Welcome to the Department of Computer Science...Broad Spectrum of Topics in Research and Education...

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Welcome to the Department of Computer Science

Professor Ueli MaurerDirector of Studies

14 September 2020

Department ofComputer Science

14.09.2020Department of Computer Science 2

Core Faculty Data Science

Broad Spectrum of Topics in Research and Education

Data Management

Machine Learning

Information Security

Probability theory

Insurance mathematics, stochasticfinance

Programming Languages

Statistics

Parallel Computing

Visual Computing

Computer Engineering

System Security

Mathematical Information Science

…und many more

Signal processing

ETH among top 5 Universities for Computer Science in 2020

Rank 2020 Institution Country

1 University of Oxford United Kingdom

2 Stanford University United States

3 ETH Zurich Switzerland

4 Massachusetts Institute of Technology United States

5 University of Cambridge United Kingdom

Source: https://www.timeshighereducation.com/world-university-rankings/2020/subject-ranking/computer-science

Start your own Company

Department of Computer Science 14.09.2020 5

46 Academic ETH Spin-offs founded since 1993

D-INFK Master Programs

MSc Data Science

MSc Cyber Security

57 newstudents

MSc Computer Science

Take advantage of the unique opportunity of studying at ETH

Attend classes, interact with TAs and faculty

Make this not only a degree, but a major step in your career

Self-reflection

Some Advice

Getting startedMaster‘s Program in Data Science

Department ofComputer Science

Who’s who

B. Gianesi / G. Fourny 9

Who’s who

Master's programin Data Science

Computer Science

Mathematics

Electrical Engineering

ETH has 16 departments,identified with four letters

(D-AAAA)

A joint program accross three departments

Who’s who

Prof. David BasinHead of Department

Prof. Ueli MaurerDirector of StudiesExamination regulationsValidation of examinationresults

Bernadette GianesiStudies AdministrationMain point of contactbernadette.gianesi@inf.ethz.ch

Dr. Ghislain FournyStudy CoordinatorQuestions on planning your studiesand course cataloggfourny@inf.ethz.ch

Tutors (Core Data Science Faculty)

...and many more Professors who can supervise Master's theses.

Discuss and approve yourpersonal study program

List onhttps://www.inf.ethz.ch/studies/master/master-ds/faculty.html

Contact via e-mail

The Master’s Program

Study Guide

We recommend:Read it!

• ECTS credits (European Credit Transfer System)

• Course completed successfully full amount of credits is awarded

• 30 credits per semester

Master’s program: 120 credits

Credit System

120 Credit Points

The master’s program is designed to be completed within 4 semesters. The overall study duration must not exceed 8 semesters. The last semester focuses completely on the Master’s thesis.

Semester 3

30 credits

Semester 4

30 credits

Semester 1

Semester 2

Semester 3

Semester 4

4 more semesters of

leeway

Recommended CP / SemesterHard limit at4 years

• Pass: grade ≥ 4• Fail: grade < 4• Resolution for individual grades: 0.25

Repetition of examsEvery examination or project can be repeated once.

Grading System

6 Very good5 Good4 Sufficient3 Insufficient2 Poor1 Very poor

Master's in Data Science 120Core Courses and Interdisciplinary Electives 72

Core Courses 60Data Analysis 16

Data Management and Processing 16

Core Electives 10

Information and Learning 8

Statistics 8

Interdisciplinary Electives 8

Data Science Lab 14Seminar 2

Master's Thesis 30Science in Perspective 2

Master’s Program Structure

Minimum required credit points

Program Structure

Master's in Data Science 120

Program Structure

Core Courses 60

Core courses

High level of competence in Data Science

Solid and sound knowledge basis.

Lectures Exercises Self-studying Projects+ + +

Program Structure

Core Electives 10

Statistics 8

Program Structure

Core Electives 10

Statistics 8

Does not sum up:

freedom

Program Structure

Core Electives 10

Statistics 8

Core courses

Data Analysis: Information & LearningAdvanced Machine Learning (10)Neural Network Theory (4)Mathematics of Information (8)

Data Analysis: StatisticsFundamentals of Mathematical Statistics (10)Computational Statistics (8)

Data Management and ProcessingBig Data (10)Advanced Algorithms (9)Optimization for Data Science (8)

Core ElectivesA lot of choice (30+ courses)

Core courses

Roughly:

At last one here

At least one here

At least two here

Data Analysis: Information & LearningAdvanced Machine Learning (10)Neural Network Theory (4)Mathematics of Information (8)

