{"id":5005,"date":"2020-02-18T15:34:33","date_gmt":"2020-02-18T14:34:33","guid":{"rendered":"http:\/\/ensai.fr\/?page_id=5005"},"modified":"2020-02-18T16:44:35","modified_gmt":"2020-02-18T15:44:35","slug":"2nd-year-engineer-statistician-curriculum","status":"publish","type":"page","link":"https:\/\/ensai.fr\/en\/etudier-a-lensai\/2nd-year-engineer-statistician-curriculum\/","title":{"rendered":"2nd-Year Engineer Statistician Curriculum"},"content":{"rendered":"

International students with low levels in French can study in English during the second semester of the second year for 30 ECTS credits. All teaching units or electives available in English are noted with an asterisk (*).<\/p>\n

The second year of study is composed of fundamental and optional elective courses including advanced theoretical topics in Statistics. Second-year courses carry on from the first-year studies with a combination of introductory and in-depth classes. While some courses are compulsory and form the core syllabus, others are chosen as options to enable students to begin specializing in one of the principal domains in which Statistics is used. Students make their choices on the basis of their intended third-year specialization. They learn the techniques essential for their future professions as statisticians, including classes in high-level computer language. Students learn to apply their wide range of knowledge acquired during their first two years of study through group projects (Project in Statistics, Computer Science Project), using real-world data. These projects are led by professionals as well as academics.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Semester 1<\/strong><\/td>\nTotal Hours<\/td>\nECTS<\/td>\n<\/tr>\n
UE 2-01\u00a0: STATISTICAL MODELING<\/strong><\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nMultivariate Regression<\/td>\n33<\/td>\n3<\/td>\n<\/tr>\n
<\/td>\nGLM & Regression of categorical variables<\/td>\n33<\/td>\n3<\/td>\n<\/tr>\n
<\/td>\nTime Series 1<\/td>\n33<\/td>\n3<\/td>\n<\/tr>\n
<\/td>\nTotal UE 2-01<\/em><\/td>\n99<\/td>\n9<\/td>\n<\/tr>\n
UE 2-02\u00a0: COLLECTION & LEARNING<\/strong><\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nSupervised Learning<\/td>\n27<\/td>\n2,5<\/td>\n<\/tr>\n
<\/td>\nSampling Theory<\/td>\n30<\/td>\n3<\/td>\n<\/tr>\n
<\/td>\nLaw and Data Ethics<\/td>\n6<\/td>\n0,5<\/td>\n<\/tr>\n
<\/td>\nTotal UE 2-02<\/em><\/td>\n63<\/td>\n6<\/td>\n<\/tr>\n
UE 2-03\u00a0: IT FOR DATA SCIENCE<\/strong><\/td>\n<\/td>\n<\/td>\n<\/tr>\n
\u00a0<\/strong><\/td>\nIntermediate Computer Science<\/td>\n18<\/td>\n2<\/td>\n<\/tr>\n
\u00a0<\/strong><\/td>\nComputer Science Project<\/td>\n36<\/td>\n4<\/td>\n<\/tr>\n
<\/td>\nRemedial IT (Transfer\/Exchange students only)<\/td>\n21<\/td>\n1<\/td>\n<\/tr>\n
<\/td>\nTotal UE 2-03<\/em><\/td>\n54<\/td>\n7<\/td>\n<\/tr>\n
UE 2-04\u00a0: ECONOMIC MODELING<\/strong><\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nMicroeconomic Modeling<\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nApplied Econometrics<\/td>\n33<\/td>\n3<\/td>\n<\/tr>\n
<\/td>\nTotal UE 2-04<\/em><\/td>\n54<\/td>\n5<\/td>\n<\/tr>\n
UE 2-06\u00a0: HUMANITIES<\/strong><\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nFrench as a Foreign Langauge<\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nEnglish<\/td>\n30<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nTotal UE 2-06<\/em><\/td>\n51<\/td>\n4<\/td>\n<\/tr>\n
TOTAL 1ST SEMESTER<\/strong><\/td>\n345<\/strong><\/td>\n31<\/strong><\/td>\n<\/tr>\n
Semester 2<\/strong><\/p>\n

UE 2-07\u00a0: STATISTICS PROJECT*<\/strong><\/td>\n

<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nStatistics Project*<\/td>\n33<\/td>\n5<\/td>\n<\/tr>\n
<\/td>\nTotal UE 2-07<\/em><\/td>\n33<\/td>\n5<\/td>\n<\/tr>\n
UE 2-08\u00a0: INTERMEDIATE STATISTICAL MODELING *<\/strong><\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nSurvival Analysis*<\/strong><\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nNonparametric Statistics<\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nMarkov Chains*<\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nTotal UE 2-08<\/em><\/td>\n63<\/td>\n6<\/td>\n<\/tr>\n
UE 2-09\u00a0: COMPUTATIONAL METHODS *<\/strong><\/td>\n<\/td>\n<\/td>\n<\/tr>\n
\u00a0<\/strong><\/td>\nChoose from: Baysian Calculus or Applied Micro and Macro Econometrics*<\/strong><\/td>\n39<\/td>\n4<\/td>\n<\/tr>\n
\u00a0<\/strong><\/td>\nChoose: OOP with Java*<\/strong> or,
\nC++ for Computational Statistics<\/td>\n		18<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nBig Data Tools*<\/strong><\/td>\n24<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nTotal UE 2-09<\/em><\/td>\n81<\/td>\n8<\/td>\n<\/tr>\n
UE 2-10\u00a0: PRE-SPECIALIZATION*<\/strong><\/td>\n<\/td>\n<\/td>\n<\/tr>\n
\u00a0<\/strong><\/td>\nElective n\u00b01*<\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
\u00a0<\/strong><\/td>\nElective n\u00b02*<\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nElective n\u00b03*<\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nElective\u00a0 n\u00b04*<\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nElective n\u00b05*<\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nTotal UE 2-10<\/em><\/td>\n105<\/td>\n10<\/td>\n<\/tr>\n
UE 2-11\u00a0: HUMANITIES & COMMUNICATION*<\/strong><\/td>\n<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nFrench as a Foreign Language<\/td>\n21<\/td>\n2<\/td>\n<\/tr>\n
<\/td>\nProfessional Project\u00a0 and Project Management*<\/strong><\/td>\n20<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nTotal UE2-11<\/em><\/td>\n41<\/td>\n2<\/td>\n<\/tr>\n
TOTAL 2ND SEMESTER<\/strong><\/td>\n323<\/strong><\/td>\n31<\/strong><\/td>\n<\/tr>\n
TOTAL YEAR<\/strong><\/td>\n\u00a0<\/strong><\/td>\n668<\/strong><\/td>\n62<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

UE 2-10 Elective Courses<\/strong><\/p>\n

Martingales & L\u00e9vy Process
\nAdvanced Regression Models*
\nBootstap
\nTime Series 2*
\nStatistical Mathematics*
\nSampling Theory
\nCartography & Spatial Statistics
\nRisk Economics
\nGrowth Theory
\nDemography
\nFinancial Economics*
\nAdvanced Programming with R
\nContract Economics
\nIndustrial Economics*
\nMobile Technology
\nSignal Processing*
\nSoftware Design
\nData Challenge
\nData Visualization*<\/p>\n","protected":false},"excerpt":{"rendered":"

International students with low levels in French can study in English during…
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