Data and Decision Sciences🔗
The Data and Decision Sciences program is a Master-level specialization in Data Science, modern Artificial Intelligence and Decision Support at ISAE-SUPAERO.
Syllabus🔗
The program is composed of the following modules:
-
Fundamentals of Decision Making (FSD310)
47 hours on data engineering fundamentals, statistics, and optimisation -
Machine Learning (FSD311)
77 hours on supervised, unsupervised, deep, and reinforcement learning -
Data Engineering (FSD312)
60 hours on data storage, computation, and distribution -
Applied Data Science (FSD313)
55 hours on data privacy and ethics, the digital economy, and applications of data science -
Seminars (FSD319)
Seminars from professional experts, training sessions, and challenges
This program is complemented by a 6 months internship in data science.
Courses details🔗
Fundamentals of Decision Making (FSD310)🔗
| Course title | Coordinator | Volume | Content |
|---|---|---|---|
| Data Engineering Fundamentals | Christophe Huet | 10h | Capture the Flag: Linux, Git, SSH, Python and NumPy |
| Statistical Models for Decision Making | Benjamin Bobbia, Laurent Risser | 24h | Descriptive Statistics, Probability, Linear Models, Regression Analysis, Mixed-Effects Models |
| Optimisation for Decision Making | Zoé Krug | 13h | combinatorial, stochastic, and continuous optimisation, with automatic differentiation |
Machine Learning (FSD311)🔗
| Course title | Coordinator | Volume | Content |
|---|---|---|---|
| Unsupervised and Supervised Learning Algorithms | Jonathan Sprauel | 23h | SVM, Bayesian classification, Gaussian Processes, Decision Trees, Boosting, Bagging, Anomaly Detection |
| Deep Learning | Axel Carlier | 39h | ANN, CNN, RNN, Transformers, LLM, RAG |
| Reinforcement Learning | Valentin Guillet | 15h | MDP, Bellman equation, Value function, Deep Q-Learning, Actor-Critic |
Data Engineering (FSD312)🔗
| Course title | Coordinator | Volume | Content |
|---|---|---|---|
| GPGPU | Laurent Risser | 6h | |
| Data Storage | Hugues Larat | 12h | SQL, PostGreSQL, ETL |
| Data Security | Marina Dehez-Clementi | 9h | |
| Cloud Systems | Axel Carlier | 18h | Cloud computing, GCP, virtualization, containerization, Docker |
| Cloud Data Engineering | Guillaume Eynard-Bontemps | 21h | MapReduce, Hadoop, Spark, Orchestration, Kubernetes, Dask |
Applied Data Science (FSD313)🔗
| Course title | Coordinator | Volume | Content |
|---|---|---|---|
| AI, Law and Ethics | Ronan Pons | 9h | Data privacy, GDPR, European AI Act |
| AI Business models | Lionel Rigaud | 10h | SQL, PostGreSQL, ETL |
| Hackathon | Axel Carlier | 21h | |
| In-depths | Axel Carlier | 15h | computer vision, business intelligence, and reinforcement learning |
Seminars (FSD319)🔗
Seminars given throughout the year on data science topics by academics and professional experts, challenges like Kaggle competitions, and more.