Master of Science MSc and M.Sc In – MSc Data Science & Business Analysis
BAC +5WORK-STUDY AND ENGLISH COURSE
About
Our MSc – Data Science & Business Analysis combines a technical and business approach. Its purpose is therefore to put data analysis and big data at the service of “business” and “strategic” decision-making in fields as diverse as marketing, operations management and finance.
The participants will thus acquire an in-depth knowledge of the latest methods for structuring, analyzing and visualizing data, enabling them to solve business problems.
EDC Paris Business School’s DNA, represented by experience-based pedagogy by means of projects or missions, will naturally be privileged.
Objectives
→ To develop basic big data skills
→ To convey the management tools specific to the data processing, analysis and visualization industries
→ To impart management tools specific to the data processing, analysis and visualisation industries.
→ To make data scientists true business partners
Career opportunities
→ Marketing Science Director
→ Consultant DATA
→ Chief Data Officer
→ Audit Manager
→ Chef de Projet Data
→ Data Analyst
→ Consultant Pilotage & Business Intelligence
At the completion of this degree course, each participant will have acquired skills in the 4 interconnected fields of data science:
→ Information Systems & Computing: use of management software, databases
→ Mathematics & Statistics: Data Analysis, Machine Learning et Data Science
→ Business & Fields of expertise: project management, marking, finance and operational excellence
→ Communication & Impact: data visualization, communication skills and cross-functional management
1st and 2nd years in English and in initial alternating work experience (3 weeks in the company and 1 week in class)
Program is labelised MSc (Master of Science) by the “Conférence des Grandes Ecoles”
Tuition fees
→ September 2022: Master 1 and 2: €26 500 / Master 2 €15 900
Appointment or phone call back
Appointment
Participate in an event
Event
Master Data Science & Business Analysis
Program
1st year - Semester 1
→ Ethics and solidarity
→ Corporate finance
→ Strategic diagnosis of the company
→ Management information system and project management
→ Entrepreneurial ecosystem
→ Self actualization
→ Business English
1st year - Semester 2
→ Probability and statistics for data science
→ Mathematics for data science
→ Excel and data analysis
→ SQL and database operations
→ Introduction to the programming language python
→ Professional and career effectiveness
→ Business English
2nd year - Semester 3
→ Tools of business analytics I
→ Tools of business analytics II
→ Machine learning (level 1)
→ Big data stakes and tools
→ Advanced python
→ Data visualization and storytelling
→ Research methodology
→ Professional and career effectiveness
→ Business English
2nd year - Semester 4
→ Finance for analytics and data science
→ Marketing for analytics and data science
→ Operational excellence for analytics and data science
→ Machine learning (level 2)
→ Research methodology
→ Professional and career effectiveness
→ Action seminar – Hackathon
→ Business English
Assessment procedures
Students are evaluated in many different ways throughout their course:
→ Exams are specific to the teaching cycle:thereafter, students are evaluated mainly through case studies, role-plays and project presentations.
→ Each placement requires a report to be written demonstrating that the relevant skills have been acquired.
→ In the 5th year, students submit an End of Studies Thesis (EST) and defend it before a jury composed of two professors. The validation of the EST is one of the requirements for the diploma.
More generally, we use the following six levels of cognitive skill to evaluate our students:
→Understand: quizzes, pairing exercises, etc.
→ Recognise / Know: quizzes, pairing exercises, etc.
→Apply: (practical exercises, simulations, etc.)
→Analyse: (problem-solving, case studies, etc.)
→Evaluate: (case studies, critiques, etc.)
→Create: (projects, etc.)
Professors award bonus points for active participation in class or in remote sessions when students contribute to a discussion forum.
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