Data Analysis: StatisticsFundamentals of Mathematical Statistics (10)Computational Statistics (8)

Data Management and ProcessingBig Data (10)Advanced Algorithms (9)Optimization for Data Science (8)

Core ElectivesA lot of choice (30+ courses)

Program Structure

Core Electives 10

Statistics 8

Interdisciplinary electives

Bridge the gap with other disciplinesculturesmindsets

Data Science would not exist without

Data!8-12 credits

Interdisciplinary electives

Course compilations

Computational Biology, Bioinformatics, and Biomedicine

Computer Networks

Finance and Insurance

Geographic Information Systems

Law, Policy, and Innovation

Neural Information Processing

Social Networks

Transportation Systems

Weather and Climate Systems

Program Structure

Core Electives 10

Statistics 8

Program Structure

Core Electives 10

Statistics 8

Program Structure

Core Electives 10

Statistics 8

Data Science Lab 14

Data Science Lab

Groups of three students + Presentation

Apply your knowledge and skills to

Real Data!

Interdisciplinary projects

Program Structure

Core Electives 10

Statistics 8

Data Science Lab 14

Seminar 2

Seminar

Read and understand publications

Present a research paper

Get involved in discussions

Program Structure

Core Electives 10

Statistics 8

Data Science Lab 14Seminar 2Science in Perspective 2

Science in Perspective

Humanities and Social Sciences

Language courses 851-xxxx-xx(≤ 3 credits including ETH BSc)

Coordinator's pick:Big Data, Law, and Policy

Program Structure

Core Electives 10

Statistics 8

Data Science Lab 14Seminar 2

Master's Thesis 30Science in Perspective 2

Master's Thesis

This is the final step!

6 months of researchand complex problemsolving

(And think about your future... maybe a PhD?)

General recommendations

• Stick to 30 credits per semester (don't overload)

• Start with the core courses

• Data Science Lab after interdisciplinary courses, ideally in same field

At least 8 CP must habe been obtained under Data Analysis and 8 CP under Data Management. Interdisciplinary courses are not mandatory to have been taken priorto Data Science Lab

Exchange programs

Prof. Dr. Bernd Gärtner

(No credits for "core core" courses and Data Science Lab)

Dr. Claudia Otto

• Only for students with a ETH bachelor degree

• Not in the first semester

Plan your studies

Select a tutor

First, contact the professor you would like as a tutor.

Select a tutor

Create your learning agreement

First, meet your tutor and discuss your study plan.

Fill your learning agreement

Submitting your learning agreement

Submit your learning agreement after discussing with your tutor.

Submitting your learning agreement

Academic Year

R. Sasse / B. Gianesi 51

Autumn Semester

examination registration

(until end of 4th

course registration (until end of 2nd week)

beginning of term end of term

term term brake

end of term examinations session examinations

deregistration end of term

examinations

deregistration session

examinations

Spring Semester

course registration (until end of 2nd week)

end of term examinations session examinations

deregistration end of term

examinations

deregistration session

examinations

examination registration

(until end of 4th

end of term

• Important deadline (course registrations, exam registration and deregistration, etc.) are always announced ahead of time via e-mail xxxx@student.ethz.ch

• Make sure you read your e-mails!

Deadlines

• Solve the exercises during the semester

• Solve old examinations (available from the student body, i.e. VIS)

• Oral examinations: Get minutes of former examinations from VIS

• If you have questions, ask your fellow students or the assistants

Preparing Examinations

highly, highly, highly recommendedto attend all lectures and exercise sessions

Course times

3 pm – 4 pm

actually means

3:15 pm – 4:00 pm

G. Fourny 56

• At ETH Zentrum (here): Classes start a quarter past the indicated hour.

• On Hönggerberg Campus: depends on exact building course is in! see https://ethz.ch/students/en/studies/academic-support/course-catalogue/lectures-times.html

• Also check https://ethz.ch/students/en/studies/academic-support.html for general information – including lecture recording links, etc

• Autumn semester 2020: The lecturers will communicate the exact lesson times of ONLINE courses.

Exam times

3 pm – 4 pm

really means

3pm – 4pm

This does not apply to exams, meetings, etc.

G. Fourny 57

Student Portal

https://ethz.ch/students/en.html

All the best for your studies

Welcome to the Department of Computer Science...Broad Spectrum of Topics in Research and Education...

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