Dipl么me d鈥檃nalyse digitale et intelligence d'affaires

脌 propos de ce programme

Credit

Lancez votre carri猫re dans le monde florissant du commerce en ligne. En acqu茅rant une formation compl猫te en programmation informatique et en marketing num茅rique, vous d茅montrez aux employeurs que vous poss茅dez ce qu鈥檌l faut pour obtenir d鈥檈xcellents r茅sultats dans le march茅 en ligne actuel.

搁茅蝉耻濒迟补迟蝉

Le programme est con莽u pour vous permettre de :

cr茅er des sites Internet avec un contenu dynamique;
concevoir, 茅laborer, r茅aliser et lancer un projet professionnel sur Internet;
concevoir des applications logicielles;
茅laborer un plan de marketing num茅rique;
quantifier et analyser des campagnes de marketing num茅rique;
comprendre la recherche pay茅e, l鈥檕ptimisation des moteurs de recherche et la promotion en ligne;
optimiser l鈥檈xp茅rience du consommateur sur une plateforme num茅rique.

Crit猫res d鈥檃dmission

Les participants doivent d茅tenir un baccalaur茅at d鈥檜ne universit茅 reconnue obtenu dans une universit茅 reconnue avec une moyenne pond茅r茅e cumulative minimale de 3,0/4,0 ou 3,2/4,0 au cours des deux derni猫res ann茅es d鈥櫭﹖udes universitaires 脿 temps plein.

Le candidat aux programmes D茅veloppement de carri猫re et perfectionnement professionnel des 2e ou 3e cycles doit 锚tre comp茅tent en anglais.

Courses & Workshops

Credit Courses

Cours associ茅s

CMS2 500 Mathematics for Management. (3 credits)

Automne 2019, Hiver 2020, Printemps/脡t茅 2020

Basic mathematics needed for business applications, including graphs of functions, series summation, mathematics of finance, annuity, discounted cash flow, internal rate of return, permutations, combinations, maxima and minima of functions with business applications in optimization, introductory statistics and probability

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Cours obligatoires

CCS2 505 Programming for Data Science. (3 credits)

Tools and techniques for designing and implementing software applications by using modern programming languages relevant to data science.

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CMIS 530 Digital Analytics and Targeting. (3 credits)

Covers fundamental techniques in measuring and analysing the digital marketing experience success and effectiveness as well as using audience data to improve advertising and content using targeting and experiments. How to measure, analyze, and act upon the evolving internet technologies and trends.

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CMIS 543 Digital Customer Experience. (3 credits)

Covers the fundamental techniques for understanding, analyzing and optimizing customer experience on digital platforms. Explores best practices in designing and optimizing conversion actions in an online business. Management of customer data and confidentiality.

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CMIS 544 Digital Marketing Automation, Planning and Technology. (3 credits)

Covers the fundamental concepts needed to develop a digital marketing plan. Enables students to gain an understanding of market behaviour, translation of corporate goals into digital marketing objectives, basic overview of various strategic approaches to align to objectives, as well as implementation and control.

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CMIS 545 Cloud Computing Architecture. (3 credits)

Covers different cloud infrastructures and architectures in the context of deployed cloud computing systems that are appropriate for different businesses. Enables students to use key business metrics to make decisions on the suitability of applications for cloud deployment.

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CMIS 549 Digital Media and Search Engine Optimization. (3 credits)

Covers the fundamentals of promoting a brand through digital mediums and how to take advantage of earned digital media. Provides an understanding of how paid search, search engine optimization, various forms of digital media planning and placement, social media promotion work and, how to monitor and optimize performance.

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CMIS 550 Fundamentals of Big Data. (3 credits)

Investigates big data鈥檚 enabling technologies; compares big data to traditional data models; and explores how big data enables applications such as data mining and deep learning.

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CMS2 505 Quantitative Analysis Tools in Decision Making. (3 credits)

This course provides applications-oriented operations research modeling tools, such as: linear programming, integer programming, network modeling, and queuing theory. Use of spreadsheet/modeling software is an integral part of this course.

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CMS2 527 Business Intelligence and Analytics. (3 credits)

This course provides a managerial and technical focus on computational and business techniques which can help to identify new business opportunities and transform an organization鈥檚 future by optimizing operational and strategic decision making.

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CMS2 529 Introduction to Data Analytics. (3 credits)

Focuses on executing statistical methods on data sets for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results in support of business decision making.

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Contacts

D茅veloppement de carri猫re et perfectionnement professionnel

info.conted@mcgill.ca

T茅l.: +1 514-398-6200

Fax: +1 514-398-3108

680, rue Sherbrooke Ouest, bureau聽1140 Montr茅al, Qu茅bec, Canada聽聽H3A 2M7

Horaires d'ouverture

Du lundi au vendredi
de 9聽h 脿 17聽h

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