Data Science Master |
Core Courses |
Data Analysis |
Information and Learning |
Number | Title | Type | ECTS | Hours | Lecturers |
---|
227-0434-10L | Mathematics of Information | W | 8 credits | 3V + 2U + 2A | |
227-0434-10 V | Mathematics of Information | | | 3 hrs | | H. Bölcskei |
227-0434-10 U | Mathematics of Information | | | 2 hrs | | H. Bölcskei |
227-0434-10 A | Mathematics of Information | | | 2 hrs | | H. Bölcskei |
|
Statistics |
Number | Title | Type | ECTS | Hours | Lecturers |
---|
401-3632-00L | Computational Statistics | W | 8 credits | 3V + 1U | |
401-3632-00 V | Computational Statistics
On 18 April 2019 the course takes place in HG E 3. | | | 3 hrs | | M. H. Maathuis |
401-3632-00 U | Computational Statistics
A "Präsenzstunde" directly following the exercises will be offered Friday 11-12 in HG F 3. | | | 1 hrs | | M. H. Maathuis |
|
Data Management |
Number | Title | Type | ECTS | Hours | Lecturers |
---|
261-5110-00L | Optimization for Data Science | W | 8 credits | 3V + 2U + 2A | |
261-5110-00 V | Optimization for Data Science | | | 3 hrs | | B. Gärtner,
D. Steurer |
261-5110-00 U | Optimization for Data Science | | | 2 hrs | | B. Gärtner,
D. Steurer |
261-5110-00 A | Optimization for Data Science | | | 2 hrs | | B. Gärtner,
D. Steurer |
|
Core Electives |
Number | Title | Type | ECTS | Hours | Lecturers |
---|
151-0566-00L | Recursive Estimation | W | 4 credits | 2V + 1U | |
151-0566-00 V | Recursive Estimation
The lecture starts in the second week of the semester. | | | 2 hrs | | R. D'Andrea |
151-0566-00 U | Recursive Estimation
The exercise starts in the second week of the semester. | | | 1 hrs | | R. D'Andrea |
227-0150-00L | Systems-on-chip for Data Analytics and Machine Learning Previously "Energy-Efficient Parallel Computing Systems for Data Analytics" | W | 6 credits | 4G | |
227-0150-00 G | Systems-on-chip for Data Analytics and Machine Learning | | | 4 hrs | | L. Benini |
227-0420-00L | Information Theory II | W | 6 credits | 2V + 2U | |
227-0420-00 V | Information Theory II | | | 2 hrs | | A. Lapidoth,
S. M. Moser |
227-0420-00 U | Information Theory II | | | 2 hrs | | A. Lapidoth,
S. M. Moser |
227-0558-00L | Principles of Distributed Computing | W | 6 credits | 2V + 2U + 1A | |
227-0558-00 V | Principles of Distributed Computing | | | 2 hrs | | R. Wattenhofer,
M. Ghaffari |
227-0558-00 U | Principles of Distributed Computing
In Gruppen | | | 2 hrs | | R. Wattenhofer,
M. Ghaffari |
227-0558-00 A | Principles of Distributed Computing
No presence required. Creative task outside the regular weekly exercises. | | | 1 hrs | | R. Wattenhofer,
M. Ghaffari |
252-0211-00L | Information Security | W | 8 credits | 4V + 3U | |
252-0211-00 V | Information Security | | | 4 hrs | | D. Basin,
S. Capkun,
E. Mohammadi |
252-0211-00 U | Information Security | | | 3 hrs | | D. Basin,
S. Capkun,
E. Mohammadi |
252-0526-00L | Statistical Learning Theory | W | 7 credits | 3V + 2U + 1A | |
252-0526-00 V | Statistical Learning Theory | | | 3 hrs | | J. M. Buhmann |
252-0526-00 U | Statistical Learning Theory | | | 2 hrs | | J. M. Buhmann |
252-0526-00 A | Statistical Learning Theory | | | 1 hrs | | J. M. Buhmann |
252-0538-00L | Shape Modeling and Geometry Processing | W | 5 credits | 2V + 1U + 1A | |
252-0538-00 V | Shape Modeling and Geometry Processing | | | 2 hrs | | O. Sorkine Hornung |
