Second-Year Program

Overview

It is the year during which advanced statistical concepts are introduced and strengthened by practical applications. Specialized courses covering different types of data are offered: temporal data, duration, economic data, Big Data… The year is also characterized by two major projects: one in computer science, and the other in statistics. Students gain greater autonomy, and elective courses are available to prepare for their 3rd-year specialization (engineering students) or the start of their career (civil servant students). The second semester is marked by a stronger emphasis on English-language courses. 

Following feedback from company partners and INSEE on the importance of English in students’ training, the school decided to implement a second semester in English, with several courses freely chosen by students. The aim is to give all students the opportunity to follow a curriculum in English during an “international” semester, whether they are on an exchange program or not. The introduction of this English-language curriculum is also intended to enable our European partners to send us more students, and thus perpetuate our Erasmus agreements. For engineering students, the year concludes with a 2 to 3-month application internship in statistics. 

Fields of study

Apart from a few highly specialized courses in the third year, courses can be grouped into four main areas:

  • Mathematics, probability, and statistics
  • Computer science
  • Economics and social sciences
  • Humanities
MATHEMATICS, PROBABILITY, STATISTICS

Statistics is an integral part of applied mathematics. The second year focuses on learning techniques useful to the professional statistician: parametric or non-parametric regression modeling, the study of time series modeled by the Box-Jenkins method, survey theory, the analysis of discrete choice models, supervised learning, Markov chains, Bayesian calculations, duration models. Depending on the student's status and choices, these foundations are supplemented by an introduction to stochastic processes, courses in non-parametric regression methods, resampling, time series complements, mathematical statistics, mapping or advanced sampling.

A statistical project, supervised by professionals and operating in small groups, enables students to apply a wide range of the techniques studied in the first two years to real data. Students can also take part in a Data Challenge.

COMPUTER SCIENCE

At the start of the second year, all students carry out a project designed to put into practice what they have learned in the first year, as well as additional IT training on database management in Web and/or Big Data contexts.

In the second semester, engineers take an object-oriented programming course in C++ or Java, as well as an introduction to Big Data tools. Several optional courses are offered in computer science, advanced R, mobile technologies, software design, signal processing, and data visualization. Additional IT tools (R Shiny, VBA, Libre Office Basics, SAS Complements) are offered without ECTS.

ECONOMICS AND SOCIAL SCIENCES

The aim of the economics, management, and social sciences courses is to give all students a real ability to analyze and understand the essential aspects of the contemporary world, through the mobilization of economic modeling and data derived from human behavior.

In the second year, the core econometrics course aims to provide students with methods for the empirical validation of theoretical models. This course can be supplemented in the second semester by courses in applied micro and macroeconometrics. Elective courses round out the curriculum, covering topics such as risk economics, industrial economics, contract economics and financial economics.

HUMANITIES and soft skills

For our Data Scientists or public statisticians, the notion of competence refers to autonomy and the ability to act in the field of data production and analysis, and decision-making in complex situations (non-repetitive tasks). Knowledge of mathematics, computer science, statistics and economics (ENSAI's DNA) forms the essential foundation for the training of a competent Data Scientist. Cross-disciplinary skills, or Soft Skills, are also essential to make the most of the potential acquired during the 3 years at ENSAI in a professional context.

The school has produced a set of skills adapted to the future careers of the students it trains. A Data Scientist is expected to display important qualities in the following areas: intellectual rigor, analytical reasoning and conceptualization, creativity and a sense of innovation, communication and pedagogy, human relations, teamwork in project mode and time management, openness to the world and social and civic responsibility. These qualities are put to work in the various learning processes: courses, practical work and personal work.

The school has chosen to focus specifically on building students' skills in "knowing how to act", mainly through situations that are as close as possible to professional situations: projects, Data Challenges, internships and associative activities.

Communication techniques and project management are taught progressively, based on practical experience and personalized advice. Students are introduced to these skills as part of the descriptive statistics project in the first year, and then develop them by working on the projects that punctuate their studies, in particular the second-year statistics project, the second-year IT project and the third-year statistics project.

The "Professional Project" in the second and third years enables students to get to know themselves better, in particular through the use of a personality test widely used in recruitment, to enhance their skills in their search for an internship or a job by preparing the supporting documents for their applications, and to put their scientific and behavioral skills into practice during their statistics application internship and their end-of-study internship.

The study of English is compulsory throughout the school year. Students are divided into groups of varying levels, to ensure appropriate content and pedagogy. TOEIC preparation modules are integrated into the courses, but the acquisition and development of linguistic and communicative skills remain the main objectives. Level B2 of the CEFR is compulsory to obtain the engineering diploma, but the courses aim to acquire level C1. In addition to language skills, English courses aim to equip future engineers with the cross-disciplinary skills that will enable them to operate in a variety of international contexts, keep abreast of scientific developments and understand cultural norms in foreign countries. Humanities courses aim to deepen students' knowledge of several disciplines in the arts, social sciences and humanities. By virtue of their structure and content, they enable students to develop cross-disciplinary skills, notably those linked to openness to the world and social and civic responsibility.

Students can choose from two types of course:

Optional languages: Chinese, German, Italian, Japanese, Russian and Spanish can be studied from A1 to B2+ level. In addition to language and communication skills, optional language courses aim to prepare future engineers to operate in multicultural contexts.

In the 2nd year, the opening course is replaced in the first semester by two compulsory courses: sustainable development/ESR (12 hours of classes) and 12 hours of classes on ethics). For S2, several options are organized. Some courses focus on general culture (geopolitics, art history, philosophy...), while others stimulate creativity and self-awareness through artistic practice (drawing, music, painting, theater...). Finally, the possibility of taking part in associative activities or special projects encourages social and civic commitment.

Courses

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Program
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