specialized master’s program data science information for ... · department of computer science |...

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Monday, 5 March 2018, 12:15 hCAB G 51

05.03.2018B. Gianesi / G. Fourny 1

Specialized Master’s ProgramData ScienceInformation for ETH Students


Master’s Program Data Science

Master’ Program / Application / Admission for ETH students



Structure Master’s Program Data Science Course Catalog Design Principles Eligibility Application + Documents


Agenda




Agenda


StructureMaster's in Data Science 120

Core Courses and Interdisciplinary Electives 72Core Courses 60

Data Analysis 16Information and Learning 8

Statistics 8

Data Management and Processing 16

Core Electives 10

Interdisciplinary Electives 8

Data Science Lab 14

Seminar 2

Science in Perspective 2

Master's Thesis 30



120 Credit Points

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

Semester 3

30 credits

Semester 4

30 credits


Semester 1

30 CP

Semester 2

30 CP

Semester 3

30 CP

Semester 4

30 CP

4 more semesters of

leeway

Recommended CP / SemesterHard limit at4 years


Program Structure

Master's in Data Science 120



Program Structure

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

Minimum required credit points



Program Structure


Core Courses 60



Core Courses

High level of competence in Data Science

Solid and sound knowledge basis.

Lectures Exercises Self-studying Projects+ + +

Exam+



Program Structure


Core Courses 60Data Analysis 16


Core Electives 10

Information and Learning 8

Statistics 8



Program Structure




Core Electives 10


Statistics 8

Does not sum up:

freedom


18 u

p to

you


Core Courses

Data Analysis: Information & LearningMachine Learning (8)Mathematics of Information (8)

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

Data Management and ProcessingBig Data (8)Algorithmic aspects of Data Science (8)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

At least two here

Data Analysis: Information & LearningMachine Learning (8)Mathematics of Information (8)

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

Data Management and ProcessingBig Data (8)Algorithmic aspects of Data Science (8)Optimization for Data Science (8)

Core ElectivesA lot of choice across CS, Math, EE (30+ courses)



Program Structure




Statistics 8


Core Electives 10


18 u

p to

you



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

Finance & Insurance

Geographic Information Systems

Social Networks

Transportation Systems

Weather and Climate Systems



Program Structure




Statistics 8


Core Electives 10


Data Science Lab 14

18 u

p to

you

4 up

to y

ou



Data Science Lab

Groups of three students + Presentation

Apply your knowledge and skills to

Real Data!Interdisciplinary projects



Program Structure




Statistics 8


Core Electives 10


Data Science Lab 14

18 u

p to

you

4 up

to y

ou

Seminar 2



Seminar

Read and understand publications

Present a research paper

Get involved in discussions



Program Structure




Statistics 8


Core Electives 10


Data Science Lab 14

18 u

p to

you

4 up

to y

ou

Seminar 2




Science in Perspective

Humanities and Social Sciences

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



Program structureMaster's in Data Science 120

Core Courses and Interdisciplinary Electives 72Core Courses 60

Data Analysis 16Information and Learning 8

Statistics 8


Core Electives 10


Data Science Lab 14

Seminar 2


Master's Thesis 30

18 u

p to

you

4 up

to y

ou





Agenda


Course Catalog: «Core Courses»

Data Analysis: Information & Learning (min. 1 Kurs)252-0535-00 Machine Learning HS 8 D-INFK227-0434-10 Mathematics of Information FS 8 D-ITET

Data Analysis: Statistics (min. 1 Kurs)401-3621-00 Fundamentals of Mathematical Statistics HS 10 D-MATH401-3632-00 Computational Statistics FS 10 D-MATH

Data Management and Processing (min. 2 Kurse)263-3010-00 Big Data HS 8 D-INFKNew Algorithmic Aspects of Data Science HS 8 D-INFK261-5110-00 Optimization for Data Science FS 8 D-INFK



Part of vvz SS18: «Core Electives»



Interdisciplinary Electives: Example

Atmosphäre & Klima701-0412-00 Klimasysteme 3 D-USYS701-0473-00 Wettersysteme 3 D-USYS701-0023-00 Atmosphäre 3 D-USYS

701-1251-00 Land-Climate Dynamics 3 D-USYS

701-1252-00 Climate Change Uncertainty and Risk: From Probabilistic Forecasts to Economics of Climate Adaptation

3 D-USYS

701-1226-00 Inter-annual Phenomena and their Prediction 3 D-USYS





Agenda


Solid and sound knowledge in analyizing and handling ofbig data

Specialized knowledge in a research area First experience in handling real data

Design Principles Master in Data Science





Agenda


Qualifying Bachelor’s Programs Bachelor in Electrical Engineering and Information

Technology Bachelor in Computer Science Bachelor in Mechanical Engineering Bachelor in Mathematics Bachelor in Physics

Eligibilty





Agenda


Specialized Master‘s program

Bologna admission period: 1 - 31 march 2018

Application & Admission, AS 2018

Even ETH bachelor’s students have to apply



Documents Online application tool (fill in, print & sign)

ETH transcript: printed from mystudies Official transcripts of other study programs and mobility CV

GRE General Test Recommandation letters

ETH Bachelor’s students are waived Language test Application fee

Application Documents



Website with information material

Admission without any additional requirements

Gaps in Statistics, analysis, linear algebra Programming Databases, data modelling

are expected to be filled in self-study

Admission Principles

Excellent track record



Data Science:https://www.inf.ethz.ch/de/studium/master/master-ds.html Study guide Regulations of study Recommended reading …

Admission office:https://www.ethz.ch/en/studies/registration-application/master/application.html


Information

https://www.inf.ethz.ch/de/studium/master/master-ds.html

https://www.ethz.ch/en/studies/registration-application/master/application.html


Studies administration:Bernadette GianesiOffice CAB F [email protected]

Program coordination:Dr. Ghislain [email protected]


Information

mailto:[email protected]

mailto:[email protected]