Program Overview

Data Science and Modeling

CERTIFICATION

This training corresponds to a block of competences whose title reads "Artificial Intelligence Project Manager", currently under instruction at France Compétences. It will lead to a certification recognized and registered in the Répertoire national des certifications professionnelles (RNCP) and will therefore be eligible for the CPF.

This certification can be capitalized on over 5 years. You can choose to prepare the entire title progressively over time or have your complementary skills recognized by the VAE.

Performance indicators 2022/2023

• Satisfaction rate: 100%
• Diploma presentation rate: 100%
• Diploma success rate: 100%

TARGET AUDIENCE AND PRESENTATION

This program is designed for professionals in the field of data science and computer science, or for any scientist and any technical or managerial profile with prior knowledge in linear algebra, probability, statistics and programming (Python), and who wish to acquire operational skills in data science and machine learning. This program teaches how to ethically and responsibly deploy artificial intelligence solutions. This program also aims to strengthen and foster collaborations between scientific teams and business departments.

OBJECTIVES

This training will allow you to acquire:

• The skills to implement data solutions, strategic for your company.
• Concrete experience with machine learning models and their applications to give a new dimension to your company.
• The acquisition of a critical look at today's issues related to artificial intelligence, and in particular its ethical, legal and social stakes.

CONTENT

• Module 1: Data-driven Decision Making Take control of data visualization, exploratory data analysis, then exploit the power of data and its role in corporate decision-making. The main concepts covered in this module are: decision making using data, data cleansing, data coding and data visualization using Python.
• Module 2: Classical machine learning algorithms To learn to know and use the fundamental techniques of machine learning, and to know how to gauge the impact of such tools in a company. The main concepts covered in this module are: time series, clustering (data partitioning), and regression methods using scikit-learn.
• Module 3: Ethics, bias and limitations of the learning machine Explore the main challenges of machine learning, and the ethical and legal considerations of data use in the business world. The main concepts covered in this module are: model evaluation, performance analysis, overlearning vs. underlearning, data augmentation, ensemble methods, and the ethical, legal and social issues of data use.

TRAINERS / TEACHERS

• Doreid Ammar Expertise: Data science Professor in Data science and Computer science | Academic Director
• Virginie Mathivet Expertise: AI & Deep learning Expert AI & Deep learning teacher | Director of R&D, Corporate Teamwork
• Levente Szabados Expertise: Data science Visiting professor in Data science | Lecturer at Frankfurt school of finance & management

Data Science and Modeling

• Prerequisite Good knowledge of mathematical tools (linear algebra, probability, statistics) and programming (Python).
• Location Cachan
• Duration of the training 12 days
• Awards 5 600 € excl. tax