252-0538-00 U | Shape Modeling and Geometry Processing | | | 1 hrs | | O. Sorkine Hornung |
252-0538-00 A | Shape Modeling and Geometry Processing | | | 1 hrs | | O. Sorkine Hornung |
252-0579-00L | 3D Vision | W | 4 credits | 3G | |
252-0579-00 G | 3D Vision | | | 3 hrs | | M. Pollefeys,
V. Larsson |
252-3005-00L | Natural Language Understanding Number of participants limited to 200. | W | 4 credits | 2V + 1U | |
252-3005-00 V | Natural Language Understanding | | | 2 hrs | | M. Ciaramita,
T. Hofmann |
252-3005-00 U | Natural Language Understanding | | | 1 hrs | | M. Ciaramita,
T. Hofmann |
261-5130-00L | Research in Data Science Only for Data Science MSc. | W | 6 credits | 13A | |
261-5130-00 A | Research in Data Science | | | 180s hrs | | Professors |
263-0008-00L | Computational Intelligence Lab Only for master students, otherwise a special permission by the study administration of D-INFK is required. | W | 8 credits | 2V + 2U + 3A | |
263-0008-00 V | Computational Intelligence Lab | | | 2 hrs | | T. Hofmann |
263-0008-00 U | Computational Intelligence Lab | | | 2 hrs | | T. Hofmann |
263-0008-00 A | Computational Intelligence Lab
No presence required. | | | 3 hrs | | T. Hofmann |
263-2300-00L | How To Write Fast Numerical Code Number of participants limited to 84.
Prerequisite: Master student, solid C programming skills.
Takes place the last time in this form. | W | 6 credits | 3V + 2U | |
263-2300-00 V | How To Write Fast Numerical Code | | | 3 hrs | | M. Püschel |
263-2300-00 U | How To Write Fast Numerical Code | | | 2 hrs | | M. Püschel |
263-2925-00L | Program Analysis for System Security and Reliability | W | 5 credits | 2V + 1U + 1A | |
263-2925-00 V | Program Analysis for System Security and Reliability | | | 2 hrs | | M. Vechev |
263-2925-00 U | Program Analysis for System Security and Reliability | | | 1 hrs | | M. Vechev |
263-2925-00 A | Program Analysis for System Security and Reliability | | | 1 hrs | | M. Vechev |
263-3710-00L | Machine Perception Number of participants limited to 150. | W | 5 credits | 2V + 1U + 1A | |
263-3710-00 V | Machine Perception | | | 2 hrs | | O. Hilliges |
263-3710-00 U | Machine Perception | | | 1 hrs | | O. Hilliges |
263-3710-00 A | Machine Perception | | | 1 hrs | | O. Hilliges |
263-3826-00L | Data Stream Processing and Analytics | W | 6 credits | 2V + 2U + 1A | |
263-3826-00 V | Data Stream Processing and Analytics | | | 2 hrs | | V. Kalavri |
263-3826-00 U | Data Stream Processing and Analytics | | | 2 hrs | | V. Kalavri |
263-3826-00 A | Data Stream Processing and Analytics | | | 1 hrs | | V. Kalavri |
263-4506-00L | Massively Parallel Algorithms | W | 6 credits | 2V + 1U + 2A | |
263-4506-00 V | Massively Parallel Algorithms | | | 2 hrs | | M. Ghaffari |
263-4506-00 U | Massively Parallel Algorithms | | | 1 hrs | | M. Ghaffari |
263-4506-00 A | Massively Parallel Algorithms | | | 2 hrs | | M. Ghaffari |
263-5215-00L | Fairness, Explainability, and Accountability for Machine Learning Number of participants limited to 40.
The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the course, will officially fail the course. | W | 4 credits | 1V + 2P | |
263-5215-00 V | Fairness, Explainability, and Accountability for Machine Learning | | | 1 hrs | | H. Heidari |
263-5215-00 P | Fairness, Explainability, and Accountability for Machine Learning | | | 2 hrs | | H. Heidari |