AIM - Our programs
Master in Data Science & Artificial Intelligence Strategy
To become a High-Level Expert and strategist in Data Science and AI
The integration of AI and Data Science into business strategies and operations is not merely an advantage but a necessity. Organizations worldwide are increasingly relying on data-driven decision-making to stay competitive, and there is a growing demand for professionals who can navigate and leverage these advanced technologies responsibly and effectively. The Data Science & Artificial Intelligence Strategys specialization is designed to address this critical need by providing cutting-edge, industry-relevant curriculum that blends technical expertise, strategic thinking, and ethical considerations.
By joining the Master in Data Science & Artificial Intelligence Strategy, students will be equipped with the knowledge and skills to become a leader in the AI and Data Science landscape.
- Strategic Thinking: Develop the ability to formulate and implement AI strategies that drive business objectives effectively and responsibly
- Technical Proficiency: Master advanced Data Science techniques, Machine Learning algorithms, Large language models, Cloud computing, Big Data
- Ethical Awareness: Learn to navigate the ethical, legal, and societal implications of AI, ensuring responsible adoption of technology.
- Global Perspective: Gain international exposure through seminars and studies in different countries, enhancing your ability to operate in diverse business environments.
- Practical Application: Engage in hands-on projects, internships, and collaborations with industry partners to apply theoretical knowledge to real-world scenarios.
Master in Digital Marketing & Data Analytics
To become a highly skilled specialist in data-driven digital marketing
Today’s organizations generate vast amounts of data through various customer interaction channels and emerging technologies.
In the dynamic world of digital marketing, mastering data-driven decision-making isn't just advantageous, it's essential. At a strategic level, creating and implementing digital marketing strategies involves undertaking the crucial task of establishing effective data governance, examining the proper use and potential misuse of data, and considering the legal and ethical frameworks to shape marketing campaigns.
The Master in Digital Marketing & Data Analytics addresses these challenges and aims to empower future marketing professionals to design effective marketing strategies by transforming and analyzing data into powerful insights:
- Projects Leadership: Lead and manage analytical and marketing projects
- Ethical and Responsible Data Use: Understand the legal and ethical frameworks to build marketing campaigns
- Marketing Analytics Techniques: Learn methods such as cluster analysis, conjoint analysis, linear and logistic regression, time series analysis to improve your marketing mix,
- Business Intelligence tools: Transform data into visual insights to guide decision-makers thanks to Power BI or Tableau
- Technical Proficiency: Master marketing platforms such as Google Analytic for tracking, Meta for Business or Google ads for advertising as well as programming tools such as R or Python
Data-driven tracks in the Master in Management – Grande Ecole program (MiM)
The Master in Management – Grande Ecole program at emlyon business school offers a wide range of courses focused on data science challenges and techniques. It includes introductory courses in business intelligence/analytics, artificial intelligence, the Python programming language, and machine learning. To go further, in collaboration with the ODAI department, the program has developed two specialized tracks, "Data Analyst" and "AI," designed for students aiming for careers that require these skills.
Executive modules: AI for Business
Our artificial intelligence training program provides managers and executives with the skills needed to transform companies’ strategic decisions. By combining theory and practice, participants will learn to identify AI needs, set achievable objectives, prioritize useful data, and develop effective models.
