The program is composed of 240h of classes, shared between the following modules:
- Foundations in Decision Making (FSD301)
60h in Statistics, Optimization and Decision Theory
- Algorithms in Machine Learning (FSD311)
80h in Advanced statistical modeling, Supervized, Unsupervized and Reinforcement Learning
- Tools of Big Data (FSD313)
50h in Data integration, databases, functional programming, Spark, GPGPU and cloud computing
- Digital economy and data uses (FSD312)
15h on the business models in the digital economy, privacy and security issues.
- In-depth modules (FSD312)
15h in parallel modules for expanding understanding in a specific topic.
- Hackathon (FSD314)
3 days intensive project on a real-world Data Science challenge (count as a 20h class).
- Seminars (FSD319)
Interventions from professional experts, academics, short off-cursus training sessions, challenges.
This program is complemented by a 6 months internship in top-notch labs or companies.
Foundations in Decision Making (FSD301)
60 hours of classes on:
- Decision Theory (multi-criteria, multi-sources, collective decision making, uncertainty modeling)
- Statistics (descriptive, exploratory, inference)
- Combinatorial Optimization (Complexity analysis, Constraint Programming, Graph-based Optimization - prerequisites: Mixed Integer Linear Programming, Non-linear Programming)
- Stochastic Optimization (Simulated Annealing, Evolutionary Strategies, Genetic Algorithms)
Algorithms in Machine Learning (FSD311)
80 hours of classes on:
- Advanced statistical modeling
- Unsupervized and Supervized Learning Algorithms (k-means clustering, Hierarchical clustering, Naives Bayes classification, Gaussian Processes, Support Vector Machines, kernel methods, Boosting, Bagging, Random Forests, Statistical Learning Theory)
- Deep Learning (Neural Networks, CNNs, computer vision, NLP, )
- Reinforcement Learning and Markov Decision Processes (model based and model-free, online, offline, Monte-Carlo tree search, Deep RL)
50 hours of classes on:
- Cloud computing and virtualization
- GPGPU computing
- Functional Programming
- Distributed computing with Hadoop, Spark, and Dask
- Database Management Systems (Relational DBMS, PostgreSQL, NoSQL ecosystem)
Digital Economy and Data Uses (FSD312)
15 hours of classes on:
- Business models in the digital economy
- Data security and privacy issues
SDD In-Depths (FSD312)
15 hours given in parallel and chosen by students on:
- Business Intelligence (Problem modeling, data understanding and visualization)
- Computer Vision
- Reinforcement Learning
- Data security and privacy issues (Homomorphic encryption)
Autonomy and agility on a real-world challenge in Data Science with external validation.
Counts as a 20 hour class.
All year long, by academics and professional experts.
Short off-cursus training sessions.
Challenges: Kaggle competitions, mini-hackathon and capture the flags.
6 months, with academic validation.