Master of Informatics – University of Bordeaux France

The Internet of Things is the next technological revolution. IoT makes it possible to extend the Internet to all objects of the physical world that until now was disconnected from the digital world. It opens new opportunities and perspectives: it is an area of rapid growth and a huge opportunity. Indeed, all everyday objects will be potentially connected: it goes from televisions, watches, cars, bicycles, clothing, heating system, to buildings, etc. The peculiarity of IoT is to have a multidisciplinary cross-cutting impact, and in fact, the IoT affects many industrial sectors such as aerospace, aviation, telecommunications, agriculture, health, automobile, railway, building, energy, city, home automation, smart environments (ie, smart space, smart building, and smart city).

In this context, this course aims to provide the foundations for designing and building connected objects. In particular, it covers the key principles and tools to achieve this aim. It addresses embedded systems, the Raspberry Pi Platform, and the Arduino environment for building devices that can control the physical world. Each student will be given an ESP32 microcontroller with wireless network interface enabled. Students will have the opportunity to design completely their own IoT device with a range of hardware and electronics components. Further, the different software frameworks dedicated to IoT will be studied to design complex and connected IoT applications. Security risks related to IoT devices will also be introduced.

The main Data Mining techniques will be addressed during this course. More precisely, association rules, classification (or, supervised learning) and clustering (or, unsupervised learning). The main objective for the students is (i) to be able to identify which kind of knowledge (association vs classification model vs segmentation) is needed depending on the practical problem they are faced and (ii), the pros and limitations of each technique. Practical exercises will be performed using free software like Weka or Rapidminer.

Training objectives:

– The design of systems and software can be made more reliable through the use of formal methods. The course is a pragmatic approach to the formal design from case studies and proven techniques: proof, refinement and model checking.

Acquired skills :

– Capacity of abstraction of system’s behaviors (hardware and software) for verification of functional and / or dysfunctional properties.

– Capacity of abstraction and logical reasoning about data, instructions and sequences of instructions in order to prove software correctness.

Mastering the design of distributed software architectures, based on the object programming paradigm.

Discovering the various steps in the analysis, design and development of information systems. Emphasis is on reusability and extend ability.

This course gives an overview of the main design patterns, classical or more specific, used in the design of distributed software architectures, either in the design of AP I s or f or the design of software components.

The goal of this course is to give students an overview of development methods used in the software industry, of the situations in which these methods apply, and the pros and cons of each of them .

Different types of software, and influence of the software type on the available choices for development methods (graphical application, library, realtime system , etc).

In depth study of an agile method. Notions of responsility, test-driven development, tandem programming, usage scenarios.

After taking this course, students must be able to select a development method from those in use in the software industry, depending on the type of application to be developed (graphical application, information system, real time software, etc), the acceptable rate of flaws in the final product, and the relationship between provider and client

From 4 to 6 months internship. It can be realized either in a company or in research laboratory.