.
At the first meeting, working groups will be assembled and meetings with those will be set up.
In the small groups students will write critical essays about the read literature. At the third meeting, we will discuss the essays and develop research questions in group work.
Objective- Understand research methods used in the empirical educational sciences
- Understand and critically examine information from scientific journals and media
- Understand pedagogically relevant findings from the empirical educational sciences
851-0242-09LStudent Research Projects: Practical Research on Learning and Instruction Restricted registration - show details
Number of participants limited to 20.

The sucessful completion of both course no. 851-0240-00L "Menschliches Lernen (EW 1)" and course no. 851-0238-01L "Unterstützung und Diagnose von Wissenserwerbsprozessen (EW 3)" is a necessary prerequisite for this course.
W2 credits2SA. Deiglmayr, P. Edelsbrunner, U. Markwalder, S. Peteranderl, E. Stern
AbstractIn teams of two, participants in this seminar conduct their own research project. Each team is advised by one of the researchers serving as lecturers in this course. Basic conceptual and methodological issues are the topic of a series of plenary meetings; however, the major part of the work is done in small-group meetings with the advising researcher, and in self-directed research projects.
ObjectiveThe course is targeted at advanced students who have taken an interest in gathering practical research experience in the field of Learning & Instruction. In teams of two, students conduct their own research projects (planning, conducting, analyzing, interpreting, and presenting research); thus, the course requires a high amount of self-directed working. Students are personally advised, and supported in their research project, by one of the researchers serving as lecturers in this course. During the first half the semester, relevant methodological knowledge and skills are practiced during plenary meetings and in students` independent reading (e.g. generating and testing research questions, designing experiments, and analyzing data in the field of Learning and Instruction)

Learning goals include:
- Participants can illustrate and explain basic methods and concepts for research in the fields of Learning and Instruction, e.g. with the help of practical examples.
- Participants can generate testable research questions for a topic relevant in the fields of Learning and Instruction.
- Participants can design and conduct a study that is relevant for answering their research question.
- Participants can summarize and evaluate the main results from a study in the field of learning and Instruction, with regard to the research question being asked.
» see Educational Science Teaching Diploma
Subject Didactics in Computer Science
Important: You can only enrole in the courses of this category if you have not more than 12 CP left for possible additional requirements.
NumberTitleTypeECTSHoursLecturers
272-0101-00LSubject Didactics of Computer Science I Restricted registration - show details
Simultaneous enrolment in Introductory Practical in Computer Science - course 272-0201-00L - is compulsory.
O4 credits3GG. Serafini, J. Hromkovic
AbstractThe unit "Subject Didactics of Computer Science I" addresses key contributions of computer science to general education. The course deals with the thoughtful choice of educational contents for computer science classes, which takes into account its comprehensibility for different age groups as well as didactic approaches suitable for a successful knowledge transfer.
ObjectiveThe general objective of the course consists in highlighting the tight connection between the mathematical and algorithmic way of thinking and the approaches adopted by engineering disciplines, and in reflecting on teaching approaches for sustainable computer science teaching activities.

The students understand the fundamental concepts of computer science in the context of a broad and deep knowledge. Through this understanding, they manage to prepare teaching materials for a successful knowledge transfer and to pass their passion for the subject on to their pupils.

The students know various teaching methods as well as their advantages and disadvantages. They can handle inhomogeneous prior knowledge of the learners inside a class. Besides holding classes, the students do care about the individual pupil support.

They encourage the autonomy of the learners, manage to work with diverse target groups and to establish a positive learning environment.

The students are able to express themselves using a comprehensible and refined professional language, both in a spoken and a written way, and they master the basic terminology of computer science. Besides the English terms, they are familiar with the corresponding German expressions. The students are able to produce detailed, matured, linguistically correct and design-wise appealing teaching materials.
ContentThe course "Subject Didactics of Computer Science I" addresses key contributions of computer science to general education. The chosen topics support the young learners in developing a unique and indispensable way of thinking, in enhancing their understanding of our world as well as in achieving university education entrance qualifications.

The main topics of the course unit "Subject Didactics of Computer Science I" are the didactics of finite state automata, of formal languages and of the introduction to programming. The unit focuses on contents of computer science that contribute to general education. This involves the understanding of fundamental scientific concepts such as algorithm, complexity, determinism, computation, automata, verification, testing and programming language as well as the way to embed them into a scientifically sound and didactically sustainable computer science course.

