Executive Master’s Applied Data Science and Artificial Intelligence

The Executive Master's in Applied Data Science and Artificial Intelligence aims to provide executives and professionals with a comprehensive understanding of the concepts, techniques, and tools related to data science and artificial intelligence (AI). Participants will acquire the technical skills necessary to work with data, analyze it, and effectively leverage AI technologies. This program enables participants to apply data science and AI methodologies to make data-driven decisions in various professional contexts. They will learn to use data analysis techniques to extract insights, predict trends, optimize processes, and solve complex problems, while also exploring emerging technologies and identifying new business opportunities.

The Executive Master's in Applied Data Science and Artificial Intelligence is designed to equip executives and professionals with mastery of the principles, methodologies, and tools of data science and AI. The program provides practical skills for data analysis, AI model development, and the application of AI-based solutions in professional environments. The program emphasizes real-world applications, enabling participants to leverage data science and AI to address business challenges, improve operational processes, and make data-driven decisions. Additionally, it encourages the exploration of new technologies and fosters innovation to drive business growth.

Comprehensive Knowledge: Gain a solid understanding of the principles of data science and AI, including machine learning, image analysis, natural language processing (NLP), and Big Data technologies.
Practical Application: Learn how to apply AI techniques to solve real-world problems, optimize processes, and make strategic, data-driven decisions.
Hands-On Experience: Acquire practical skills using popular tools and libraries such as Python, TensorFlow, and Hadoop.
Data-Driven Decisions: Develop the ability to lead data-centric projects and make informed decisions to enhance business outcomes.
Emerging Technologies: Explore cutting-edge technologies in AI and data science and learn how to adapt them for practical use in various contexts.

The program covers a comprehensive range of topics related to data science and artificial intelligence, enabling participants to develop strong skills for data analysis, processing, implementing machine learning models, and working with Big Data systems. Key areas include:

Data Science and Analytics: Master concepts and techniques for data analysis, visualization, and statistical modeling to extract valuable insights.
Applied Machine Learning: Learn supervised and unsupervised learning algorithms, as well as advanced techniques such as neural networks and deep learning.
Computer Vision and Image Analysis: Explore image processing techniques, feature extraction, object detection, and image recognition.
Natural Language Processing (NLP): Work with textual data, including sentiment analysis, machine translation, and chatbot development.
Big Data Technologies: Understand Big Data systems and tools such as Hadoop, MongoDB, and NoSQL to manage and process large datasets.

1. Data Science and Analytics

Introduction to the concepts and methods of data science, including data analysis, visualization, and statistical modeling. Participants will learn to use popular tools to solve problems and make data-driven decisions.

2. Applied Machine Learning

This module delves into machine learning algorithms, both supervised and unsupervised, as well as advanced topics such as deep learning and neural networks. The focus is on practical implementation using Python and popular libraries.

3. Computer Vision and Image Analysis

This course covers the fundamentals of image processing and computer vision, including feature extraction, object detection, and image recognition, using real-world algorithms and tools.

4. Natural Language Processing (NLP)

An in-depth exploration of challenges related to textual data, including language modeling, machine translation, sentiment analysis, and chatbot development. The course also features practical case studies.

5. Big Data Technologies

Participants will explore the architectures and tools used in Big Data systems, with an emphasis on leveraging technologies such as Hadoop, MongoDB, and NoSQL for processing and managing large-scale datasets.

Academic Background: A bachelor's degree (Bac+4 or Bac+5) in engineering, mathematics, computer science, or a related field.
Professional Experience: Experience in data analysis, computer science, or a related field is recommended.
Language Proficiency: Proficiency in French is required to follow the program.
Selection Process: Candidates will be selected based on their academic qualifications, professional experience, and motivation.

Module Assessments: Each module includes evaluations such as quizzes, assignments, and case studies to measure participants' understanding.
Final Project: Participants will be assigned a final project where they must apply the concepts learned to solve a real-world problem. This project will be evaluated by the faculty members.
Certification: Upon successfully completing all modules and assessments, participants will receive a certificate in Applied Data Science and Artificial Intelligence.