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Cours scientifiques - HEC-MIE666D : Data et IE

Domaine > Management, Innovation et Entrepreneuriat.

Descriptif

Programme
Data Science and Artificial Intelligence impact the way we do business. Consequently, companies’
business models are affected regardless of their market, sector or size. This introductory course allows
managers to understand key concepts in Data Science and Artificial Intelligence relevant to their
business and enables them to work efficiently in the future with Data Scientists and Data Engineers.
INTENDED LEARNING OBJECTIVES
At the end of the course, participants should:
• Know key concepts in Data Science and Artificial Intelligence for Business
• Be familiar with the basics of coding in Python for simple Machine Learning Algorithms.
Important: this course is not a Coding course on Data Science.
• Understand how to work efficiently with their future Data Scientists and Data Engineers
colleagues
• Be able to further increase their knowledge on the topic, on their own, after the course, by
accessing during 6 months for free the DataCamp online learning platform and its more than
300 exercises on Data Science
COURSE STRUCTURE
Pre-course Preparation (8 hours maximum)
Using a free access to the DataCamp platform (online web access and an App for exercises):
• A first online course «Introduction to Python» to learn the basics of Python: 4 hours, 11 videos,
57 exercises
• A second online course «Intermediate Python»: 4 hours, 18 videos and 87 exercises
• By experience, it should take students less than 4 hours per course until full completion
• Waivers are available for this part of the course (depending on student’s actual level in Python)
Session 1 (3 hours) - Data Science and AI for Business
• Concepts of Data Science, AI, Machine Learning, Deep Learning, coding...
• Business use cases
• Examples in R and Python
• Managing Data and Data Organization in companies
• Main Business usages of Machine Learning
• Examples of different types of algorithms: Regression, Classification, Clustering...
• Use of a Machine Learning Platform to experiment the Machine Learning Pipeline
Session 3 (3 hours) - Deep Learning
• Key concepts of Deep Learning
• Main Business usages of Deep Learning
• Examples of different types of algorithms: Regression, Classification...
• Use of a Machine Learning Platform to experiment some Deep Learning Algorithms
• Governance, Ethics and Data Organization
Session 4 (3 hours) – Data for Strategic Decision
• Presentation of an efficient methodology to manage the «Data Project» of companies
• Experiment the methodology on a Business case, working in teams organized according to
students’ Business expertise domain
In addition, a conference will take place with a Data Scientist in order to share his/her experience as a
professional working in Data.
Post course activity
Participants will have access for free during 6 months to the Datacamp Platform proposing more than
300 excellent courses on Python, R and SQL, plus some introduction courses to Git, Scala, Shell...
Total duration
Total duration of the course depends on the possibility to get a waiver for Python coding courses and
participants’ willingness to learn more by themselves on the DataCamp platform after the course:
• Minimum : 12 hours
• Normal: 20 hours
• Possible: no limit... more than 1000 hours of courses are available on DataCamp!
HEC 654 - Data science and AI for strategic decisions
Vincent Fraitot : fraitot@hec.fr
Professeur HEC
13
TEACHING METHODS
Students should complete «Introduction to Python» and «Intermediate Python» courses on DataCamp
platform.
Participants will work in groups on different business cases related to Data Science.
GRADING
Evaluation will take into account the following:
• Completion of the two online Python courses (possibility to get a waiver)
• Quality of the project group works
• Presence and active participation during the sessions
Grading method: Evaluation on A-F scale.
BIOGRAPHY
Vincent Fraitot | Associate Professor - Education Track | HEC Paris
Vincent Fraitot has over 30 years of experience managing new technologies, Digital and Data in
international and multicultural organizations.
At HEC Paris, he holds the role of Scientific Director of the Master Data Science for Business, in
partnership with Ecole Polytechnique. He is the Founder and Director of the Data for
Management Certificate. He also manages the Digital Transformation Consulting Academy and
has been co-creator and co-director of the Digital Transformation Certificate.
He is Managing the Natixis-Ecole Polytechnique-HEC Chair on «Data for banking» and he holds
the role of Pedagogy Coordination Director for HEC Paris at the Hi!Paris Center.
His rich background offers him significant expertise that he shares in the classroom. After
obtaining a Master of Science in Artificial Intelligence in Edinburgh, he contributed to the
development of the High-Tech affiliate of a successful Software House. Positions as CIO and
Organization Director for Europe at Pernod Ricard provided him with strong operational
experience in New Information and Communication Technologies.
After an Executive MBA from HEC Paris, he co-founded a consulting firm to assist Managing
Directors in their digital and data projects, in particular in the Luxury industry.
He served as the Managing Director of vente-privee consulting, the consulting affiliate of
Veepee, where he supported international brands and groups in their digital transformation,
both in B2C and B2B.As a Partner at KéaEuclyd, a consulting company specialized in Digital
Strategy, he helped top executives develop their businesses.
He has been an independent consultant in Digital and Data Strategy since Sept. 2017.
Vincent Fraitot teaches Data Science & Artificial Intelligence for Business, Digital and data
Transformation, Business Models, Business Plan, eCommerce for Luxury, Marketing and Digital
Marketing as an Associate Professor in the Strategy & Business Policy Department of HEC Paris,
where he teaches students in programs from the “Grande Ecole”, MBA, EMBA and Executive
Education.

Diplôme(s) concerné(s)

Format des notes

Numérique sur 20

Littérale/grade réduit

Pour les étudiants du diplôme M2 Projet, Innovation, Conception

L'UE est acquise si Note finale >= 10
  • Crédits ECTS acquis : 3 ECTS
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