Olivier Doubiani

Core Data Science & Artificial Intelligence – 150hrs (9 ECTS)
Applied Mathematics (1 ECTS)
Calculus – Linear Algebra – Trigonometry & Complex Numbers
Continuous Optimisation (1 ECTS)
Critical points – multiple variables function optimisation – gradient methods – constraint-based optimisation with Lagrange Multipliers
Foundations of Statistical Analysis & Machine Learning Part I & II (2 ECTS)
Probabilities & distribution – tests – inference – regression – clustering
Artificial Neural Networks (1 ECTS)
Data representation & distributed representations – universal interpretation theorem – probabilistic interpretation – backpropagation & stochastic gradient descent
“The SAS Ecosystem DSTI Chair” (3 ECTS)
Preparation for SAS Certified Predictive Modeler using SAS Enterprise Miner 14: SAS/Base & SAS/STAT
Time-Series Analysis using SAS (1 ECTS)
Forecasting using SAS Software: a programming approach (SAS/ETS)
Core Data Engineering – 250hrs (9 ECTS)
Software Engineering (2 ECTS)
Classical design & programming – object-oriented design & programming

Data Wrangling with SQL (1 ECTS)
Advanced SQL queries – dynamic SQL – stored procedures & triggers

Amazon AWS “Cloud-Computing DSTI Chair” (3 ECTS)
Preparation for AWS Certified Solutions Architect – Associate

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

Discrete Optimisation (2 ECTS)
Graph-based modelling & algorithms

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