In a semester exercise, the students develop and document an adaptive teaching unit for computer science. They learn to employ the didactics methods and techniques that are introduced at the beginning of the semester.
Lecture notesUnterlagen und Folien werden zur Verfügung gestellt.
LiteratureJ. Hromkovic: Sieben Wunder der Informatik: Eine Reise an die Grenze des Machbaren, mit Aufgaben und Lösungen. Vieweg+Teubner; Auflage: 2 (2008).

K. Freiermuth, J. Hromkovic, L. Keller und B. Steffen: Einfuehrung in die Kryptologie: Lehrbuch für Unterricht und Selbststudium. Springer Vieweg; Auflage: 2 (2014).

J. Hromkovic: Berechenbarkeit: Logik, Argumentation, Rechner und Assembler, Unendlichkeit, Grenzen der Automatisierbarkeit. Vieweg+Teubner; Auflage: 1 (2011).

H.-J. Böckenhauer, J. Hromkovic: Formale Sprachen: Endliche Automaten, Grammatiken, lexikalische und syntaktische Analyse. Springer Vieweg; Auflage: 1 (Januar 2013).

J. Hromkovic: Einführung in die Programmierung mit LOGO: Lehrbuch für Unterricht und Selbststudium. Springer Vieweg; Auflage: 3 (2014)
Prerequisites / NoticeLehrdiplom-Studierende müssen diese Lerneinheit zusammen mit dem Einführungspraktikum Informatik - 272-0201-00L - belegen.
272-0103-00LMentored Work Subject Didactics Computer Science Information Restricted registration - show details
Mentored Work Subject Didactics in Computer Science for TC and Teaching Diploma.
O2 credits4AJ. Hromkovic, G. Serafini
AbstractIn their mentored work on subject didactics, students put into practice the contents of the subject-didactics lectures and go into these in greater depth. Under supervision, they compile tuition materials that are conducive to learning and/or analyse and reflect on certain topics from a subject-based and pedagogical angle.
ObjectiveThe objective is for the students:
- to be able to familiarise themselves with a tuition topic by consulting different sources, acquiring materials and reflecting on the relevance of the topic and the access they have selected to this topic from a specialist, subject-didactics and pedagogical angle and potentially from a social angle too.
- to show that they can independently compile a tuition sequence that is conducive to learning and develop this to the point where it is ready for use.
ContentThematische Schwerpunkte
Die Gegenstände der mentorierten Arbeit in Fachdidaktik stammen in der Regel aus dem gymnasialen Unterricht.

Lernformen
Alle Studierenden erhalten ein individuelles Thema und erstellen dazu eine eigenständige Arbeit. Sie werden dabei von ihrer Betreuungsperson begleitet. Gegebenenfalls stellen sie ihre Arbeit oder Aspekte daraus in einem Kurzvortrag vor. Die mentorierte Arbeit ist Teil des Portfolios der Studierenden.
LiteratureDie Literatur ist themenspezifisch. Die Studierenden beschaffen sie sich in der Regel selber (siehe Lernziele). In besonderen Fällen wird sie vom Betreuer zur Verfügung gestellt.
Prerequisites / NoticeDie Arbeit sollte vor Beginn des Praktikums abgeschlossen
werden.
272-0104-00LMentored Work Subject Didactics Computer Science B Information Restricted registration - show details
Mentored Work Subject Didactics in Computer Science for Teaching Diploma and for students upgrading TC to Teaching Diploma.
O2 credits4AJ. Hromkovic, G. Serafini
AbstractIn their mentored work on subject didactics, students put into practice the contents of the subject-didactics lectures and go into these in greater depth. Under supervision, they compile tuition materials that are conducive to learning and/or analyse and reflect on certain topics from a subject-based and pedagogical angle.
ObjectiveThe objective is for the students:
- to be able to familiarise themselves with a tuition topic by consulting different sources, acquiring materials and reflecting on the relevance of the topic and the access they have selected to this topic from a specialist, subject-didactics and pedagogical angle and potentially from a social angle too.
- to show that they can independently compile a tuition sequence that is conducive to learning and develop this to the point where it is ready for use.
ContentThematische Schwerpunkte
Die Gegenstände der mentorierten Arbeit in Fachdidaktik stammen in der Regel aus dem gymnasialen Unterricht.

