Course Page ✏️
- Data Analytics
- IF29
- Description
-
Objectives:
Data processing is central to business, particularly when it comes to understanding the market or
decision-making. It involves training in the collection, processing and understanding of
of data
Learning Outcomes:
-Modelling a complex problem to translate it into a value chain (Collection, Storage,
Analytics, Visualisation)
-collect and prepare data (cleaning, exploration, dimension selection) for Machine Learning
Machine Learning algorithms
-identify and formulate a Machine Learning problem
-identify the relevant algorithms for processing and visualisation
-dimensioning resources for a processing chain to solve a complex problem
-ensure the scalability of processing to meet the challenges of large volumes and variability in Big Data Analytics projects - ECTS credits
- 6
- Teaching Language
- Français
- Exam Language
- Français
- Support Materials Language
- Français/English
- Basic Learning Outcomes
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- Estimate resource requirements for bandwidth, processing, storage, energy or addressing based on specified traffic and service assumptions.(B-TN11.1 - Estimate resource requirements for bandwidth, processing, storage, energy or addressing based on specified… - TEB - Estimate resource requirements for bandwidth, processing, storage, energy or addressing based on specified traffic and service assumptions.)
- Resize resources or reconfigure parameters to meet defined quality and efficiency targets.(B-TN11.3 - Resize resources or reconfigure parameters to meet defined quality and efficiency targets. - TEB - Resize resources or reconfigure parameters to meet defined quality and efficiency targets.)
- Course categorized
- Managing Entity (faculty)
- Telecommunications and Networks ( UTT)