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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
This master's degree is intended for holders of a Bachelor's degree in Computer Science, a Bachelor's degree in Applied Mathematics, or equivalent, with a good level of statistics and matrix calculus. Applications for a Bachelor's degree in Mathematics with computer science skills demonstrated by obtaining specific teaching units in programming and databases are also considered.
Prerequisites for entry into M1: Computer science degree or validation of personal and professional skills (VAPP D. 08/23/1985)
Prerequisites for entry into M2: Master 1 in computer science or Master in applied mathematics with prerequisites in data science, engineering diploma or validation of personal and professional skills (VAPP D. 23/08/1985)
2 Years
Sep
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
Master in Computer Science – Track: Machine Learning for Data Science (MLSD)
Université Paris Cité, Paris, France
24 monthsProgramme duration
Data Science and Artificial IntelligenceMain Subject Area
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:
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:
Admission Requirements
Prerequisites for entry into M1: Computer science degree or validation of personal and professional skills (VAPP D. 08/23/1985)
Prerequisites for entry into M2: Master 1 in computer science or Master in applied mathematics with prerequisites in data science, engineering diploma or validation of personal and professional skills (VAPP D. 23/08/1985)
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
Scholarships to study abroad
Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
Scholarship Applications: Frequently Asked Questions
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