Lernformen
Alle Studierenden erhalten ein individuelles Thema und erstellen dazu eine eigenständige Arbeit. Sie werden dabei von ihrer Betreuungsperson begleitet. Gegebenenfalls stellen sie ihre Arbeit oder Aspekte daraus in einem Kurzvortrag vor. Die mentorierte Arbeit ist Teil des Portfolios der Studierenden.
LiteratureDie Literatur ist themenspezifisch. Die Studierenden beschaffen sie sich in der Regel selber (siehe Lernziele). In besonderen Fällen wird sie vom Betreuer zur Verfügung gestellt.
Prerequisites / NoticeDie Arbeit sollte vor Beginn des Praktikums abgeschlossen
werden.
Professional Training
Important: You can only enrole in the courses of this category if you have not more than 12 CP left for possible additional requirements.
NumberTitleTypeECTSHoursLecturers
272-0201-00LIntroductory Practical in Computer Science Information Restricted registration - show details
Simultaneous enrolment in Subject Didactics of Computer Science I - course 272-0101-00L - is compulsory.
O3 credits6PJ. Hromkovic, G. Serafini
AbstractDuring the introductory teaching practice, the students sit in on five lessons given by the teacher responsible for their teaching practice, and teach five lessons themselves. The students are given observation and reflection assignments by the teacher responsible for their teaching practice.
ObjectiveRight at the start of their training, students acquire initial experience with the observation of teaching, the establishment of concepts for teaching and the implementation of teaching. This early confrontation with the complexity of everything that teaching involves helps students decide whether they wish to and, indeed, ought to, continue with the training. It forms a basis for the subsequent pedagogical and subject-didactics training.
ContentDen Studierenden bietet das Einführungspraktikum einen Einblick in den Berufsalltag einer Lehrperson.
Die Praktikumslehrperson legt Beobachtungs- und Reflexionsaufträge und die Themen der zu erteilenden Lektionen fest. Die schriftlich dokumentierten Ergebnisse der Arbeitsaufträge sind Bestandteil des Portfolios des/der Studierenden. Anlässlich der Hospitationen erläutert die Praktikumslehrperson ihre fachlichen, fachdidaktischen und pädagogischen Überlegungen, auf deren Basis sie den Unterricht geplant hat und tauscht sich mit der/dem Studierenden aus. Zu den Lektionen, die der/die Studierende selber hält, führt die Praktikumslehrperson Vor- und Nachbesprechungen durch.
LiteratureWird von der Praktikumslehrperson bestimmt.
272-0202-00LProfessional Exercises Restricted registration - show details O2 credits4UJ. Hromkovic, G. Serafini
AbstractIn the course Professional Exercises the students achieve additional school-relevant experiences. The students carry out individually specified, practice related projects, in which they support, document or reflect on learning processes.
ObjectiveAchievement of additional school-relevant experiences. The students carry out individually specified, practice related projects, in which they support, document or reflect on learning processes.
ContentThe course Professional Exercises offers the opportunity for additional school-relevant activities.
The students are supported by the lecturers or by experienced teachers. They assist teachers at school, they create training systems and tests, correct the written homework of pupils and evaluate the progress of a class. The students create explanations and detailed solutions to exercises with respect to the actual knowledge of the pupils. A written assignment states the exact scope of the activity.
272-0203-00LTeaching Internship in Computer Science Information Restricted registration - show details O8 credits17PJ. Hromkovic, G. Serafini
AbstractThe teaching practice takes in 50 lessons: 30 are taught by the students, and the students sit in on 20 lessons. The teaching practice lasts 4-6 weeks. It gives students the opportunity to implement the contents of their specialist-subject, educational science and subject-didactics training in the classroom. Students also conduct work assignments in parallel to their teaching practice.
Objective- Students use their specialist-subject, educational-science and subject-didactics training to draw up concepts for teaching.
- They are able to assess the significance of tuition topics in their subject from different angles (including interdisciplinary angles) and impart these to their pupils.
- They acquire the skills of the teaching trade.
- They practise finding the balance between instruction and openness so that pupils can and, indeed, must make their own cognitive contribution.
- They learn to assess pupils' work.
- Together with the teacher in charge of their teacher training, the students constantly evaluate their own performance.
ContentDie Studierenden sammeln Erfahrungen in der Unterrichtsführung, der Auseinandersetzung mit Lernenden, der Klassenbetreuung und der Leistungsbeurteilung. Zu Beginn des Praktikums plant die Praktikumslehrperson gemeinsam mit dem/der Studierenden das Praktikum und die Arbeitsaufträge. Die schriftlich dokumentierten Ergebnisse der Arbeitsaufträge sind Bestandteil des Portfolios der Studierenden. Anlässlich der Hospitationen erläutert die Praktikumslehrperson ihre fachlichen, fachdidaktischen und pädagogischen Überlegungen, auf deren Basis sie den Unterricht geplant hat und tauscht sich mit dem/der Studierenden aus. Die von dem/der Studierenden gehaltenen Lektionen werden vor- und nachbesprochen. Die Praktikumslehrperson sorgt ausserdem dafür, dass der/die Studierende Einblick in den schulischen Alltag erhält und die vielfältigen Verpflichtungen einer Lehrperson kennen lernt.
LiteratureWird von der Praktikumslehrperson bestimmt.
Prerequisites / NoticeFindet in der Regel am Schluss der Ausbildung, vor Ablegung der Prüfungslektionen statt.
272-0204-00LTeaching Internship in Computer Science II Restricted registration - show details
Teaching Internship for students upgrading TC to Teaching Diploma.
W4 credits9PJ. Hromkovic, G. Serafini
AbstractThis is a supplement to the Teaching Internship required to obtain a Teaching Diploma in the corresponding subject. It is aimed at enlarging the already acquired teaching experience. Students observe 10 lessons and teach 15 lessons independently.
ObjectiveDie Studierenden können die Bedeutung von Unterrichtsthemen in ihrem Fach unter verschiedenen Blickwinkeln einschätzen. Sie kennen und beherrschen das unterrichtliche Handwerk. Sie können ein gegebenes Unterrichtsthema für eine Gruppe von Lernenden fachlich und didaktisch korrekt strukturieren und in eine adäquate Lernumgebung umsetzen. Es gelingt ihnen, die Balance zwischen Anleitung und Offenheit zu finden, sodass die Lernenden sowohl über den nötigen Freiraum wie über ausreichend Orientierung verfügen, um aktiv und effektiv flexibel nutzbares (Fach-)Wissen zu erwerben.
ContentDas Aufbaupraktikum richtet sich an Studierende, die bereits das Didaktik-Zertifikat in ihrem Fach erworben haben und nun eine Aufbauausbildung zum Lehrdiplom für Maturitätsschulen absolvieren. In diesem zusätzlichen Praktikum sollen die Studierenden vertiefte unterrichtliche Erfahrungen machen. Auf der Grundlage der zusätzlich erworbenen Kenntnisse und mit Hilfe der ihnen jetzt zu Verfügung stehenden Instrumente analysieren sie verschiedene Aspekte des hospitierten Unterrichts. In dem von ihnen selbst gestalteten Unterricht nutzen sie beim Entwurf, bei der Durchführung und der Beurteilung ihrer Arbeit insbesondere die zusätzlich gewonnen Erkenntnisse aus der allgemeinen und fachdidaktischen Lehr- und Lernforschung.
272-0205-01LExamination Lesson I in Computer Science Information Restricted registration - show details
Simultaneous enrolment in "Examination Lesson II in Computer Science" (272-0205-02L) is compulsory.
O1 credit2PJ. Hromkovic, G. Serafini
AbstractIn the context of an examination lesson conducted and graded at a high school, the candidates provide evidence of the subject-matter-based and didactic skills they have acquired in the course of their training.
ObjectiveOn the basis of a specified topic, the candidate shows that they are in a position
- to develop and conduct teaching that is conducive to learning at high school level, substantiating it in terms of the subject-matter and from the didactic angle
- to analyze the tuition they have given with regard to its strengths and weaknesses, and outline improvements.
ContentDie Studierenden erfahren das Lektionsthema in der Regel eine Woche vor dem Prüfungstermin. Von der zuständigen Lehrperson erhalten sie Informationen über den Wissensstand der zu unterrichtenden Klasse und können sie vor dem Prüfungstermin besuchen.
Sie erstellen eine Vorbereitung gemäss Anleitung und reichen sie bis am Vortag um 12 Uhr den beiden Prüfungsexperten ein.
Die gehaltene Lektion wird kriteriumsbasiert beurteilt. Die Beurteilung umfasst auch die schriftliche Vorbereitung und eine mündliche Reflexion des Kandidaten/ der Kandidatin über die gehaltene Lektion im Rahmen eines kurzen Kolloquiums.
Lecture notesDokument: Schriftliche Vorbereitung für Prüfungslektionen.
Prerequisites / NoticeNach Abschluss der übrigen Ausbildung.
272-0205-02LExamination Lesson II in Computer Science Information Restricted registration - show details
Simultaneous enrolment in "Examination Lesson I in Computer Science" (272-0205-01L) is compulsory.
O1 credit2PJ. Hromkovic, G. Serafini
AbstractIn the context of an examination lesson conducted and graded at a high school, the candidates provide evidence of the subject-matter-based and didactic skills they have acquired in the course of their training.
ObjectiveOn the basis of a specified topic, the candidate shows that they are in a position
- to develop and conduct teaching that is conducive to learning at high school level, substantiating it in terms of the subject-matter and from the didactic angle
- to analyze the tuition they have given with regard to its strengths and weaknesses, and outline improvements.
ContentDie Studierenden erfahren das Lektionsthema in der Regel eine Woche vor dem Prüfungstermin. Von der zuständigen Lehrperson erhalten sie Informationen über den Wissensstand der zu unterrichtenden Klasse und können sie vor dem Prüfungstermin besuchen.
Sie erstellen eine Vorbereitung gemäss Anleitung und reichen sie bis am Vortag um 12 Uhr den beiden Prüfungsexperten ein.
Die gehaltene Lektion wird kriteriumsbasiert beurteilt. Die Beurteilung umfasst auch die schriftliche Vorbereitung und eine mündliche Reflexion des Kandidaten/ der Kandidatin über die gehaltene Lektion im Rahmen eines kurzen Kolloquiums.
Lecture notesDokument: Schriftliche Vorbereitung für Prüfungslektionen.
Prerequisites / NoticeNach Abschluss der übrigen Ausbildung.
Spec. Courses in Resp. Subj. w/ Educ. Focus & Further Subj. Didactics
NumberTitleTypeECTSHoursLecturers
272-0400-00LMentored Work Specialised Courses in the Respective Subject with Educational Focus Computer Sc A Information Restricted registration - show details O2 credits4AJ. Hromkovic, G. Serafini
AbstractIn the mentored work on their subject specialisation, students link high-school and university aspects of the subject, thus strengthening their teaching competence with regard to curriculum decisions and the future development of the tuition. They compile texts under supervision that are directly comprehensible to the targeted readers - generally specialist-subject teachers at high-school level.
ObjectiveThe aim is for the students
- to familiarise themselves with a new topic by obtaining material and studying the sources, so that they can selectively extend their specialist competence in this way.
- to independently develop a text on the topic, with special focus on its mathematical comprehensibility in respect of the level of knowledge of the targeted readership.
- To try out different options for specialist further training in their profession.
ContentThematische Schwerpunkte:
Die mentorierte Arbeit in FV besteht in der Regel in einer Literaturarbeit über ein Thema, das einen Bezug zum gymnasialem Unterricht oder seiner Weiterentwicklung hat. Die Studierenden setzen darin Erkenntnisse aus den Vorlesungen in FV praktisch um.

