Objectives of Programme's Learning Outcomes

• Mobilise a structured set of scientific knowledge and skills and specialised techniques in order to carry out computer and management engineering missions, with a focus on Innovation and Information Systems, using their expertise and adaptability.
• Master and appropriately mobilise knowledge, models, methods and techniques related to the improvement of decision and management processes, mastery of mathematical modelling and optimisation algorithms, analysis of large volumes of data, mastery of Web and multimedia tools, design and operation of distributed and mobile computing systems, management of a software project, innovative management of a company and/or project team, information systems (data mining, database, cloud computing, etc.) and management of technological innovation.
• Assess the validity of models and results in view of the state of science and characteristics of the problem.
• Plan, manage and lead projects in view of their objectives, resources and constraints, ensuring the quality of activities and deliverables.
• Define and align the project in view of its objectives, resources and constraints.
• Communicate and exchange information in a structured way - orally, graphically and in writing, in French and in one or more other languages - scientifically, culturally, technically and interpersonally, by adapting to the intended purpose and the relevant public.
• Use and produce scientific and technical documents (reports, plans, specifications) adapted to the intended purpose and the relevant public.
• Adopt a professional and responsible approach, showing an open and critical mind in an independent professional development process.
• Exploit the different means available in order to inform and train independently.
• Contribute by researching the innovative solution of a problem in engineering sciences.
• Collect and analyse data rigorously.
• Adequately interpret results taking into account the reference framework within which the research was developed.

Learning Outcomes of UE

analyze a time serie with ANOVA models, and provide a critical analysis of the result

UE Content: description and pedagogical relevance

univariate time series (decomposition: trend, seasonality, cyclic component); ARIMA models and Box-Jenkins methodology; exponential smoothing; overview of multivariate time series.

Prior Experience

Not applicable