Description

The course  provides students with a comprehensive introduction to the field of data science, covering key concepts, methodologies, and techniques used for extracting insights and knowledge from large and complex datasets.

Through a combination of theory and practical exercises, students will gain hands-on

experience with data manipulation, exploratory data analysis, statistical modeling, machine learning, and data visualization, equipping them with the necessary skills to tackle real-world data-driven problems.

Compétences requises

Upon completing this course, students will have acquired the following skills:

• Proficiency in data manipulation, preprocessing, and exploratory data analysis techniques
• Understanding of statistical modeling concepts and their application to real-world problems
• Knowledge of fundamental machine learning algorithms and their implementation
• Familiarity with deep learning principles and techniques

• Competence in using data visualization tools and creating effective visual representations
• Ability to apply data science techniques to solve real-world problems
• Awareness of ethical considerations and data privacy issues in data science

Compétences visées

Upon completing this course, students will have acquired the following skills:

• Proficiency in data manipulation, preprocessing, and exploratory data analysis techniques

• Understanding of statistical modeling concepts and their application to real-world problems

• Knowledge of fundamental machine learning algorithms and their implementation

• Familiarity with deep learning principles and techniques

• Competence in using data visualization tools and creating effective visual representations

• Ability to apply data science techniques to solve real-world problems

• Awareness of ethical considerations and data privacy issues in data science

Contacts

Responsable(s) de l'enseignement

• Samer El Zant