Summer schools

Summer school 2024
AI for Business
​July 8 - 11, 2024
Montreal, Canada

The 4-day curriculum in the AI for Business Summer School is targeted to individuals interested in learning how to apply AI, data science and machine learning to business The lectures will focus on the areas of data science that have made the most useful advances over the last several years, including machine learning models, forecasting, optimisation, computer vision and natural language processing. The classes will be organised around AI applications that have been developed to solve business problems in multiple industries.

Why

The training provides a comprehensive immersion into the field of AI, enabling participants to develop a profound understanding of the concepts, models, and emerging technologies that underpin this discipline.

• ​By integrating practical exercises with an open-source platform, participants can apply the theoretical concepts learned. This promotes a concrete understanding and the ability to apply this knowledge in professional contexts.
• Interacting with AI experts allows participants to benefit from practical advice and gain unique perspectives. These exchanges contribute to broadening their vision and understanding industry best practices. Visits to renowned companies provide a unique opportunity to observe the successful implementation of AI in real professional environments. This allows participants to draw practical lessons and inspire their own initiatives.
• ​The training also addresses aspects of AI governance and highlights the fundamental importance of data quality. These topics are becoming increasingly essential in the effective management of AI projects and the creation of reliable and responsible systems.
• In addition, cultural activities and networking moments will foster an atmosphere conducive to informal exchanges. Participants will have the opportunity to share ideas, build professional connections, and explore potential collaborations.

Who should attend the AI for Business summer school

The AI for Business summer school will be equally suited to students, members of academia and novice practitioners who seek a comprehensive introduction to the proper AI tools for business, including data science and machine learning models, along with best practices and use cases. Leading companies will aprtner with the AI for Business Summer School to present successful reference customer cases.

AI for Business course objective

The main goal of the summer school is to provide participants with a strong foundation in Artificial Intelligence and its main disciplines like data analysis and exploration, predictive modeling, forecasting, optimization, and deep learning. Open to non-specialists, the summer school will provide hands-on opportunities to develop models and apply them to understand and solve business questions.

Learning outcomes

Overall, the summer school provides a holistic learning experience, equipping participants with a combination of technical expertise, practical skills, ethical considerations, and a mindset for innovation, all of which are essential for success in the dynamic field of artificial intelligence.

Participants will be able to:

• Develop comprehensive understanding of AI concepts, models, and emerging technologies.
• Apply theoretical knowledge in real-world scenarios, enhancing their ability to implement AI solutions.
• Leverage AI systems for quicker and more informed decision-making in various business contexts.
• Develop a heightened awareness of ethical considerations in AI development and deployment,
• contributing to responsible AI practices.
• Enhance interpersonal skills, networking abilities, and the capacity to collaborate with professionals in the AI industry.

Exposure to diverse AI applications, visits to leading companies, and the exploration of Montreal's cultural environment will also stimulate adaptability and innovation, encouraging participants to think creatively and apply AI in novel ways.

Participants who successfully complete this summer school will be awarded a certificate from SKEMA. Those demonstrating excellence in their performance will be eligible to receive recommendation letters.

Students have the possibility to get transferable credits (2 ECTS). Students need to consult their home institute to validate credits transfer.

Teaching methods

• Lectures.
• Hands-on development.
• Workgroup tasks and discussions.​