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Master n+ ENSAI Mathematics (Applied), Statistics

Options:
Risk Management and Financial Engineering
Quantitative Marketing and Customer Relationship Management (CRM)
Health Econometrics
Advanced Statistical Engineering
Statistical and Decision-Making Systems
Biostatistics

Titre officiel
Diplôme d'ingénieur de l'Ensai en statistiques

Site web de l'école
http://www.ensai.fr
Programme

Pré-requis de la formation
Bachelor (minimum)

Type de formation
Formation initiale

Langue d'enseignement
Option M1 M2
Risk Management and Financial Engineering Français Français
Quantitative Marketing and Customer Relationship Management (CRM) Français Français
Health Econometrics Français Bilingue Français et Anglais
Advanced Statistical Engineering Français Bilingue Français et Anglais
Statistical and Decision-Making Systems Français Français
Biostatistics Français Bilingue Français et Anglais

La partie M1 est enseignée par
L'établissement : ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information

La partie M2 est enseignée par
L'établissement : ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information

Mots clés
Data mining, IT.Information tech/eng, Finance, Risk, Surveying, Business Intelligence, Biomedical, Health, Health, Biomedical, Signal and image processing, Quality, Mathematics (Applied), Statistics
Partie M1

Lieux
ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information
ENSAI
Campus de Ker Lann
Rue Blaise Pascal - BP 37203
35172 Bruz Cedex
France

Coût académique moyen constaté hors assurance du M1
1800 euros

Description M1
The second year of study (M1) is made up of fundamental and optional courses involving advanced theories in statistics. Second-year classes carry on from the first-year studies with a combination of introductory and in-depth classes. Some form the core syllabus, and others are taken as options to enable students to start specializing in one of the principal fields in which statistics is used by choosing their classes during the second semester. Statistical engineering students make their choices on the basis of their intended third-year specialization. The students learn the techniques essential for their future profession as statisticians and also have specific classes in high-level computer language. Applied work group projects permit the students to apply, from real-life data, a wide range of knowledge acquired during the first two years of study. These projects are closely followed and monitored by professionals and academics alike.

The end of the M1 year leads to the Applied Statistical Internship lasting at least 8-12 weeks, starting in June. Students write up a 10-15 page report on this internship on which their work experience is assessed. This report provides a reasoned presentation of the statistical methods used and the principal results.This report provides a reasoned presentation of the statistical methods used and the principal results. This internship must be carried out within a current market competitive company, a public or private research centre or a government organisation or administration. The objective of the internship is to ensure the practical application of the theoretical teachings. The following are examples of internship themes: statistical analysis and SAS programming; the development of statistical tools for the evaluation of nutritional programs on test; clinical data management and statistical analysis; credit card analytics; statistical software development for generalized linear and non-linear mixed models.

Note: the first semester of the ENSAI's 2nd year (M1) is highly adapted to each n+i student and is modified on an individual basis and therefore changes with each student. It also will include FLE (francais comme langue etrangere) courses.

Bourses M1
Foreign students through n+i may be eligible for the scholarships available from the "n+i" Network (Bni). Other than those, there are also some possibilities: • International students are entitled to an accommodation allowance (APL/ALS) from the French government to help with the cost of rent. • Gustave Eiffel scholarships from the French government (BGF) for international students admitted to a degree awarding program and showing proof of outstanding academic performance (application deadline in December). • French Embassy scholarships program: For more information contact the local French Embassy. When other foreign students (non-n+i students) come to ENSAI, other grants or scholarships they may receive come from their home country and/or sending institution (if they're studying abroad temporarily from another university or engineering school).


Période 1
September - January Langue Heures* Crédits*
Note: tout ou partie du M1-Période 1 sera remplacée par un package "n+i" spécialement conçu pour les élèves étrangers. Voir le Package d'Intégration Méthodologique (PIM) pour plus d'informations.
or
Core
LINEAR MODELS fr 45.50 5.00

TIME SERIES en 37.00 4.00

MULTIVARIATE DATA ANALYSIS fr 40.00 3.50

SAMPLING THEORY fr 39.50 3.50

SUPPORTING COURSES FOR COMPUTER SCIENCE PROJECT fr 5.50 1.00

COMPUTER SCIENCE PROJECT fr 6.50 4.00

ECONOMETRICS fr 39.50 5.00

ANOVA fr 17.00 2.00

ENGLISH en 30.00 2.00

Période 2
January - May Langue Heures* Crédits*
or
Core
PROJECT IN STATISTICS fr 12.50 5.00

