Robot | Path | Permission |
GoogleBot | / | ✔ |
BingBot | / | ✔ |
BaiduSpider | / | ✔ |
YandexBot | / | ✔ |
Sitemap: http://www.mmmef.fr/sitemap.xml User-agent: NerdyBot Disallow: / User-agent: * Disallow: /ajax/ Disallow: /apps/ |
Title | Master 2 MMMEF - |
Description | Master 2 MMMEF: Modélisation et Méthodes Mathématiques en Economie et Home Curriculum Timetable Opportunities Application About Contact Master 2 MMMEF: Modélisation et Méthodes Mathématiques en Economie et Finance A Maste |
Keywords | N/A |
WebSite | mmmef.fr |
Host IP | 199.34.228.74 |
Location | United States |
Site | Rank |
mef-sarl.com | 22,946,974 |
Euro€467,348
Dernière mise à jour: 2022-06-06 07:35:55
mmmef.fr a un classement mondial Semrush de 22,647,627. mmmef.fr a une valeur estimée à € 467,348, sur la base de ses revenus publicitaires estimés. mmmef.fr reçoit environ 53,925 visiteurs uniques chaque jour. Son serveur Web est situé au United States, avec l'adresse IP 199.34.228.74.Selon SiteAdvisor, mmmef.fr est sûr à visiter. |
Valeur d'achat/vente | Euro€467,348 |
Revenus publicitaires quotidiens | Euro€432 |
Revenus publicitaires mensuels | Euro€12,942 |
Revenus publicitaires annuels | Euro€155,304 |
Visiteurs uniques quotidiens | 3,595 |
Remarque: Toutes les valeurs de trafic et de revenus sont des estimations. |
Host | Type | TTL | Data |
mmmef.fr. | A | 21597 | IP: 199.34.228.74 |
mmmef.fr. | NS | 21600 | NS Record: ns2.lws-hosting.biz. |
mmmef.fr. | NS | 21600 | NS Record: ns1.lws-hosting.biz. |
Home Curriculum Timetable Opportunities Application About Contact Master 2 MMMEF: Modélisation et Méthodes Mathématiques en Economie et Finance A Master 2 program in Paris city center The Master 2 MMMEF (Modélisation et Méthodes Mathématiques en Economie et Finance) is a Master’s program delivered at Université Paris 1 Panthéon-Sorbonne . With a wide variety of courses, all taught in English, the program aims at training high level specialists in financial mathematics, financial engineering, mathematical economics, game theory, optimization, control theory, data science, machine learning, and operations research. The program is divided into 4 tracks (see below) which are interrelated in terms of (i) the mathematical tools and concepts involved, and (ii) practical applications in the industry. The courses cover a large range of mathematical techniques going from analysis, to probability, to optimization, to decision making, to statistics and machine learning, and cover both |
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