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Year 2 Timetable

Tracks in semester 3 : 2015-2016

The first semester of MSIAM master 2 is essentially divided in 4 tracks. Each student should be registered in one of the following tracks:

However a personalized track may also be build for some students from the available courses (if no timetable conflicts appears). The personalized tracks must be approved by the Professors in charge of MSIAM.

Academic courses:

  • 30 ECTS scientific courses (3 or 6 each).
  • 3 ECTS language course (French or English).
  • 6 ECTS may be chosen by the students outside of the MSIAM offer (needs no timetable conflict and an approvement by the MSIAM head)

Modeling and Scientific Computing (MSC)

Geometry, Image and CAD (GICAD)

Statistics (STAT)

“I keep saying the sexy job in the next ten years will be statisticians.” said Hal Varian (Google’s Chief Economist).

Statistics has a strong presence today in many areas: Telecommunications ( the needs of subscribers a package of mobile telephony), Medical / Pharmaceutical (statistics used to quantify uncertainty and, ultimately, improve the health of patients.) Banking / Insurance (statisticians are indispensable when it comes to control risk), Environment, Marketing / Advertising …

The purpose of this Master is to train high-level researchers in statistics by providing theoretical foundations and applied methodology. The theoretical courses are followed by an internship in a research lab or company.

Proposed courses:

Data Science (DS)

The burst of data collection at unprecedented speed and scale in many fields, from biology to astrophysics, demands a paradigm shift in applied mathematics and computer science in order to face the new challenges in scientific modelling and computation.

To harness the power of this data revolution, the world needs academic researchers and professionals called “data scientists” skilled in designing and utilizing automated methods of analyzing it. We have launched a new track in the MSIAM master in order to establish the country’s leading Data Science academic training. Data science is becoming essential to answer some of the big scientific questions and technological challenges of our times: how can we prevent cancer and find better cures for diseases? how does the brain work? how can we design an artificial intelligence?

Data science lies at the crossroad of mathematics (pure and applied), statistics, computer science and an increasingly large number of application domains.

Proposed courses:

Global list of courses

tracks-old.txt · Last modified: 2016/06/29 15:27 by jbdurand
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