DATA SCIENTIST/ENGINEER
Ingénieur en Informatique Médicale et Big Data.
Multi compétences : Statistiques, Informatique et Biologie et Data Sciences/Data Engineering
The Hadoop & Spark Ecosystem (3 ECTS)
HDFS – scheduling & resources management – workflow management & ETL – dataflow management – scalable enterprise serial bus – real time processing – machine learning – data exploration & visualization
Applied Data Science & Artificial Intelligence - 150hrs (10 ECTS)
Deep Learning with Python (2 ECTS)
Introduction to PyTorch – deep learning – neural architectures & their applications – neural network training on a GPU (practice)
Advanced Statistical Analysis & Machine Learning (2 ECTS)
CART & random forests & applications to MapReduce – features selection & engineering – models comparison & competition
Survival Analysis using R (2 ECTS)
Probabilistic description of survival data – parametric / non-parametric / semi-parametric (Cox model) statistical methods – Applications to Big Data with penalised Cox regression
Agent-Based Modeling for Population Behaviour (1 ECTS)
Modelling objectives – model types – matching modelling approaches to studies objectives – ODD protocol – ABM objectives & components
Semantic Web for Data Science (1 ECTS)
Representing & querying web-rich data (RDF, SPARQL) – introducing semantics in data (RDFS, ontologies) – tracing & following data history (VOiD, DCAT, PROV-O)
Management, Ethics & Law – 50hrs (2 ECTS)
Data Regulations MEL1 (1 ECTS)
Data ownership and protection laws and regulation: Private Data – Corporate Data – EU Data Protection Act, GDPR, US-EU Data Transfers regulations
Project Management MEL2 (1 ECTS)
Project Management: PMP-PMI and Agile Approaches: PMBOK (PMI) – Agile Approaches – Kanban