Master in Computer Science – Track: Machine Learning for Data Science (MLSD)
24 monthsProgramme duration
SepStarting Month
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
Other
Study Level
Masters
Study Mode
On Campus
Most of the important decisions of business managers, but also of scientists or economists for example, are taken today on the basis of the analysis of massive and multi-view data. These data are at the heart of the functioning of current artificial intelligences. If this data is available in abundance ( Big data ), it is most often in raw form and first requires informed reorganization and preprocessing. Then, an analysis phase, using machine learning methods ( Machine Learning) from artificial intelligence and statistics, is therefore necessary. This is the subject of the work-study Master's degree "Machine Learning for Data Science". This master requires skills in computer science and applied mathematics. In M1, teaching units specific to the fields of machine learning, data science, big data and artificial intelligence are offered. This master also exists in initial training ( FI ) under the name “Machine Learning for Data Science”.
This work-study master's degree aims to:
- Train Data Scientists who master the different machine learning methods (supervised, unsupervised and semi-supervised using different approaches including deep learning) and are capable of designing new methods adapted to the various fields of activity with the aim of extracting knowledge useful for optimizing the company's offers and services.
- Also allow to continue with a thesis in the field of machine learning, artificial intelligence and data science on theoretical and applied subjects in various fields including text-mining, NLP, recommendation and Computer vision.
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
Other
Study Level
Masters
Study Mode
On Campus
Most of the important decisions of business managers, but also of scientists or economists for example, are taken today on the basis of the analysis of massive and multi-view data. These data are at the heart of the functioning of current artificial intelligences. If this data is available in abundance ( Big data ), it is most often in raw form and first requires informed reorganization and preprocessing. Then, an analysis phase, using machine learning methods ( Machine Learning) from artificial intelligence and statistics, is therefore necessary. This is the subject of the work-study Master's degree "Machine Learning for Data Science". This master requires skills in computer science and applied mathematics. In M1, teaching units specific to the fields of machine learning, data science, big data and artificial intelligence are offered. This master also exists in initial training ( FI ) under the name “Machine Learning for Data Science”.
This work-study master's degree aims to:
- Train Data Scientists who master the different machine learning methods (supervised, unsupervised and semi-supervised using different approaches including deep learning) and are capable of designing new methods adapted to the various fields of activity with the aim of extracting knowledge useful for optimizing the company's offers and services.
- Also allow to continue with a thesis in the field of machine learning, artificial intelligence and data science on theoretical and applied subjects in various fields including text-mining, NLP, recommendation and Computer vision.
Admission Requirements
Prerequisites for entry into M1: Bachelor's degree in computer science or validation of personal and professional experience (VAPP D. 23/08/1985)
Prerequisites for entry into M2: Master 1 in computer science or Master in applied mathematics with prerequisites in data science, engineering degree or validation of personal and professional experience (VAPP D. 23/08/1985)
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