• Motivation for Agile development
  • Microsoft Visual Studio tools and programming languages (C, C++, C#, WPF, Java)
  • Python language and specific tools for Big Data analysis and Machine Learning algorithms (Tensor Flow, Keras, Scikit-Learn, NumPy, Pandas)


  • Complementary and overlapping skills to run the software activity
  • Foundations of real-time software development
  • Problem optimization through operative research approach
  • Big data management and Machine Learning techniques
  • Predictive Analytics and Clustering Models
  • Technologies and Algorithms for Artificial Intelligence applications (Neural Networks, Linear/Polynomial Regressions, Logistic Regression, K-Means)


  • Tools : Languages, development tools , source & version management, bug tracking, planning
  • Software Architecture
  • Hardware platforms
  • Description and development of the different bricks of the software
  • Integration test
  • Software Quality Assurance
  • Configuration management and software versioning control
  • IT infrastructure administration
  • Participation to the Agile rituals


  • Global architecture including inter-modules communication (OPC UA)
  • HMI/UI : parametrization and reporting
  • Database storage, contextualisation and management
  • Real time including supervision, controls and alarms
  • IA kernel : implementation of rules
  • AI/Machine Learning approach to problem solving
  • Data acquisition, formatting and analysis
  • Low level software: hardware interfaces, PLC connection

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