GENERALIZED LINEAR MODELS AND REGRESSION ON CATEGORICAL DATA fr 19.50 2.00

MISSING DATA fr 10.00 1.00

COMPUTERIZED STATISTICAL INFERENCE fr 35.50 3.00

SURVIVAL ANALYSIS fr 19.50 2.00

IT AND COMMUNICATION TECHNOLOGIES fr 10.00 1.00

PROGRAMMING IN C++ fr 19.50 2.00

R AND C++ fr 10.00 1.00

NONPARAMETRIC ECONOMETRICS fr 20.00 2.00

ECONOMIC INFORMATION AND DECISIONS fr 20.00 2.00

HUMANITIES COURSE #1 fr 20.00 1.00

HUMANITIES COURSE #2 fr 20.00 1.00

PROFESSIONAL PREPARATION fr 12.50 1.00

APPLIED STATISTICAL INTERNSHIP TO BE COMPLETED IN FRANCE OR ABROAD (2-3 months beginning in June; 5 credits to appear on following year's grade transcript; hours listed are an approximation and will depend on internship requirements) fr 300.00 5.00

Elective courses, choose 3 in "ELECTIVE COURSES (CHOOSE 3, KEEPING IN MIND NOT ALL WITH BE COMPATIBLE TOGETHER FOR SCHEDULING REASONS) (Key: CS = Computer Science, E = Economics, S = Statistics)"
FINANCE (E) fr 20.00 2.00

MARKETING (E) fr 20.00 2.00

HEALTHCARE SYSTEMS (E) fr 20.00 2.00

STRATEGIES AND MARKETS (E) fr 15.50 2.00

MOBILE TECHNOLOGIES (CS) fr 20.00 2.00

VISUAL BASIC PROGRAMMING USING EXCEL (CS) fr 20.00 2.00

ADVANCED REGRESSION MODELS (S) fr 19.50 2.00

MARKOV CHAINS - MIXED MODELS (S) en 20.00 2.00

MARTINGALES AND LEVY PROCESS (S) fr 20.00 2.00

DISCRIMINANT ANALYSIS (S) fr 29.50 2.00


* Les heures de cours indiquées peuvent être soumis à de légères variations.
* Plus d'informations sur les crédits ECTS.
Partie M2

Lieux
ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information
ENSAI
Campus de Ker Lann
Rue Blaise Pascal - BP 37203
35172 Bruz Cedex
France

Coût académique moyen constaté hors assurance du M2
1800 euros

Description M2
The third year of study (M2) seeks to provide students with a genuine specialization while at the same time introducing them to the professional world. Most of the teachers are from the professional sector, giving students an introduction to the sort of problems they will handle after graduation. This introduction is completed by professional seminars which are held throughout the year to complement theoretical classes. The following six specialisations are offered : Risk Management and Financial Engineering, Quantitative Marketing and Customer Relationship Management (CRM), Health Econometrics, Advanced Statistical Engineering, Statistical and Decision-Making Systems, and Biostatistics. These specializations allow students to specialize in one area of advanced statistical applications.

At the end of the third year (M2), the End-of-studies Internship adds a new professional dimension to the students' scientific studies and is the final step that allows students to obtain their degree. Beginning in April and lasting 5 to 6 months, this internship enables the students to apply what they have learned in their third, specialized year of studies (M2). Students work in the statistical, I.T., or economics departments of public or private companies in France or abroad, and learn how to draw on what they have learned and discover their future professional environment. Students write up a report on this period and then have an oral defense in November. The jury, or examining board, then decides whether or not to validate their internship on the basis of the report from the president of the jury.

Bourses M2
Foreign students through n+i may be eligible for the scholarships available from the "n+i" Network (Bni). Other than those, there are also some possibilities: • International students are entitled to an accommodation allowance (APL/ALS) from the French government to help with the cost of rent. • Gustave Eiffel scholarships from the French government (BGF) for international students admitted to a degree awarding program and showing proof of outstanding academic performance (application deadline in December). • French Embassy scholarships program: For more information contact the local French Embassy. When other foreign students (non-n+i students) come to ENSAI, other grants or scholarships they may receive come from their home country and/or sending institution (if they're studying abroad temporarily from another university or engineering school).


