Criteria and Admission Procedure
Prerequisites
Eligibility Conditions:
- A general baccalaureate from the French secondary education system, obtained in France or abroad, or a foreign diploma with recognized equivalence, with strong academic results across all subjects.
- Completion of advanced mathematics courses and at least one advanced science course (physics, computer science, biology, etc.).
- Proficiency in English at level C1 according to the Common European Framework of Reference for Languages (CEFR).
Expectations
Candidates for the IBSAI Bachelor program must:
- Show a strong intellectual curiosity for sciences, technologies, and their interdisciplinary applications.
- Demonstrate solid skills in mathematics and an advanced scientific discipline (analysis, modeling, problem-solving).
- Possess the ability to engage in rigorous reasoning, as well as strong organizational skills and the capacity for thorough work.
- Have an excellent level of written and spoken English (minimum C1).
Application Procedure
Selection based on application file.
- Admissions are conducted through Parcoursup (according to the national calendar) or via the Etudes en France platform for eligible candidates, in accordance with the regulations for first-time enrollment in the first year of a bachelor’s degree in France.
- Applications are evaluated based on academic criteria, language proficiency, and the candidates’ motivation.
Required documents in the application file:
For high school seniors:
- First and final year report cards (available terms for future 2025 baccalaureate graduates)
- Results of the preliminary Baccalaureate exams (French).
- A motivation letter explaining the interest in the IBSAI Bachelor program.
- “Fiche Avenir” (Future Sheet)
For candidates who already hold the baccalaureate, also include:
- Third-term report card from the final year
- Baccalaureate transcript
- Higher education transcripts (if applicable).
For international candidates (in high school or higher education), also include:
- Certified translation of transcripts
- Proof of English proficiency (TOEFL, IELTS, or equivalent).
General Criteria for Reviewing Applications (CGEV)
Applications will be evaluated based on the following elements:
Academic Results:
- Level in mathematics and an advanced scientific discipline.
- Progress in results over the past few years.
Skills and Competencies:
- Ability to analyze, model, and solve complex problems.
- Autonomy, organization, and work methods.
Attitude and Motivation:
- Curiosity about artificial intelligence and interdisciplinary sciences.
- Alignment between the expressed project and the objectives of the program.
- Quality of written and spoken English.
Organization and Composition of the Recruitment Committee
The recruitment committee is chaired by the director of the IBSAI Bachelor program, accompanied by the program’s academic coordinators. It includes faculty members and professionals from the disciplines covered by the Bachelor program.
Your 1st Year of Bachelor in AI
Fall semester
| Course Type | Course Title | Syllabus Overview |
|---|---|---|
| Transverse Courses | 1) Languages 2) A Healthy Mind in a Healthy Body 3) Principles of Economics 1 | 1) French (Beginner to Advanced based on placement test). Focus on communication skills, grammar, and cultural integration. 2) Physical education and mental health strategies. Emphasis on balancing academic pressures with physical fitness and mindfulness. 3) Core project: https://www.core-econ.org |
| AI-focused Courses | Introduction to AI | Overview of AI fundamentals: history, applications, ethical implications. Topics include machine learning, neural networks, and automation. |
| Foundations of AI | 1) Math in Practice: Calculus 2) Math in Practice: Mathematical Reasoning & Writing 3) Algebra 1 4) Analysis 1 5) The Art of Computer Programming 1 6) Climate fresk 7) Introduction to Statistics | 1) Introduction to calculus with applications in AI. Topics include limits, differentiation, and integration techniques. 2) Formal reasoning and proofs, mathematical writing skills, and logical deduction. 3) Linear algebra foundations: vector spaces, linear transformations, matrices, and systems of equations with AI applications. 4) Real analysis: sequences, limits, continuity, derivatives, and their applications in AI algorithms. 5) Introduction to computer programming with a focus on algorithms, data structures, and object-oriented programming using Python or C++. 7) Fundamental concepts in probability and statistics, including probability distributions, hypothesis testing, and statistical inference. |
Spring semester
| Course Type | Course Title | Syllabus Overview |
|---|---|---|
| Transverse Courses | 1) Principles of Economics 2 2) Law and Tech 3) Meet the AI Innovators 4) Languages | 1) Core project 2) Overview of legal frameworks surrounding AI and digital technologies. Topics include IP law, data privacy, and regulatory challenges. 4) Continuation of language studies with a focus on technical and academic vocabulary for AI students. |
| AI-Focused Courses | 1) Machine Learning 101 2) ML Project | 1) Continuation of language studies with a focus on technical and academic vocabulary for AI students. 2) Hands-on project applying machine learning techniques to a real-world problem. Includes data analysis, model building, and evaluation. |
| Foundations of AI | 1) Analysis 2 2) Algebra 2 3) Introduction to Probability 4) Database Management 5) The Art of Computer 6) Programming 2 | 1) Further study of real analysis, including complex functions, integration, and series. Applications in AI and optimization. 2) Continuation of Algebra 1 with advanced topics: eigenvalues, eigenvectors, and spectral theory in AI. 3) Core probability theory, including discrete and continuous distributions, expected values, and Markov chains. Applications in AI. 4) Principles of database design, SQL, and database management systems (DBMS) with a focus on data for AI applications. 5) Advanced programming concepts, parallel computing, and algorithmic efficiency in AI. |