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SUMMER SCHOOLS

 

 

Overview



Summer school, 3 July to 7 July 2023​

AI for Business

Grand Paris Campus


The AI for Business summer school five-day curriculum is targeted to individuals interested in learning about how to apply AI, data science and machine learning with a primary focus on practical application to business. The classes in this summer school will focus on the areas of data science that have made the biggest advances in utility over the last several years, including machine learning models, forecast, optimisation, network science, computer vision and natural language processing. Classes will concentrate on methods that allow algorithms to train effectively and be applied to solve business problems in multiple industries.



Why


The AI for Business summer school will introduce the main techniques, methodologies and ethical business implications associated with data engineering, data exploration, statistical and machine learning models, forecasting, optimisation, network science, computer vision, natural language processing, and model assessment and deployment.

All these topics will be covered from a business application perspective. Topics in modern artificial intelligence such as computer vision and natural language processing will be demonstrated as AI tools to be used in specific business  pplications.

Additionally, the AI for Business summer school will provide hands-on training in the latest data science and machine learning software, both open source and world-class frameworks.



Who should attend the AI for Business summer school


The AI for Business summer school is particularly suited to students as well as academics and practitioners who seek a comprehensive introduction to the proper tools assigned to AI for Business, including data science and machine learning models, along with best practices and real use cases presented by leaders in the field. Leading companies will partner with the AI for Business Summer School to present successful reference customer cases.


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AI for Business course objective


The main goal of the summer school is to provide students a strong foundation in artificial intelligence and its main disciplines like data analysis and exploration, predictive modelling, forecasting, optimisation, and deep learning, but mostly in how to apply AI techniques and models to solve business problems. The summer school is open to non-specialists and gives a solid understanding of AI for business. The summer school will provide hands-on opportunities to develop models and apply them to understand and solve business questions.



Learning outcomes


By the end of the summer school, students will be able to: 

  • Understand different AI techniques and identify which one fits specific business problems best.

  • Know the process associated to the analytical lifecycle.

  • Understand the main algorithms for supervised machine learning.

  • Understand the objectives and techniques for forecasting.

  • Understand the main goals in optimisation models and the different approaches according to the type of business problem to solve.

  • Understand the deep learning models and identify possible business applications for each one of them.

  • Identify the main tasks assigned to the ModelOps, the importance of model assessment and the benefits of monitoring models in production. 

  • Understand the importance of ethics in AI and its consequences in society.

Students can 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.


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