Période 1
September - March Langue Heures* Crédits*
or
Core
PROJECT MANAGEMENT fr 10.00 1.00

CORPORATE LAW fr 10.00 1.00

ENGLISH en 30.00 2.00

COMMUNICATION (OPTIONAL) fr 5.00 0.00

HUMANITIES COURSE (OPTIONAL) fr 20.00 0.00

Majeure à choisir
or
Option : Advanced Statistical Engineering
NONLINEAR MODELING fr 19.50 1.00

EXTREME VALUE THEORY fr 21.00 1.00

ADVANCED FINANCIAL ENGINEERING MODELS fr 14.00 1.00

MODERN METHODS OF PARAMETRIC STATISTICS en 10.00 1.00

MARKOVIAN MODELS FOR IMAGE ANALYSIS fr 25.50 1.50

IMAGE ANALYSIS PROJECT fr 14.00 1.50

STATISTICS OF STOCHASTIC PROCESSES fr 20.00 2.00

LINEAR AND NONLINEAR FILTERING fr 11.50 1.00

GEOSTATISTICS fr 11.50 1.00

SEMIPARAMETRIC FORECASTING fr 13.00 1.00

STATISTICAL QUALITY CONTROL en 20.00 2.00

DURATION MODELS fr 10.00 1.00

DESIGN OF EXPERIMENTS fr 14.00 1.00

RISK MANAGEMENT AND OPERATION SAFETY (presence required but does not award student with any credits) fr 6.00 0.00

RELIABILITY fr 25.50 2.00

MODERN STATISTICAL LEARNING fr 15.50 2.00

NEURAL NETWORKS fr 8.50 1.00

GRAPHICAL MODELING UNDER THE BAYESIAN PARADIGM fr 15.50 1.00

FINAL YEAR PROJECT (IN MARCH AT ENSAI) fr 11.50 2.00

METHODOLOGICAL RESEARCH PROJECT en 7.00 2.00

PROFESSIONAL SEMINARS (presence required but does not award student with any credits) fr 36.00 0.00

or
Option : Biostatistics
NONLINEAR MODELING fr 11.50 1.00

ADVANCED BAYESIAN STATISTICS fr 11.50 1.00

STATISTICS OF STOCHASTIC PROCESSES fr 10.00 0.50

COMPARTMENTAL MODELING fr 10.00 0.50

DESIGN OF EXPERIMENTS fr 17.00 1.50

MIXED MODELS fr 22.50 1.50

SURVIVAL ANALYSIS APPLIED TO BIOSTATISTICS fr 22.50 1.50

MEASURING QUALITY OF LIFE fr 15.50 1.00

SEQUENTIAL METHODS IN CLINICAL TRIALS fr 22.50 1.00

MISSING DATA en 11.50 0.50

META ANALYSIS en 15.50 1.00

CLINICAL TRIALS fr 20.00 1.00

PHARMACOMETRICS fr 11.50 0.50

PROJECT IN CLINICAL TRIALS en 22.50 2.50

ECONOMIC EVALUATION IN HEALTH CARE fr 20.00 1.00

QUANTITATIVE EPIDEMIOLOGY fr 20.00 1.00

EPIDEMIOLOGY WORKSHOP fr 17.00 1.00

HEALTH AND ENVIRONMENTAL TOPICS PROJECT fr 22.50 2.50

GENOMICS fr 17.00 0.50

GENETICS PROJECT fr 17.00 2.50

METHODOLOGICAL RESEARCH PROJECT fr 22.50 2.50

PROFESSIONAL SEMINAR (SENSORY STUDIES) (presence required but does not award student with any credits) fr 12.00 0.00

or
Option : Health Econometrics
ECONOMETRIC ANALYSIS OF PANEL DATA fr 20.00 2.00

ADVANCED MICROECONOMETRICS fr 20.00 2.00

FORECASTING USING TIME SERIES fr 20.00 2.00

SURVEY METHODOLOGY fr 17.00 1.00

DISCRETE CHOICE MODELS fr 14.00 1.00

HIERARCHICAL LINEAR MODELS fr 14.00 1.00

VALUING HEALTH en 20.00 1.50

HEALTH ECONOMICS fr 30.00 2.00

HEALTH INSURANCE fr 20.00 1.50

ECONOMIC EVALUATION IN HEALTH CARE fr 24.00 2.00

CLINICAL TRIALS (presence required but does not award student with any credits) fr 10.00 0.00

QUANTITATIVE EPIDEMIOLOGY fr 20.00 1.00

EPIDEMIOLOGY WORKSHOP fr 17.00 1.00

MEASURING QUALITY OF LIFE fr 15.50 1.00

META ANALYSIS en 15.50 1.00

HEALTH ECONOMETRICS PROJECT fr 14.00 3.00

ECONOMIC EVALUATION PROJECT fr 14.00 3.00

PROFESSIONAL SEMINARS (presence required but does not award student with any credits) fr 10.00 0.00

or
Option : Quantitative Marketing and Customer Relationship Management (CRM)
DATA MINING fr 22.50 2.00