Lernformen:
Alle Studierenden erhalten ein individuelles Thema und erstellen dazu eine eigenständige Arbeit. Sie werden dabei von ihrer Betreuungsperson begleitet. Gegebenenfalls stellen sie ihre Arbeit oder Aspekte daraus in einem Kurzvortrag vor. Die mentorierte
Arbeit ist Teil des Portfolios der Studierenden.
LiteratureDie Literatur ist themenspezifisch. Sie muss je nach Situation selber beschafft werden oder wird zur Verfügung gestellt.
Prerequisites / NoticeDie Arbeit sollte vor Beginn des Praktikums abgeschlossen werden.
272-0401-00LMentored Work Specialised Courses in the Respective Subject with Educational Focus Computer Sc B Information Restricted registration - show details O2 credits4AJ. Hromkovic, G. Serafini
AbstractIn the mentored work on their subject specialisation, students link high-school and university aspects of the subject, thus strengthening their teaching competence with regard to curriculum decisions and the future development of the tuition. They compile texts under supervision that are directly comprehensible to the targeted readers - generally specialist-subject teachers at high-school level.
ObjectiveThe aim is for the students
- to familiarise themselves with a new topic by obtaining material and studying the sources, so that they can selectively extend their specialist competence in this way.
- to independently develop a text on the topic, with special focus on its mathematical comprehensibility in respect of the level of knowledge of the targeted readership.
- To try out different options for specialist further training in their profession.
ContentThematische Schwerpunkte:
Die mentorierte Arbeit in FV besteht in der Regel in einer Literaturarbeit über ein Thema, das einen Bezug zum gymnasialem Unterricht oder seiner Weiterentwicklung hat. Die Studierenden setzen darin Erkenntnisse aus den Vorlesungen in FV praktisch um.

