Master of Science Data Artificial Intelligence and Cloud

The production of digital data has continued to increase exponentially in recent years. This ‘Big Data’ arrives at high speed via multiple channels and in various and varied formats. In this raw data, there is value in many sectors such as health, telecommunications, energy, business, security, and many others. Data Science makes it possible to extract this value from data by relying on interdisciplinary skills in mathematics, computer science, artificial intelligence, etc.

But to extract information from ‘Data’ and transform it into knowledge, it would first be necessary to collect it, prepare it and transform it, expose it, then explore it and model it, then visualize it and finally deploy the best models.

On the other hand, the public cloud market has experienced very significant growth in recent years. Cloud solutions (SaaS, ‘Software-As-As Service’, PaaS ‘Platform As As Service’, IaaS ‘Infrastructure as a service’) bring undeniable advantages to accelerate the digital transformation of companies. We can cite: A flexible pricing model (Pay-As-You-Go), a rapid Go-To-Market, a natural scalability. Based on this observation, companies are increasingly looking for cloud skills. Hence the knowledge and mastery of services offered by the well-known cloud providers (Microsoft Azure, Google Cloud Platform, AWS, Alibaba) is becoming more than ever important.

At the end of the MSc ‘Data, Artificial Intelligence and Cloud’, students should be able to accompany companies in their ‘data-driven’ transformation by providing the necessary skills to:

• Exploit big data to improve decision-making strategy and management efficiency and anticipate future trends.
• Collect, store, analyze, transform and protect these masses of multiple and diverse data.
• Design, implement and optimize cloud storage and data processing solutions.

The teachings include integration, processing and engineering of data, the regulations and  governance of data, cloud computing, artificial intelligence.

At the end of this program, students shall be able to:

• Identify business needs and issues related to the exploitation of big data.
• Design and create architectures and infrastructures to collect, prepare and transform data into formats that can be used by data scientists, data analysts and Machine Learning experts.
• Manage the scalability of Big Data infrastructures.
• Ensure data integrity and publish APIs.
• Design, implement and optimize cloud storage and data processing solutions.
• Apply machine learning methods to business data.
• Choose Big Data solutions according to business needs