SCORING TECHNIQUES AND METHODS fr 22.50 1.00

SURVEY METHODOLOGY fr 17.00 1.00

GEOMARKETING fr 22.50 2.00

STATISTICAL LEARNING fr 27.00 3.00

FORECASTING USING TIME SERIES fr 20.00 2.00

DURATION MODELS fr 15.50 1.00

EXPERIENTIAL MARKETING fr 20.00 2.00

CONSUMER BEHAVIOR MODELS fr 26.00 2.00

PSYCHOMETRICS fr 10.00 1.00

CUSTOMER RELATIONSHIP MANAGEMENT en 17.00 1.00

ADVANCED MICROECONOMETRICS fr 28.00 2.00

ECONOMETRIC ANALYSIS OF PANEL DATA fr 20.00 2.00

DISCRETE CHOICE MODELS fr 14.00 1.00

MARKET MODELS fr 10.00 1.00

METHODOLOGICAL RESEARCH PROJECT fr 11.50 2.00

MARKETING STRATEGY SIMULATION: MARKSTRAT CHALLENGE (presence required but does not award student with any credits) fr 11.50 0.00

CAREER CONFERENCES (presence required but does not award student with any credit) fr 37.00 0.00

PROFESSIONAL SEMINARS (DATA MINING METHODS AND SOFTWARE, MARKETING AND SURVEYS, SOCIAL PSYCHOLOGY OF CONSUMER BEHAVIOR) (presence required but does not award student with any credits) fr 31.00 0.00

or
Option : Risk Management and Financial Engineering
ADVANCED MICROECONOMETRICS fr 20.00 1.00

ADVANCED TIME SERIES fr 22.50 2.00

BANKING RISK MANAGEMENT fr 20.00 2.00

SCORING TECHNIQUES AND METHODS fr 24.00 2.00

EXTREME VALUE THEORY fr 15.50 1.00

STATISTICS OF EXTREME RISKS fr 14.00 2.00

COPULAS THEORY fr 5.50 1.00

STATISTICS OF MULTIPLE RISKS fr 10.00 2.00

ASSET ALLOCATION fr 24.00 2.00

QUANTITATIVE STRATEGIES fr 17.00 1.00

STATISTICS OF HEDGE FUNDS en 8.50 1.00

SOCIALLY RESPONSIBLE INVESTMENT fr 15.50 1.00

STOCHASTIC CALCULUS fr 24.00 2.00

CALIBRATION OF STOCHASTIC PROCESSES fr 15.50 1.00

YIELD CURVES MODELS fr 22.50 1.00

NUMERICAL METHODS fr 24.00 2.00

ADVANCED FINANCIAL ENGINEERING MODELS fr 14.00 1.00

ADVANCED SCORING METHODS en 10.00 0.50

MICROSTRUCTURE AND TRADING ALGORITHMS INTRODUCTION fr 10.00 0.50

PROFESSIONAL SEMINARS (presence required but does not award student with any credits) fr 51.00 0.00

or
Option : Statistical and Decision-Making Systems
DATA MINING fr 22.50 1.50

DATA MINING PROJECT fr 10.00 1.00

DATA MINING METHODS AND SOFTWARE (presence required but does not award student with any credits) fr 14.00 0.00

NEURAL NETWORKS fr 8.50 1.00

STATISTICAL LEARNING fr 27.00 2.00

RELATIONAL AND OBJECT-ORIENTED DATABASES fr 10.00 1.00

SECURITY AND ADMINISTRATION OF DATABASE MANAGEMENT SYSTEMS fr 19.50 1.50

DATABASE TUNING AND DATABASE TAGGING (presence required but does not award student with any credits) fr 11.00 0.00

ADVANCED OBJECT DESIGN MODELS fr 14.00 1.00

SOFTWARE ENGINEERING fr 19.50 1.50

NETWORKS AND SYSTEMS fr 28.00 2.50

DATA SECURITY fr 15.50 2.00

XML fr 18.00 1.00

WEB SEMANTICS fr 21.50 1.50

J2EE PROJECT fr 10.00 1.00

WEB APPLICATIONS (J2EE) fr 21.50 2.00

FINAL YEAR PROJECT fr 17.00 2.50

BIBLIOGRAPHIC STUDY en 3.00 1.00

FOLLOWING THE EVOLUTION OF TECHNOLOGY THROUGH THE MEDIA fr 5.50 1.00

PROFESSIONAL CAREER PREPARATION fr 17.00 1.00

PROFESSIONAL SEMINARS (GEOGRAPHICAL DATA, BIOINFORMATICS) (presence required but does not award student with any credits) fr 14.00 0.00

Période 2
April - September Langue Heures* Crédits*
or
Core
END-OF-STUDIES INTERNSHIP TO BE COMPLETED IN FRANCE OR ABROAD (5-6 months from April through August/September. Oral defense of Internship Report in November. Hours listed are an approximation and will depend on internship requirements.) fr 500.00 25.00


* Les heures de cours indiquées peuvent être soumis à de légères variations.
* Plus d'informations sur les crédits ECTS.