Lernformen:
Alle Studierenden erhalten ein individuelles Thema und erstellen dazu eine eigenständige Arbeit. Sie werden dabei von ihrer Betreuungsperson begleitet. Gegebenenfalls stellen sie ihre Arbeit oder Aspekte daraus in einem Kurzvortrag vor. Die mentorierte
Arbeit ist Teil des Portfolios der Studierenden.
LiteratureDie Literatur ist themenspezifisch. Sie muss je nach Situation selber beschafft werden oder wird zur Verfügung gestellt.
Prerequisites / NoticeDie Arbeit sollte vor Beginn des Praktikums abgeschlossen werden.
252-0417-00LRandomized Algorithms and Probabilistic MethodsW8 credits3V + 2U + 2AA. Steger
AbstractLas Vegas & Monte Carlo algorithms; inequalities of Markov, Chebyshev, Chernoff; negative correlation; Markov chains: convergence, rapidly mixing; generating functions; Examples include: min cut, median, balls and bins, routing in hypercubes, 3SAT, card shuffling, random walks
ObjectiveAfter this course students will know fundamental techniques from probabilistic combinatorics for designing randomized algorithms and will be able to apply them to solve typical problems in these areas.
ContentRandomized Algorithms are algorithms that "flip coins" to take certain decisions. This concept extends the classical model of deterministic algorithms and has become very popular and useful within the last twenty years. In many cases, randomized algorithms are faster, simpler or just more elegant than deterministic ones. In the course, we will discuss basic principles and techniques and derive from them a number of randomized methods for problems in different areas.
Lecture notesYes.
Literature- Randomized Algorithms, Rajeev Motwani and Prabhakar Raghavan, Cambridge University Press (1995)
- Probability and Computing, Michael Mitzenmacher and Eli Upfal, Cambridge University Press (2005)
252-0535-00LAdvanced Machine Learning Information W8 credits3V + 2U + 2AJ. M. Buhmann
AbstractMachine learning algorithms provide analytical methods to search data sets for characteristic patterns. Typical tasks include the classification of data, function fitting and clustering, with applications in image and speech analysis, bioinformatics and exploratory data analysis. This course is accompanied by practical machine learning projects.
ObjectiveStudents will be familiarized with advanced concepts and algorithms for supervised and unsupervised learning; reinforce the statistics knowledge which is indispensible to solve modeling problems under uncertainty. Key concepts are the generalization ability of algorithms and systematic approaches to modeling and regularization. Machine learning projects will provide an opportunity to test the machine learning algorithms on real world data.
ContentThe theory of fundamental machine learning concepts is presented in the lecture, and illustrated with relevant applications. Students can deepen their understanding by solving both pen-and-paper and programming exercises, where they implement and apply famous algorithms to real-world data.

