MSc Data Science and Artificial Intelligence The job opportunities are endless


Aims choice Master of Data Science To train students to design, build and deploy infrastructures and systems responsible for collecting, storing, analyzing and interpreting data appropriately within evolving application contexts.

About MSc Data Science

He presents Master of Data Science A two-year program of high-level theoretical and practical studies in the new field of data science. It includes a combination of courses, lab sessions, research projects, and internships. This training will give you a solid foundation in mathematics (Statistics Probabilities, Optimization), Computer Science (Algorithms, Complexity, Databases) with an emphasis on statistical learning and related disciplines (Signal processing, images, graphs, and networks).

During this training, several internships will take place each year in research and development departments or in academic research laboratories.

This master program provides a two-year high-level theoretical and practical curriculum in the new and trendy field of data science. It includes a combination of courses, lab sessions, research projects, and internships.

The Master of Data Science will give you a solid grounding in mathematics (statistics, probability, optimization), computer science (algorithms, complexity, databases) as a basis for a very high knowledge of machine learning and applications (signal processing, images, graphs and networks…).

Students will spend several months training each year. Training will be conducted in research and development departments or in academic research laboratories. They are part of this two-year program.

Data Science Masters Courses

Software development and testing:

  • big data level
  • The blockchain
  • data and virtual
  • Data science
  • machine learning
  • business malaise

Web design and development technologies:

  • Open Data: Actors and Technologies
  • CNIL, data law, copyright, image rights and intellectual property.

Information Systems Management:

  • rotation
  • Individual training
  • Professional certifications

Targeted skills in MSc Data Science

  • High scientific level in data science andartificial intelligence with a very good machine learning culture, mathematical foundations (optimization, probability, statistics) and computer science (effective implementation of algorithms);
  • eligibility for research and/or development activities in the laboratory or in industry;
  • Design and implement data science methods.
  • High level of knowledge and know-how in Data Science and Artificial Intelligence, with a very good culture of machine learning, mathematical foundations (optimization, probability, statistics) and computer science (effective implementation of algorithms);
  • eligibility for research and/or development activities in the laboratory or in industry;
  • Design and implement data science methods.

Data scientist assignments after graduation

On a daily basis, a data scientist analyzes data (numeric, audio or visual cues, images, metadata, etc.) After analyzing it, the data scientist formulates his conclusions which he presents to the public administration or to his client.

Its analyzes have different functions: it can look for new areas for improvement, growth levers, but also identify new uses and operating patterns or even measure the scope of a recently undertaken project.

To carry out their tasks, a data scientist uses different skills and handles different tools. For data analysis, it can in particular opt for machine learning (a subclass of artificial intelligence) which allows it to predict future trends from the data collected. This is what sets it apart from a data analyst who uses more Excel, SQL, or pandas (Python library to process data more easily for analysis).

The data scientist also knows different programming languages ​​for formulating and executing queries: Python, C/C++, SQL… Finally, he has many other skills such as intellectual curiosity, communication skills, analytical ability and rigor…

What do you do after MSc Data Science?

The Master of Data Science allows students to easily integrate into the world of work, particularly in industry. Generally, graduates work in research and development departments of large companies or innovation-related start-ups. You have several career options:

  • Data Scientist/Engineer
  • Designer/Developer of Big Data Analytics and Management Architecture
  • Application manager
  • Application integration
  • Data engineer
  • Data analyst
  • Database Administrator
  • Big data manager
  • Big Data Application Designer/Developer
  • Research and development engineer
  • ……

However, further studies cannot be ruled out. After obtaining a master’s degree in data science, you can obtain a doctoral degree and thus join the research sector.

common questions

What is data science?

Data science is the process of using tools and techniques to extract actionable information from huge amounts of noisy data. Data science is used for everything from business decision making to mathematical analytics to insurance risk assessment.

What is the nature of the work of a data scientist?

Data scientists are the ones who deal with big data, collecting and analyzing large sets of structured and unstructured data. The data scientist role combines computer science, statistics, and mathematics. They analyze, process and model data and then interpret the results to create actionable plans for businesses and other organizations.

Data scientists are analytical experts who use their skills in both technology and the social sciences to find trends and manage data. They use industry knowledge, contextual understanding, and question current assumptions – to uncover solutions to business challenges.

A data scientist’s work usually involves making sense of messy and unstructured data, from sources like smart devices, social media feeds, and emails that don’t quite fit into a database.

What will you need to study Master of Data Science ?

information technology (IT) is an indispensable pillar of modern society. We are now witnessing an information technology revolution, at its center “big data” and deep learning, where we are creating, collecting, storing, and processing data at rates exponentially higher than what is sustainable.

This training offers a mixed profile, who must have a strong background in Maths andStatistics But also proficient Information technology majors or infrastructures needed to manage and process data. Its job is to arouse curiosity and a thirst for understanding the workings of the sector in which it operates. The aim of this Master is to prepare you to become the data scientists of tomorrow, both in the academic world and in the industrial world.

This training is Master of Data Science Students to pursue PhD studies in disciplines such as Imagery, Computer Vision, Machine Learning, Big Data, Cloud and finally Smart Business. The MSc program provides you with a comprehensive education, from foundations to implementation, from algorithms to database architecture, and from information theory to machine learning.

What is the difference between a data analyst and a data scientist?

Data Analyst, as its title suggests, has a role in analyzing data. The Data Scientist goes above and beyond, with business experience and skills in “Data

Why hire a data scientist?

Data science offers the potential to stimulate business growth through the use and exploitation of data. Data science projects create value creation opportunities and can therefore generate significant returns on investment

What is the difference between data science and big data?

Big data is about speed, variety, and volume of information. On the other hand, data science will provide the technologies to exploit this data. They also differ in the tools used. Big data analytics refers to quantitative storage





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