Artificial Intelligence and Data Science

Explore the programs and courses offered by Artificial Intelligence and Data Science

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Program Overview

The Artificial Intelligence and Data Science specialty is an attractive and constantly evolving field, offering highly sought-after skills that allow graduates to work in sectors with high innovation potential. With comprehensive training, practical projects, and a multidisciplinary approach, this specialty prepares students for exciting careers at the intersection of technology, data, and artificial intelligence.

Future engineers will be able to:

  • Design and implement systems based on artificial intelligence techniques.
  • Develop Big Data solutions using the latest AI techniques, Machine Learning, and distributed architectures.
  • Store, extract, analyze, and leverage large volumes of data for various professional/academic goals such as decision-making, evaluation, optimization, prediction, etc.

The duration of this specialty is two years, plus one year of common foundation with other specialties.

Teaching Language : English and French

Curriculum Highlights

Core Courses

1.      Advanced Technical Training

The AI and Data Science specialty provides a solid and complete technical training in key areas of computer science. Students gain in-depth knowledge of:

  • ·        Machine Learning, Deep Learning, and Natural Language Processing: Machine Learning and Deep Learning are central to this specialty, with applications ranging from image recognition to automated decision-making.
  • ·        AI tools and frameworks: Mastery of programming languages like Python, Java, and AI frameworks such as TensorFlow, PyTorch, or Keras used in creating models and developing AI algorithms.
  • ·        Algorithms and optimization: Students learn to design and optimize algorithms to process massive datasets efficiently.

2.      Practical Applications and Research Projects

This specialty places a strong emphasis on the practical application of the concepts studied. Students work on real Data Science projects, where they must collect, clean, analyze, and interpret data. These projects often involve using:

  • ·        Big Data and high-performance computing: Managing large data volumes and using technologies like Hadoop or Spark.
  • ·        Data visualization: Advanced techniques for representing data and analysis results using tools like Tableau, PowerBI, or Python libraries (matplotlib, seaborn).
  • ·        Real-world case studies: Students collaborate with companies or institutions to solve concrete problems in various fields such as healthcare, finance, robotics, or cybersecurity.

3.      Interdisciplinary Approach

AI and Data Science are highly interdisciplinary fields, and this specialty integrates skills from various disciplines, such as:

  • ·        Mathematics: Statistics, probability, linear algebra, and optimization to model phenomena.
  • ·        Information and systems theory: Studying how to represent and manipulate information optimally.

Advanced Topics

This specialty prepares students for technological innovations and advanced research in rapidly evolving fields. AI and Data Science applications are continuously developing, and students have access to the latest research on topics like:

  • Reinforcement Learning
  • Computer vision and image processing
  • Cloud and Fog computing
  • Network Sciences
  • Ethical and responsible AI: How to build transparent, fair, and responsible AI systems with societal implications.


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Admissions Information

Access to the first semester of the first year of the proposed program is reserved for students who have successfully completed two years of preparatory computer science education, subject to available teaching spots.

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