Topics covered in the lecture include:

Fundamentals:
What is data?
Bayesian Learning
Computational learning theory

Supervised learning:
Ensembles: Bagging and Boosting
Max Margin methods
Neural networks

Unsupservised learning:
Dimensionality reduction techniques
Clustering
Mixture Models
Non-parametric density estimation
Learning Dynamical Systems
Lecture notesNo lecture notes, but slides will be made available on the course webpage.
LiteratureC. Bishop. Pattern Recognition and Machine Learning. Springer 2007.

R. Duda, P. Hart, and D. Stork. Pattern Classification. John Wiley &
Sons, second edition, 2001.

T. Hastie, R. Tibshirani, and J. Friedman. The Elements of Statistical
Learning: Data Mining, Inference and Prediction. Springer, 2001.

L. Wasserman. All of Statistics: A Concise Course in Statistical
Inference. Springer, 2004.
Prerequisites / NoticeThe course requires solid basic knowledge in analysis, statistics and numerical methods for CSE as well as practical programming experience for solving assignments.
Students should have followed at least "Introduction to Machine Learning" or an equivalent course offered by another institution.
263-2800-00LDesign of Parallel and High-Performance Computing Information W7 credits3V + 2U + 1AT. Hoefler, M. Püschel
AbstractAdvanced topics in parallel / concurrent programming.
ObjectiveUnderstand concurrency paradigms and models from a higher perspective and acquire skills for designing, structuring and developing possibly large concurrent software systems. Become able to distinguish parallelism in problem space and in machine space. Become familiar with important technical concepts and with concurrency folklore.
Compulsory Elective Courses
Further course offerings from the category Educational Science are listed under "Programme: Educational Science for Teaching Diploma and TC".
» see Compulsory Elective Courses Teaching Diploma
  •  Page  1  of  2 Next page Last page     All